0709-SpecialReport vol 16 2010.7.20 9:45 AM 페이지1 열림4 HP-LaserJet-A3
Volume 16 KRIHS SPECIAL REPORT 2010 0709-SpecialReport vol 16 2010.7.20 9:45 AM 페이지2 열림4 HP-LaserJet-A3
KRIHS SPECIAL REPORT 2010
Copyright � 2010 Korea Research Institute for Human Settlements
All rights reserved. Printed in the Republic of Korea. No part of this publication may be reproduced in any manner without written permission from KRIHS except in the case of brief quotations embodied in critical articles and reviews. For more information, please address inquiries to: Korea Research Institute for Human Settlements, 224 Simin-ro, Dongan-gu, Anyang-si, Gyeonggi-do, 431-712, Korea.
Tel: +02.31.380.0114 Fax: +82.31.380.0470 Website: http://www.krihs.re.kr
p.cm Includes bibliographical references ISBN 978-89-8182-705-2 0709-SpecialReport vol 16 2010.7.20 9:45 AM 페이지3 열림4 HP-LaserJet-A3
KRIHS SPECIAL REPORT 2010 Contents
The Development of Transportation Infrastructure in Korea: Retrospect and Prospect ______Il-ho Chung
1. Introduction 12 2. Features of the Transportation Infrastructure 13 3. Korea’s TI Development Policy Changes and Achievements 15 4. Condition Change Outlook and Tasks for Korea’s TI Development 25 5. Conclusion 35 Bibliography 36
Climate Change and Sustainable Land Management Strategies in Korea - Focusing on Greenhouse Gas Inventories by Region ______Yeong-kook Choi, Jin-kyu Chung, Eun-sun Im, Ou-bae Sim, Myung-soo Kim, Moon-woun Lee, Kwang-ik Wang, Yeon-mi Seo, Jung-eun Park
1. Introduction 38 2. Review of Previous Studies 41 3. Methods to Estimate Greenhouse Gas Emissions by Region 42 4. Status and Characteristics of Greenhouse Gas Emissions by Region 69 5. Utilization of Inventories for Sustainable Land Management 77 6. Conclusion 75 Bibliography 81
Applications of KOPSS (KOrea Planning Support Systems) ______Eun-sun Im, Dae-jong Kim, Gyoung-ju Lee, Young-joo Lee, Kirl Kim, Yoon-young Jeong, Jong-duk Park
1. Overview 90 2. Regional Planning Support Model: REPSUM 96 3. Land Use Planning Support Model 101 4. Urban Regeneration Planning Support Model 107 5. Application of the Urban Public Facility Planning Support Model 113 6. Applications of the Landscape Planning Support System 119 Bibliography 124 0709-SpecialReport vol 16 2010.7.20 9:45 AM 페이지4 열림4 HP-LaserJet-A3
Authors
The Development of Transportation Infrastructure in Korea: Retrospect and Prospect
Il-ho Chung Research Fellow. Ph.D. in Transportation Planning and Engineering, University of Leeds, UK. Recent research works include「 The Development of Nationwide Road Network System(I)」(2007),「 Economic Appraisal Guidelines for Public Investment of Infrastructures」(2007),「 A Study on Enhancing the Acceptability of Road Congestion Pricing Policy」(2006),「 Feasibility Study on Honam Express Railway Construction」(2005), and「 The Development of Partnership between Central and Local Government to Promote the Construction and Operation of Transport Facilities」(2004). His major research concern has been for transport feasibility studies and network evaluation of expressway and railway since 1985. He is currently an acting member of some government commissions of the Ministry of Land, Transport and Maritime Affairs, Ministry of Planning and Budget, and Director of the Center for Road Policy Research.
Climate Change and Sustainable Land Management Strategies in Korea - Focusing on Greenhouse Gas Inventories by Region
Yeong-kook Choi Senior Research Fellow. Ph.D. in Landscape Architecture, Agricultural University of Norway, Norway. Major Research works include「 Climate Change and Sustainable Land Management Strategies in Korea」(2008), 「Category Classification and Systematic Management of Protected Areas for Effective Territorial Resources Management」(2007),「 Strategic Assessment Indicators and Prototype for their Application to Green Belts: Evaluating a New Public Facility on a Green Belt Land」(2007),「 A Diagnosis of Environmental Degradation and Practical Countermeasures: Focusing on Planning Process and Institutionalization」(2006), and「 Basic Strategies for 0709-SpecialReport vol 16 2010.7.20 9:45 AM 페이지5 열림4 HP-LaserJet-A3
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Promoting Resident-oriented Eco-tourism based on In-depth Interviews and Case Studies」(2005).
Jin-kyu Chung Research Fellow. Ph.D. in Urban Studies, Portland St. University, USA. Interested fields are transportation & land use, metropolitan & urban transportation planning, telecommuting, and planning theory. Major project experiences include「 Rational Financing System for Metropolitan Transportation Planning in Large-Scale Land Development」(2007),「 A Study of Supporting Construction of Infrastructure for Enterprise Cities」(2006),「 A Study of Factors for Telecommuting Facilitation」(2005),「 A Study of SOC Policy Making Systems for Metropolitan Areas」(2004),「 The Spatial Impact of the High Speed Rail and its Countermeasures」(2003), and「 A Study on the Factors of Transportation Energy Change in National Spatial Structure」(2002).
Ou-bae Sim Research Fellow. Ph.D. in Water Resources and Disaster Prevention, Hongik University. Recent research works include「 A Study on the Disaster-Prevention Urban Planning for the Creation of Safe City」(2008),「 Master Plan for Multifunctional Administrative City, Korea」(2006),「 Development Plan for Multifunctional Administrative City, Korea」(2006),「 Institutional Reform for Flood Management in Urban Area」(2006),「 Analysis of Flood Damage Traits through a Field Study and Policy Implications」(2006),「 GIS Application Methods for National Territorial Disaster Prevention(I)」 (2005),「 Application of the Strategic Environmental Assessment to National Territorial and Transportation Plans」(2005),「 Strategies for Water Management and Disaster Prevention」(2005), and「 A Study on the Efficient Management Method or Rainwater」(2005).
Myung-soo Kim Research Fellow. Ph.D. in Engineering, Seoul National University. Recent research works include「 Climate Change and Sustainable Land Management Strategies in Korea」(2008),「 Strategy of Multi-purpose Corridors for Human Health, Culture and Ecology(CHCEs)」(2008),「 Category Classification and Systematic Management of Protected Areas for Effective Territorial Resources Management」 (2007),「 Development Plan for Multifunctional Administrative City, Korea」(2006),「 Master Plan 0709-SpecialReport vol 16 2010.7.20 9:45 AM 페이지6 열림4 HP-LaserJet-A3
Authors
for Multifunctional Administrative City, Korea」(2006),「 Measures for Improving Urban Landscape Management System」(2005),「 Landscape Master Plan for Incheon Free Economic Zone(IFEZ), Songdo Area」(2005),「 Guideline for Ecological Corridor」(2005), and「 Green Master Plan of POSCO」(2005).
Moon-woun Lee Associate Research Fellow. Ph.D. candidate (All but dissertated) in Urban Engineering, University of Seoul. Recent research works include「 A Review of Historical Literature on Ulleungdo and Dokdo」(2009),「 Climate Change and Sustainable Land Management Strategies In Korea」(2008),「 A Study on the Disaster-Prevention Urban Planning for the Creation of Safe City」(2008),「 A Study on the Basic Plan for the Nakdong-river Project」(2008),「 Strategies to Create National Amenity Resources Enhancing Quality of Life」(2007),「 A Study on the Utilization and Project Making of Former Military Facility Sites」(2007), and「 Strategies for the Efficient Utilization of Tourism Resources in North Korea: Cooperative Measures for Pilot Tourism Projects in North Korea」(2006).
Kwang-ik Wang Associate Research Fellow. Ph.D. in Urban Engineering, University of Tokyo, Japan. MRP in State University of New York at Albany. Recent research works include「 Climate Change tackling through Urban Planning Method」(2009), 「Climate Change and Sustainable Land Management Strategies in Korea」 (2008),「 The Evaluation and Issues for Territorial Spatial Plan Against Climate Change」(2008), 「Future Urban Policy in Korea」(2008),「 A study on the Disaster-Prevention Urban Planning for the Creation of Safe City」(2008),「 Urban Regeneration Strategies to Improve the Environment of CBD Area」(2008),「 Master Plan for Wide Area of New Multifunctional Administrative City」 (2007), and「 Changes in the Spatial Structure of Metropolitan Regions amid Slow Population Growth and the Directions of Policy Responses: Focusing on Japan」(2006).
Yeon-mi Seo Associate Research Fellow. Ph.D. in Geography, Seoul National University. Major research works include「 Climate Change and Sustainable Land Management Strategies in Korea」(2008),「 Measures to Enhance Social Capital in the Field of National Territorial Management」(2008),「 Category 0709-SpecialReport vol 16 2010.7.20 9:45 AM 페이지7 열림4 HP-LaserJet-A3
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Classification and Systematic Management of Protected Areas for Effective Territorial Resources Management」(2007),「 A Study on Industrial Cluster Strategies of Gyeonggi Province」(2007),「 Internationalization and Localization of Korean SMEs in Silicon Valley」 (2007), and「 A Study on Cluster Development Strategy of Red Pepper Sauce Manufacturing in Soonchang」(2005).
Jung-eun Park Assistant Research Fellow. Master in Urban Planning, Kyungwon University. Recent research works include「 Climate Change and Sustainable Land Management Strategies in Korea」(2008),「 Strategy of Multi-purpose Corridors for Human Health, Culture and Ecology(CHCEs)」(2008),「 Category Classification and Systematic Management of Protected Areas for Effective Territorial Resources Management」(2007),「 Guidelines to a Plan for Industrial Site Supply」(2007),「 Decentralization Strategies and Policy Guidelines for Balanced National Development(II)」(2006),「 Territorial Policy in Overseas and Its Implications for Korea」(2006), and「 A Study on Energy Conservation Policy of Korean Cities」(2006).
Applications of KOPSS (KOrea Planning Support Systems)
Eun-sun Im Research Fellow of KRIHS. Ph.D. in Geography and Regional Sciences, Konkuk University, Korea. Major research fields are spatial analysis and regional science using GIS. Main research projects and studies include 「Development of Korea Planning Support Systems」(2006~2009),「 A Study on the Basic Frameworks of the National Territorial Policy Decision Support Systems」(2007), 「Measurement of Urban Form in Urban Growth Management : Urban Sprawl and Compactness」(2006), and「 Integrated Spatio-temporal Simulation Model for National Territorial Policy(I), (II)」(2005~2006). 0709-SpecialReport vol 16 2010.7.20 9:45 AM 페이지8 열림4 HP-LaserJet-A3
Authors
Dae-jong Kim Associate Research Fellow. Ph.D. in Geography, State University of New York at Buffalo, USA. Main research projects are「 Development of Korea Planning Support Systems」(2009),「 Ecological boundary-Setting in mental and geophysical models」(2008),「 Case study on the assessment of facility location in USA and development of agent-based model」(2007),「 Development of methodologies and models for monitoring land speculation」(2005),「 Development of national land management information systems」(1998 - 2003),「 Development of preliminary environmental suitability analysis system for land development」(2001),「 GIS applications in land use planning」(1998), and「 Sustainable land use plan of Jeju Island using GIS」(1995 - 1997).
Gyoung-ju Lee Associate Research Fellow. Ph.D. in Geography, State University of New York at Buffalo, USA. His research interests include spatial data analysis in statistical framework, Geographic Information Science (GIS), and urban and regional planning. He developed『 GeoSurveillance』software for spatial pattern analysis and spatiotemporal monitoring. He also worked with the National Institute of Health (NIH) for developing geographic disease simulation framework based on agent-based model. Currently, he participates in KOPSS (KOrea Planning Support Systems) project, National Territorial Simulation Model construction project, etc. in KRIHS.
Young-joo Lee Associate Research Fellow. Ph.D. in Media and Governance, Keio University, Japan. Recent research works include「 KOPSS (KOrea Planning Support Systems)」(2010),「 Establishment of Korean Spatial Data Infrastructure Model and Study of Globalization Strategy」(2009),「 Trends of the National Spatial Data Infrastructure: Focus on Comparative Analysis」(2008),「 Strategies of NGIS Preparation for Paradigm Shift in Geospatial Information」(2007),「 Study on Locational Strategy of Bank Channels using GIS: Case Study of the 3 Mega Banks in Tokyo 23 Wards」(2006), and「 A Study on the 3rd National GIS Master Plan」(2005). 0709-SpecialReport vol 16 2010.7.20 9:45 AM 페이지9 열림4 HP-LaserJet-A3
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Kirl Kim Associate Research Fellow, Ph.D. in Geography, Florida State University, USA. Recent research works include「 Master Plan on Saemangeum」(2010), 「A Case Study on Spatial and Temporal Distribution Patterns of Crime by Land Use」(2009),「 Migration Patterns of Low-Income Residents and Settlement Strategies in Urban Regeneration Projects」(2009),「 How to Institutionalize CPTED in Korea (I)」(2008), and「 The Policies to Promote Geo-Information Capacities of Local Authorities」.
Yoon-young Jeong Assistant Research Fellow. Master of Urban planning in Gyeongsang National University, Korea. Recent research works include「 KOPSS, KOrea Planning Support Systems」(2009),「 A Study of Development Planning for Designation of Five Specific Area Include Jirisan Cultural Area」(2009),「 Analysis of Housing Market in Jinju City by Housing Attributes and Price Function Model」(2008), 「Determinant Factors and Probabilities of House Type Choice-Case Study in Jinju City」(2008), and「 Analysis of Factors or House Type Choice and Calculation of Housing Demand」(2007).
Jong-duk Park Assistant Research Fellow. Currently, he is enrolled in Sangmyung University as a Master of Geography. Recent research works include「 Development of KOrea Planning Support Systems」(2009~2010),「 Development of Incheon Real Estate Guide System」(2009),「 Development of Saemangeum Environment Data Management System」(2007~2008),「 Standardization System for Emergency Rescue」(2006), and「 Development of National Inland Wetlands Biotope-map」(2005). 0709-SpecialReport vol 16 2010.7.20 9:45 AM 페이지10 열림4 HP-LaserJet-A3 0709-SpecialReport vol 16 2010.7.20 9:45 AM 페이지11 열림4 HP-LaserJet-A3
The Development of Transportation 01 Infrastructure in Korea: Retrospect and Prospect
KRIHS SPECIAL REPORT 2010
�Il-ho Chung 0709-SpecialReport vol 16 2010.7.20 9:45 AM 페이지12 열림4 HP-LaserJet-A3
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The Development of Transportation Infrastructure in Korea: Retrospect and Prospect
Il-ho Chung
1. Introduction
Transportation infrastructure is one of the key factors propelling national economic growth and regional development. Historically, countries with transportation networks connecting national territory in all directions to transcend spatial and time barriers have prospered economically. When travel time is reduced and travel expenses are slashed thanks to the development of transportation network, productivity improvement of goods and services follows. An advantageous position in terms of economy can also be seized compared to other surrounding countries. In particular, Korea can sustain the current high economic status in the world economic system because it has consistently invested in transportation infrastructure (TI) such as roads and railroads. For the past 50 years, the construction and operation of Korea’s TI have been carried out so rapidly we cannot find any precedent in the world. Bold and heavy investments in TI by concentrating national capability given the limitations of investment funds have been evaluated to have contributed greatly to regional development and social integration as well as national economic growth. Korea’s experience—wherein most of social efforts and investments are channeled into the construction, operation, and management of TI after understanding the importance of national TI as social asset from the early stages of economic development—is expected to benefit developing countries immensely. This report seeks to identify the difficulties in Korea’s TI sector and establish the policy direction for overcoming such difficulties as well as introducing Korea’s TI development strategies to help developing countries.
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2. Features of the Transportation Infrastructure
2.1 Characteristics of transportation infrastructure
Transportation Infrastructure provides a man-made environment to humans, and is an element hugely affecting regional economy, as well as providing benefits to the residents. It is also an important means for regional policy development. National competitiveness can also be referred to as regional and municipal competitiveness. TI can be somewhat similar to the natural environment like mountains and rivers in some ways, since it consistently offers benefits to humans from a set position. In addition, consumers tend to recognize TI as a given condition just like the natural environment and adapt themselves to TI the way they adapt themselves to the natural environment. In this context, understanding of TI is required as follows: First, the supply of TI is made exclusively, and uncertainties of transactions are high. This offers market participants—be they from the public sector or private sector—an environment conducive for rent seeking and opportunistic behaviors. Second, government regulations are established to address the incompleteness of transactions and contracts and shun evil practices of monopoly. Also, it is a worldwide trend to expand supply from the private sector to secure efficiency and transparency in the infrastructure market. The consolidation of government regulations in relation to TI supply, and the expansion of private sector participation in TI supply can be considered to achieve the same goal: creation of a competitive environment in the infrastructure market. Third, support systems and transparent corporate environment should be secured to establish a competitive system and ensure the feasibility of project selection and transparency of execution. To create such conditions, residents should be interested in government expenditures and participate in their execution. Also, for the participation of residents to produce some results, the residents themselves should be equipped with expertise. Lastly, role sharing between the government and private sector and resident participation to enhance the efficiency and transparency of supply should be directed toward minimizing transaction expenses and opportunistic behaviors.
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2.2 Ripple effects of TI construction and operation
Although the impacts of mobility and accessibility improvement arising from TI development have close correlations, there are generally many difficulties in sufficiently identifying such correlations in the planning and evaluating processes. First, there are no proper planning and evaluating techniques that can sufficiently consider the correlations between transportation development and regional development. Even though feedback on the improvement effects of mobility and accessibility should be continuously obtained in the evaluation process, such process will reach equilibrium state in the long run in reality; hence the impossibility of establishing an evaluation technique for realistic reflection. Second, since the impacts of supply and operation of TI have secondary and tertiary effects on communities, cities, and lands, judging and measuring the extent of transportation technology effects are difficult. Even more difficult is forecasting the effects because the process of manifestation of the effects is complicated. The primary, short-term, direct effects of TI development include the change in transport time and expenses, energy savings, or reduction in air pollutant emissions. On the other hand, the secondary, mid- and long-term, indirect effects are the various auxiliary effects such as change in land use and distribution structure of goods and services, tourist
Figure 2.1. Chain Effects of TI Supply and Operation
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attraction development, and regional development and creation effects such as residents’ exchange expansion; these effects induce secondary and tertiary chain effects. Consequently, a precise forecast of effect generation process and causal relationship needs to be made. In other words, prediction should be made on the cause of TI development, its effect according to time progression, and the beneficiaries of TI development.
3. Korea’s TI Development Policy Changes and Achievements
3.1 Retrospect of TI policies
If we look back at Korea’s TI development process, Korea invested heavily in national principal road network construction centered on expressways in the early 1970s. Nonetheless, the roads and railroads that had been built by colonial Japanese authorities to exploit Korea during the Japanese colonial age were destroyed during the Korean War. After that, handling the traffic volume with roads only became difficult as the number of passengers rapidly grew owing to the increase in the number of vehicles as an offshoot of economic growth. Thus, heavy investment in city train construction was made. Under Korea’s export-oriented economic structure, full-fledged investment has been made in ports and airports since the mid-1990s in an effort to consolidate national competitiveness for the smooth handling of export-import freight. By period, there were some changes in the TI investment basis. Still, Korea’s TI development process has been in line with the fast growth and development direction of the country’s economy. In other words, in the early stages of economic development, the function and role of TI as production base facilities were deemed important. After the 1990s when economic growth reached a certain level, TI was recognized as livelihood- based facilities that make our everyday life comfortable; the corresponding TI supply and investment policies have been established and executed accordingly. With the national economy adopting an export-oriented economic structure following economic growth through the Five-Year Economic Development Program on five occasions from 1962 to 1991, the demand for passengers and freight/cargo rapidly rose. In particular, excessive travel load began in the Gyeongbu axis connecting the Seoul
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Metropolitan Area and South Gyeongsang Region where large-scale industrial complexes are located including Pohang and Ulsan. Such gave rise to the social awareness that the rapidly increasing passenger and freight transportation demand in the economic growth process can serve as a snag in economic development if TI is not sufficiently supplied and operated in a timely manner. Supplying only demand- responsive infrastructure centered on solving bottleneck sections where traffic congestion is generated proved to be a limitation. Furthermore, the importance of systematic approach has been recognized in securing efficiency of investment in transportation by supplying transportation facilities considering the transportation network effects. Meanwhile, TI supply policy including roads, railroads, ports, and airports for the past 60 years has changed, with close relationships noted in the situation during those days. As Korea entered into the full-fledged economic growth age in the 1970s after the dawning of the industrialization age in the country in the 1960s, the construction of the Gyeongbu Expressway to respond provocatively to regional development and expected passenger and freight/cargo demand increases and aggressive investment in expansion projects for national highways became an opportunity for Korea to develop a national road network system. Cognizant of the fact that the urban traffic congestion problem cannot be solved through roads only, Korea concentrated on urban railroad construction and fortified the foundation for mass transportation infrastructure in large city regions. In the 1990s, Korea commenced the building of the Gyeongbu Express Railroad to solve the bottleneck problem of transporting passengers and freight/cargo on the Gyeongbu road axis. The development of the Incheon International Airport and Busan and Gwangyang ports was a socially inevitable decision in an effort to enhance national competitiveness through the smooth handling of export-import freight/cargo as well as the rapidly increasing number of international passengers following the deregulation of outbound travels in 1988. With Korea receiving IMF bailout assistance in 1997, a re-review of investment in large-scale national infrastructure building projects and the consolidation of investment evaluation guidelines have enabled measuring investment efficiency more thoroughly. In retrospect, the modernization of our transportation infrastructure has been relatively recent. The supply of transportation facilities in full scale started from the construction of expressways in the 1970s and urban railroads, which began in full swing in the latter part of the 1980s. Meanwhile, railroad construction between major regions has been carried out only partially except the Gyeongbu Express Railroad; investment in
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the construction and expansion of ports and airports was anything but huge. In particular, the lack of proactive transportation facility supply based on the forecast of transportation demand or number of future vehicles gave rise to severe traffic jam that was prevalent not only in large cities but in other regions as well beginning the 1990s. The rapid increase in export-import freight/cargo and traffic congestion in large cities expanded into a social and economic loss such as traffic jam expenses and logistics expenses beyond the problem of simple traffic jam. The SOC Investment Planning Commission made by presidential decree was set up in Chong Wa Dae (Blue House) considering the need to supply comprehensive and systematic TI; special accounts for transportation facilities were prepared for stable investment funding in 1994. Therefore, the history of investment in transportation facilities spans about 15 years only. Although Korea’s investment in TI leaves a lot to be desired compared with advanced countries’ long-time investment in TI, the country is encouraging investment in TI by the private sector considering its national financial operation wherein the capacity for infrastructure investment is insufficient due mainly to the expansion of the investment requirement in the social welfare sector such as education and health care. Meanwhile, except for Gyeongbu Expressway, the supply of TI for the past 60 years has not gone beyond the demand-responsive dimension, which is a bit frustrating. Considering the fact that TI supply has not only the fundamental function of passenger and freight/cargo handling but also the function of spurring regional development or symmetric development of national land, Korea has been somewhat careless in this regard.
3.2 Infrastructure development process in each transportation sector
For the past 60 years, the infrastructure establishment that has had the greatest impact on our transportation network construction today is the Gyeongbu Expressway. Completed in 1970, it was an innovative project during those days since the Korean government perceived that national highway expansion/pavement projects—which were sporadically implemented through overseas aids (loans from IBRD, ADB, etc.)— had limits in terms of systematic road network construction. The opening of the Gyeongbu Expressway along with the Gyeongin Expressway, which was completed in 1968, became a valuable opportunity to convert the railroad-centered transportation system gradually into a road-focused one. Despite strong objections at the time, the completion of the 428 km-long Gyeongbu Expressway by consolidating national
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capacity within two and a half years was not just aimed at coping with the “my own car age.” Another reason was that the innovative improvement of logistics flow following the construction of the arterial road connecting the industrial zones of the Busan/South Gyeongsang region including Ulsan, Pohang, and Metropolitan Seoul Area and infrastructure construction for Korea to grow as an export-oriented industrial country were necessary. The construction of many industrial complexes including the Gumi Industrial Complex along the Gyeongbu Expressway was carried out; thus, Gyeongbu Expressway played a pivotal role in developing the national economy. Moreover, the Gyeongbu Expressway became a valuable national experience that made Koreans realize that the supply of TI has not only smoothened the traffic passage function, but that it is also leading—and performing the function of—regional development. Since the construction of Gyeongbu Expressway and constant expansion of expressway network including Jungbu Expressway, West Coast Expressway, and Jungbu Inland Expressway, more than 3,000km of expressways have played the role and function of national principal transportation facilities. As a result of estimating1) the various project effects of expressway construction promoted by concentrating national capacity that influences the improvement of the national economy and quality of people’s lives, the direct effect of the entire expressway network built up to 2005 was estimated to have reached approximately 139 trillion won annually (about 17.2% of GDP). The effects of reducing the 9.05 million won in annual expenses per vehicle and realizing reductions of 420 liter of gasoline, 84 minutes of travel time per day, and 5.2 km of mileage per day were estimated. In particular, looking into the change in the average travel time from cities/countries nationwide to Seoul areas that had taken more than 300 minutes to reach showed sharp reduction in travel time after 1995. Areas covered by expressways recorded faster growth in terms of increase in the manufacturing industry’s added value, numbers of businesses, and employers than areas that were not covered by an expressway. The enhancement of accessibility between regions has contributed to transportation convenience and improvement in the quality of people’s lives. The growth speed in rural areas was faster than urban areas, implying that expressways have contributed to balanced regional development.
1) “New Frontier Policy of Expressway Construction Required,” by Ho-jung Kim and Sun-young Jung, 2007, Land Policy Brief,136, The Korea Research Institute for Human Settlements.
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The construction of the expressway network has an impact on the reduction of psychological distance as well.2) Such psychological distance reduction effect by road connection as recognized by citizens through the expressway construction was estimated to be about 16%. When comparing before and after the construction of main
Table 3.1. Expressway Construction Effects
Total Vehicle Mileage Category Direct Effect Total Travel Time Saved Saved Total effect of all 139.2641 21.41 million 80 million expressway in 2005 trillion won/year vehicles/day vehicles∙km/day Effect per vehicle 9.05 84 min/day 5.2km/day (note) million won/year
Note. Calculated the effects of all lines based on the no. of registered vehicles in 2005. From “New Frontier Policy of Expressway Con- struction Required,” by Ho-jung Kim and Sun-young Jung, 2007, Land Policy Brief, 136, The Korea Research Institute for Human Settle- ments.
Figure 3.1. Change in Average Travel Time to Seoul
<1995> <2000> <2005>
Less than 100min.~ 200min.~ 300min. 100 min. less than 200min. less than 300min. or more
Note. From “New Frontier Policy of Expressway Construction Required,” by Ho-jung Kim and Sun-young Jung, 2007, Land Policy Brief, 136, The Korea Research Institute for Human Settlements.
2) “Psychological Effects of Spatial Land Distance by Expressway Network Construction,” by Ho-jung Kim and Il-ho Jung, 2008, Land Policy Brief, 192, The Korea Research Institute for Human Settlements.
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expressways, direct connection by Figure 3.2. Perceived Distance Reduction From Expressway Network expressway was analyzed to wield about Construction 60% of psychological distance reduction effect. Looking into road projects implemented mainly along with expressway and national highway construction, road expansion/pavement projects were carried out in the 1970s and 1980s; Korea concentrated on the enhancement of national highway and provincial road pavement rates. The expansion/pavement projects for national roads and provincial roads were consistently implemented in the 1990s and deemed to contribute to the improvement of regional living environment. Due to the increase in the
number of private cars in large cities, Note. From “Psychological Effects of Spatial Distance by however, urban traffic conditions Expressway Network Construction,” by Ho-jung Kim and Sun- young Jung, 2008, Land Policy Brief, 192, The Korea Research deteriorated. Institute for Human Settlements. Korea needs to seek road policy transformation into a new road policy paradigm that can enhance environment- friendliness, stability, and investment efficiency along with the expansion of connection with the principal road network by large city region in the 2000s. Railroads had played a central role in land transportation for a while after liberation from the Japanese colonial rule, but they have not developed remarkably since then, compared to roads. With the railroad network centered on south-north, which was built by Imperial Japan to exploit the resources of Korea, the supply of underground resources such as coals—which became the base of industrial development—was cut off from North Korea after the Korean Peninsula was divided into South and North Korea. Therefore, east-west transverse railroad network construction including the Yeongam Line, Hambaek Line, and Mungyeong Line was implemented after the Korean War.
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Figure 3.3. Development Features of Roads by Periods
1960s 1970s 1980s 1990s 2000s
Completion Twofold Expansion Major road Full-fledged of national expansion of of principal pavement national highway expressways road and basic highway and and national network Road network road network pavement & major roads. and of the construction expressway provincial enhancement 21st century construction road of pavement environmental safety
User-centered Economic Relief transportation Balanced Residential system, growth and regional from environment traffic balanced infrastructure growth improvement construction bottleneck development of the national territory
Note. From Roads in Korea, by the Ministry of Land, Transportation and Maritime Affairs, 2008.
Note, however, that most railroad construction projects were simply making double tracks, building subways, and constructing a lead line into industrial complexes; construction of the new arterial railroad network was poor. The lack of investment in railroad was believed to be attributable to its lower competitiveness compared to that of roads. Railroads were not only disadvantageous in terms of door-to-door transportation compared to roads; the competitiveness of railroads could not be secured as well compared to roads in terms of just in time delivery and economic aspect, since large and long freight/cargo turned into small and light freight/cargo. In the spatial structure wherein the railroad’s operation length does not go beyond 500km, the division of the Korean Peninsula posed a structural limit in securing the competitiveness of railroads. If the distance of land had doubled with a united Korea instead of a divided South and North Korea, no policy similar to that for the past 60 years would exist in terms of investment in railroad. Full-fledged investment in railroad was made first for railroads within cities rather than railroads between regions. This was because traffic congestion in roads became a social issue in everyday life centered on large cities owing to rapid urbanization in the 1980s. Full-fledged city railroad projects have been continuously implemented since the partial opening of subway line No. 2 in 1980 following the construction of subway line No. 1 (Jongro Line) in 1974: today’s Metropolitan Seoul Area’s subway and electrified
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Table 3.2. Transportation Policy Changes by Period
Policy Change in Each Sector Period Policy Basis Railroad Marine Shipping Aviation Road /Subway /Port /Airport Rehabilitation ∙Restoration of ∙Rehabilitation ∙Rehabilitation and roads and ∙Establishment of 1950s reconstruction ∙Adoption of reconstruction 5-year port after the mechanization ∙Introduction of construction Korean War technology diesel train plan
∙Repair of road ∙Inauguration of facilities Railroad ∙Industrial port ∙Commencement Authority and construction and of expressway adoption of expansion construction sound operation ∙Construction of Infrastructure ∙Establishment of system ∙Launch of 1960s large harbor for construction basic road ∙Industrial railroad private airline the unloading of network construction & imported raw ∙Establishment of maintenance materials 10-year program ∙Facility for expressway modernization construction
∙Full-fledged national highway ∙Modernization of pavement industrial ∙Facility ∙Facility project railroads and Infrastructure expansion, expansion and ∙Expansion of construction of expansion to stevedoring modernization 1970s expressway subways boost the equipment ∙Improvement network ∙Introduction of economy modernization of private ∙Completion of subway in the airline national Metropolitan highway & Seoul area provincial road pavement ∙Runway and ∙Expansion of the ∙Wharf passenger ∙Investment in existing line construction, terminal roads to improve capacity new port expansion Infrastructure the national ∙Feasibility review development, ∙Improvement maintenance 1980s living of high-speed facility of local to improve the environment trains expansion airports and quality of life ∙Completion of ∙Review of ∙Enhancement of private airline the Jungbu subway coastal facilities Expressway introduction in transportation ∙Launch of Busan capacity second private airline
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Table 3.2. (Continued)
Policy Change in Each Sector Period Policy Basis Railroad Marine Shipping Aviation Road /Subway /Port /Airport
∙Expansion of ∙Commencement expressways & of Gyeongbu national Express Railroad ∙Commencement highways along construction of Incheon ∙Expansion of with the ∙Feasibility International Solving international national review of the Airport bottlenecks logistics 1990s principal road Honam Express construction owing to facilities in network Railroad ∙Expansion of high growth keeping with ∙Road ∙Spring subway airport globalization maintenance construction as facilities including uban mass nationwide bottleneck point transportation improvement facility
Establishment ∙1st stage of express ∙Construction of completion of arterial principal road Gyeongbu ∙Construction of ∙Construction transportation network system Express Railroad Busan New Port of Incheon 2000s network and thru expressway ∙Launch of and Gwangyang International improvement of and national Honam Express Port Airport inter-country highway Railroad transportation’s expansion construction competitiveness
train network was built. Meanwhile, the Gyeongbu Express Railroad, which was intended to solve the traffic jam in Gyeongbu Expressway, commenced construction in 1992; it was partially opened in 2004, implying that the railroad age between regions is in full scale. The deregulation of outbound travels in 1988 increased international passenger demand dramatically and made the government realize the capacity limit of Gimpo Airport; thus triggering the construction of the Incheon International Airport. Busan Port, which handled most freight/cargo nationwide in the export-centered national economy, suffered from extreme vessel and freight/cargo demurrage in the early 1980s. The container wharf with 7 berths in the Busan Port was lagging behind in the competition with the surrounding ports such as Hong Kong, Singapore, and Taiwan in terms of
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Table 3.3. Change in Major TI Indices (1957~2006)
Change ratio Category 1957 (A) 1981 (B) 2006 (C) B/A C/B C/A Increase in total road 27,169 50,336 12,061 1.85 2.03 3.76 length (km)
Increase in expressway - 1,245 31,023 - 2.49 - length (km)
Total road pavement 3.5 34.1 77.6 9.74 2.28 22.17 ratio (%) Road Annual no. of expressway - using vehicles - 5,196 1,600,004,640 - 31.68 - (10,000 vehicles)
No. of registered vehicles 2.8 57.1 1,589.5 20.34 27.83 565.95 (10,000 vehicles)
Increase in total service 2,938 3,121 3,392 1.06 1.09 1.15 length (km)
Increase in express - - 240.4 - - - railroad length (km) Railroad Double tracking 15.6% 22.9 40.6 1.47 1.77 2.60 ratio (%)
Increase in total - 13.7 482.1 - 35.19 - subway line length (km)
Loading and unloading 670 8742 600,009,213 13.05 7.92 103.30 capacity (10,000 tons) Sea Ship (10,000 G/T) 32.5 495.9 1025.0 15.26 2.06 31.54
Aircraft 24 199 326 8.29 1.64 13.58
(International) Air passenger 2.2 313.0 3,036.0 143.32 9.70 1,389.97 Air (10,000 people)
(International) Air freight 137.1 200,005,431 2,600,001,773 149.84 12.74 1,909.36 (10,000 tons)
Note. From data from Statistics Korea and the Ministry of Construction and Transportation, 2008.
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facilities. Thus, large foreign shipping companies avoided Busan Port. As a result, our export-import freight/cargo competitiveness dropped. In response to such, two-port system development (Busan and Gwangyang Container ports) was decided in 1991, with 7 berths and 16 berths operated in Busan New Port and Gwangyang Port, respectively, as of the end of 2007 following intensive investment.
4. Condition Change Outlook and Tasks for Korea’s TI Development
4.1 Outlook of future conditions change related to TI
4.1.1 Outlook of external conditions change
A single transportation market is forecast to emerge rapidly in light of integration of the world market. With the development of ICT (Information and Communication Technology) and spread of globalization awareness, the concept of economic borders is rendered meaningless, and the movement for integrating the world market is forecast to pick up speed. According to the trend of free trade breaking down tariff and non-tariff barriers, the expansion of the market integration effect is forecast to accelerate the formation of a single market. In particular, there is a need to cope with the expansion of a single transportation market in the transportation sector in keeping with the acceleration of the world market including the diffusion of the airline deregulation policy in the airline sector. The consolidation of cooperation systems among countries is expected considering the overheated competition to become the transportation and logistics hub in Northeast Asia. With the signing of the FTA between Korea and the US, the age of borderless, fierce competition has dawned, and demand for international freight/cargo transportation is forecast to increase further based on the increased interchanges between South and North in the world. Korea has laid down the foundation for becoming the hub with the opening of Incheon Airport and Busan New Port, but the competition with Shanghai Pudong Airport, Yangshan Port, and Shenzhen Port in China intensifies. In the meantime, Korea needs to make an effort to cope with the enforcement of the Kyoto Protocol and high oil price age. With the adoption of UNFCCC and 1997 Kyoto
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Protocol, an agreement to reduce CO2 emissions to a certain amount by 2021 was made. To establish an environment-friendly, energy-saving transportation system mode, Korea needs to strengthen national competitiveness with the adoption of the road feeder service (RFS) that transports freight/cargo at port/airport to an airport through trucks and subsequently ships the freight/cargo to the destination airport by air through transfer transportation, not to mention inter-modalism establishment. Lastly, Korea needs to prepare for the progress and expansion of interchanges between South and North Korea. Through the railroad function consolidation resulting from the progress of South and North interchange activation, Korea should make an effort to reinforce connection functions among transportation means to cope with the following: (1) role increase in railroad and coastal shipping as long-distance transportation means in case of train ferry and railroad network construction between South and North Korea and continent, and; (2) establishment of continent-linking railroad network including Trans Chinese Railway and Trans Siberian Railroad.
4.1.2 Outlook of internal conditions change
Because of the change in the spatial aspect of land, balanced land development policy implementation centered on the “5+2 mega-economic regions” is projected to necessitate the reorganization of the existing transportation system. On the symmetric land development dimension, the local economy can be activated through the decentralization of key functions including the relocation of public institutions to provincial areas; wide-area urbanization centered on large city regions can also trigger wide-area transportation demand. Consequently, one or two leading strategic industries in mega-economic regions should be fostered as representative industries for continuous growth and job creation to induce the activation of linkage and cooperation among regions beyond municipal and provincial boundaries and to pursue openness. For changes in the social and economic aspects, a demographic change can be seen. Korea’s total population is predicted to rise from 48,875,000 in 2010 to 49,326,000 in 2020 but go down to 48,635,000 and 42,343,000 in 2030 and 2050, respectively. Such decreasing trend in the population implies entry into aging society in full scale. With the rapid increase in the number of elderly people at 9.1% in 2005 and 14.3% in 2018, elderly people are estimated to account for 20.8% in 2026 to create a super aging society and over 38.2% by 2050. With such full-scale entry into aging society, the elderly and the weak in terms of transportation will increase along with the improvement in participation in society
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by the elderly in keeping with the changes in the social living and educational standards. The change in the transportation system aspect is predicted to be more remarkable. Social demand for securing investment efficiency increases, whereas duplicate, excessive, and diversified investments are minimized given the restrictions on funding for transportation investment. Accordingly, changes in competition/complementation relationships among transportation means such as fast train and aviation and development of digitalization and intelligent technologies should be considered along with the demand for a reduction in the excessive road use fee rate in the future. Specifically, high-quality investment in roads is expected to be requested. Therefore, the need for the consolidation of mass transportation investment for the provision of environment-friendly and efficient transportation services, transportation facility expansion, and enhancement of mobility for weak people is forecast to arise. Investment focused on efficiency is linked to consolidated investment in regions and large city regions characterized by heavy traffic jam. This is expected to induce a reduction in travel time and improve transportation service quality. Information technology (IT) development can be viewed as a revolution in information; the development into a new society with ubiquitous concept—wherein time and space barriers no longer exist after 2010—can be forecast. The development of IT and relevant services can have direct impacts on various sectors including transportation along with the utilization of IT. Thus, the development direction of roads can be projected. Consequently, the development of intelligent and digitalized technologies in roads is expected to be accelerated. More specifically, traffic volume can be dispersed through the expansion of the intelligent traffic system; cutting-edge traffic management system on high-speed national highways will likely be expanded and reinforced consistently to strengthen traffic information provision and guidance.
4.2 Main projects for TI
Korea has made an extensive investment in expanding and modernizing its transport infrastructure since the 1960s, aiming not only to ease traffic congestion, but also to enhance growth potential and improve quality of life. From 2005-09, despite relative increases in government expenditure on welfare and education, transport infrastructure investment has gained 7.8 percent on average, on a par with the 7.9 percent expansion of the overall national budget. Infrastructure investment accounted for 7.7-8.7 percent of total public expenditure during the same period, attesting
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its importance for national growth and advancement. In 2009, the government raised its spending on transport infrastructure to assist regional development by a whopping 26 percent, far higher than the average growth rate of 3 percent during 2004-08. With continued increases in infrastructure investment, the nation could expand its transportation stock, complete the frame of a nationwide transport network and sharply increase transport capacity for both passengers and freight. The stock of roads that connect key regional hubs has jumped 2.5-fold from 40,000 kilometers in 1970 to 104,000 kilometers in 2008. Roads currently account for 95 percent of passenger traffic and 96 percent of freight transport. Through the 1980s, it became evident that congestion problems could not be resolved simply by building more roads. The Korea Research Institute for Human Settlements thus came up with “The Master Plan to Establish Nationwide Arterial Road Networks” in 1992. The plan detailed measures for building a systemic arterial road network that could disperse traffic flow by means of a stratified road structure, and contribute to more balanced regional development as well. Though revised to reflect changes afterward, the latest version still retains the underlying philosophy and Figure 4.1. Plan for the Formation of a National contents of the 1992 master plan. Arterial Transportation Network by 2019 The current plan envisions the establishment by 2020 of a “7 by 9” nationwide arterial road network, consisting of seven north-south and nine east-west corridors. Once completed, main roads in the network will be reachable from anywhere of the nation within 30 minutes. Of its total length of 6,527 kilometers, 55 percent, or 3,447 kilometers of those highways have already been completed while another 1,570 kilometers of sections are
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Figure 4.2. Concept Diagram of Smart Highway
Source: Korea Expressway Corporation
in construction or design stages. Only 23 percent, or 1,500 kilometers of the envisioned network remain to be started. In the meantime, the government is pushing for a national research and development project for a “smart highway,” seeking to combine Korea’s accumulated know-how in road construction and management and its advanced information technology. It aims to chart new business opportunities by crafting future-oriented, high value-added road technologies and entering overseas markets for high-function roads. The project envisions an IT-powered intelligent road system, which will enable interactive communications of traffic information anywhere, anytime. The system is expected to help cut the nation’s road accident rates by 60 percent to reach the G7 average and improve the road mobility by 30 percent through a speedier road construction. The R&D program began in 2008 for completion by 2017. Diverse trial services will be conducted on a 58.1-kilometer section of highway that links Seoul to the
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new Sejong city, which is now under construction. Sluggish for decades, investment in railways has also gained a new vigor. The opening of the first phase of the Gyeongbu (Seoul-Busan) High-Speed Railway has greatly contributed to putting much of the nation within half a day’s travel as well as helping to balance the national transport system, which had relied heavily on automobiles. The Korea Train Express (KTX) has the design speed of 330 km/h and a maximum service speed of 300 km/h. Once the remaining 167.2-kilometer Daegu-Busan section of the Gyeongbu line and the 230.3-kilometer Osong-Mokpo section of the Honam line are completed—planned for 2010 and 2015, respectively—the KTX will connect more of the nation, helping solidify national competitiveness and social cohesion. The nation also plans to develop high-speed electric tilting trains and next-generation light trains based on new materials for operation in areas where KTX cannot run. As for air transportation, Incheon International Airport serves as the nation’s hub for external connection. To accommodate a ever-growing flight demand, the airport is set to expand its passenger and cargo terminals and concourse in steps. The scope and timing of a third phase of expansion will depend on future travel demand. Seaports are another pillar of transportation in Korea. With the completion of Busan New Port and the expansion of Gwangyang Port, the nation achieved its long- anticipated “Two-Port System,” adding momentum for the nation’s ambition to become a Northeast Asian logistics hub. In addition, with the aim of increasing the annual cargo handling capacity at seaports from the current 423 million tons to 1.01 billion tons by 2019, the government plans to put port bases in operation in each of six mega-economic regions, including the greater Seoul zone, develop more logistics complexes in port hinterlands, and build Saemangeum New Port as part of the development plan for the Saemangeum area of reclaimed land. The master plan also looks to construct a nationwide logistics network by expanding and refurbishing large-scale inland freight docks in five regional economic zones. The government will consider constructing two or three more such facilities depending on future demand.
4.3 Vision and objectives of transport infrastructure policies
In transport infrastructure policies, the nation set its sights on the enhancement of national competitiveness by lowering logistics costs. It also aims to improve quality of
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life through higher mobility, better accessibility and greener transportation. In addition to measures to address the above problems, the transportation authorities have established a set of policy objectives to proactively deal with expected changes in domestic and international transport conditions. The first objective is to establish more capable transport infrastructure facilities. As information and communications technologies advance, transport methods and networks evolve and the awareness of a global community spreads, the concept of an economic border is becoming increasingly obsolete. Especially in Northeast Asia, where the momentum for free trade is building quickly, the movement toward the consolidation of transport markets and ultimately toward a single regional market in the sector is expected on a fast track. The second objective is to achieve an efficient, sustainable integrated transport system that will better conform to a new socio-economic environment. Drastic spatial changes are expected to take place in the near future as new territorial development projects based on mega-economic regions will unfold and key national functions will likely be dispersed geographically with the planned relocations of government facilities. Transportation policies should proactively prepare for and assist such changes. Moreover, given that the fiscal operation plans of late indicated a gradual decrease in resources for transport infrastructure investment, the nation needs to further sharpen investment efficiency by minimizing overlapping, excessive and dispersed infrastructure outlays. In the other hand, it is crucial to ensure seniors’ and vulnerable people’s access to transport services and develop more environmentally-friendly and energy-saving transportation. The third objective is to develop technologies to upgrade the nation’s transport and logistics systems. One priority task in this aspect is to improve efficiency, mobility and accessibility of existing systems using cutting-edge technology. The industry must enable road informatization and the intelligent road system, and must strategically respond to changes in relations between different transport means such as high-speed rail and airplanes. Informatization and the intelligent road system are key to the competitiveness of the transport and logistics industries at a time when the society is moving toward a ubiquitous communications environment free from restriction by time and space.
4.4 Strategies for transport infrastructure policies
Establish an integrated national transport system: The plan calls for a systemic dispersion of traffic taking into account different characteristics transport modes. Long-
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distance passenger traffic can be transferred to high-speed trains while short- and mid- distance travelers can be encouraged to use expressways and low-capacity national roads. Long-haul freight movements can be dealt with by rail and costal shipping. Though an appropriate level of infrastructure investment should be maintained, efforts should be doubled to improve efficiency by avoiding overlapping and excessive investment and properly allocating funds to different transport modes. The master plan seeks to increase the transport adequacy ratio to the gross domestic product from 34.1 percent in 2003 to 45.5 percent by 2019, considering factors like transport facility stock, private capital stock, the output elasticity of transport facility capital, expected future economic growth rates and depreciation costs. To establish effective links between different means of transport, the government plans to build multi-function transit centers at major transport nodes. The plan also seeks to ensure that the national arterial road network of expressways is accessible from anywhere within 30 minutes. Integrated shipping systems should be installed at major logistics bases like seaports and industrial complexes to better meet the changing demand and make the industry more competitive.
Improve mobility and accessibility of the arterial land transport network: To promote balanced regional development and meet growing transport needs, the government seeks to finalize the lattice patterned arterial road network to bring the entire territory within half a day’s travel. Railways will be extended in stages from the current 3,300 kilometers to 4,800 kilometers. The plan also calls for the improvement of wide-area transport systems in metropolises to help strengthen competitiveness of cities. Above all, mass transit networks will be expanded at metropolitan areas including the greater Seoul zone. Wide-area transport coordination bodies will be formed to address various urban traffic problems while measures to manage transport demands will be taken more actively to ease congestion.
Realize a sustainable transport system: In preparation for a new climate change pact, the nation needs to build an environmentally-friendly transportation system by prompting a switch to an environmentally-friendly one. Investment should be aimed at encouraging wider use of public transport and building safer, more convenient pedestrian-only roads and bicycle paths.
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Korea aims to improve transport safety level to rank 15th in the Organization of Economic Cooperation and Development by 2019. The government will try to improve the road safety rate and increase transport safety measures, aiming to reduce the nation’s death toll from car accidents to half the number of 2005 by 2019. Greater transport access will be provided to the economically and socially disadvantaged and a user-oriented transportation system will be introduced. The government will prioritize the values of sustainability, increasing investment in transport services for seniors and the disabled, and reducing unnecessary social costs through user- charge policies like congestion road pricing and parking pricing, both of which would discourage personal vehicle use.
Establish an international transport system to cope with changing external conditions: As globalization builds, the plan seeks to create a single transport market in Northeast Asia. Such a market would bring mutual benefits to countries in the region, the last remaining part of the world devoid of an economic community. As a short-term preparation, the government will strive to globalize domestic logistics firms that have grown accustomed to protectionist transport policies. In the long term, Korea will phase out physical and institutional barriers to the operation of international logistics networks, for example through connecting domestic networks to the Trans- Chinese Railway and the Trans-Siberian Railway and liberalizing its airline market. The nation will establish an air transport system of G7-level quality, hub ports and global maritime networks. A third phase of expansion is expected to equip Incheon International Airport with facilities and systems necessary for it to serve as a regional hub. The government will push for an open-sky policy to cope with the ever-expanding market in and outside the region. Logistics infrastructure at Busan Port and Gwangyang Port will be developed to allow them to increase their significance as freight hubs and become key maritime bases in Northeast Asia. The plan also demands the preparation for inter-Korean transport links in line with improvement in ties across the border, and continental connections through the Asian Highway and the Trans Asian Railway. The government will consider establishing a comprehensive plan for transport networks covering the entire Korean Peninsula in preparation for the South-North integration.
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Build an intelligent transport system and develop related technologies: Korea is looking to apply IT solutions to informationize transport and create an intelligent road system. These will boost operational efficiency through real-time transport management, improve safety through a tighter control of dangerous factors that cause accidents, and make roads more convenient by providing real-time transportation information. The nation needs to expedite the development and commercialization of cutting- edge transport technologies by encouraging both public and private sectors to engage more in research and development of core technologies. The government is striving to speed up penetration into ITS and other next-generation transport management system markets with its mid- and long-term R&D, strategy choices and investment in the development of ubiquitous network-based transport systems.
Enhance competitiveness of the transport and logistics industries: The government seeks to enhance transport competitiveness by restructuring vulnerable businesses and encouraging private sector participation in transport facility management. It plans to restructure the industry by encouraging private sector competition, to boost investment in transport facilities by easing regulations. It will consider ending the current monopoly in facility maintenance and management. The government seeks to strengthen the competitiveness of the logistics industry through higher value-added logistics systems, informationization and standardization, and integrating its logistics policies. To this end, the government plans to nurture logistics companies by expanding local complexes of airports and seaports. The government will also operate an integrated national logistics information center to support corporate logistics activities with one-stop information services.
4.5 Scale and effects of transport infrastructure investment
The implementation of the above-mentioned transport infrastructure strategies is estimated to cost about 291 trillion won (based on 2005 prices) between 2007 and 2019. Of the total, the government is required to pour in an estimated 193 trillion won. The sum translates into an average annual spend of 14.8 trillion won, not far different from the current government budget set aside for transport infrastructure (amounting to 14.2 trillion won as of 2004). The remaining 98 trillion won, or an annual average of 7.5 trillion won, is not impossible to raise, given that the government has attracted
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about 8 trillion won per year from public firms such as Korea Express Corporation and Korea Rail Network Authority and private companies. But detailed investment, timing and resources will be reviewed along with the overall budget operation planning when the government sets up a new five-year mid-term plan for transport infrastructure investment. Meanwhile, the huge investment should have significant social effects. The expansion of expressways and railways alone is expected to cut transit time, vehicle operation costs, car accidents and environmental costs, together equivalent to an estimated 132 trillion won. The investment is also expected to generate 819 trillion won in output and added value and create 4.17 million new jobs.
5. Conclusion
Korea’s transportation infrastructure (TI) has continuously developed for the past 50 years and has secured a considerably high level of accessibility and mobility. This is the result of great efforts of the Korean government and citizens that have concentrated their capacity on the development of TI. Nonetheless, Korea should not be contented with its achievements so far. Internal and external conditions related to TI—which we will face in the future—are predicted to vary. Due to the acceleration of a single market formation movement derived from the integration of the world market, competitiveness enhancement in the aviation and port sectors is a matter of urgency. With the Kyoto Protocol taking effect and dawning of the high oil price age, more effort to establish an environment-friendlier, energy-saving type of transportation system is required. Internally, Korea needs to respond to efficient investment demand arising from the reduction of investment in the transportation sector. The country should also prepare for social demand for various transportation services provision in response to aging and income increase. Specifically, thorough preparation is required to cope with the unification of the two Koreas. Korea has wisely coped with situation changes for the past 50 years. The development of a nation is in line with securing safe, convenient, and efficient transportation infrastructure. Thus, policymakers and people engaged in the transportation industry as well as transportation experts need to cope actively with future changes as well.
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Bibliography
Chung, Il-ho (2003, September). Proceedings of the seminar for exploring SOC and land policy directions toward the age of US$20,000 per capita income. The Korea Research Institute for Human Settlements. Chung, Il-ho (2008, December). Proceedings of the Creative Land Development Strategy Symposium. The Korea Research Institute for Human Settlements. Chung, Il-ho (2009, August). Proceedings of the Policy Forum on the Road Investment Direction for Green Growth. The Korea Research Institute for Human Settlements. Ministry of Construction and Transportation. (2007, November). National Principal Transportation Network Plan (2000~2019, first revision).
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Climate Change and Sustainable Land 02 Management Strategies in Korea - Focusing on Greenhouse Gas Inventories by Region
KRIHS SPECIAL REPORT 2010
Yeong-kook Choi Moon-woun Lee Jin-kyu Chung Kwang-ik Wang Eun-sun Im Yeon-mi Seo Ou-bae Sim Jung-eun Park Myung-soo Kim 0709-SpecialReport vol 16 2010.7.20 9:46 AM 페이지38 열림4 HP-LaserJet-A3
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Climate Change and Sustainable Land Management Strategies in Korea - Focusing on Greenhouse Gas Inventories by Region
Yeong-kook Choi et al.
1. Introduction
1.1 Background and purpose
Unusual weather conditions such as floods, droughts, and tsunami are frequently occurring around the world and the size of the damage caused is almost unprecedented. Many scientists are pointing their fingers at climate change as the main cause of these unusual weather conditions. Climate change is threatening the necessities of life, such as water, food, health, land, and the environment. The national territory causes global warming through various human activities, e.g., manufacturing. Meanwhile, it is also influenced directly by the climate change. Although there is a significant relationship between climate change and national territory, not enough studies have been conducted on territorial management to cope with climate change. This is because climate change has been approached by sector, i.e., energy, environment, industry, etc. There have been recent efforts to suggest various policies for climate change in terms of the national territory. However, it is not easy to suggest viable policies because the range of influence of climate change on the national territory is very wide and many areas, such as territorial environment, territorial spatial structure, use of energy and resources, traffic systems, economics and industry, and living culture, affect one another. In addition, most of the policies prepared by each area and ministry for a reduction of greenhouse gases and adjustment of climate change remain at the theoretical level. The fundamental reason for the lack of viable policies is thought to be the lack of
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Figure 1.1. The Structure of the 1st Year Study
specific data for the identification of greenhouse gas emissions and the vulnerability of each region against climate change. Currently, the greenhouse gas inventory is established at the national level, but with the national level greenhouse gas inventory, it is impossible to suggest policies customized for each region and their practicability is also low. Therefore, it is most urgent to identify greenhouse gas emissions by region and regional conditions vulnerable to climate change to establish more practical policies and countermeasures. Against this backdrop, the study was suggested as part of a three-year study (2008- 2010) to establish sustainable territorial management strategies based on the analysis and evaluation of regional features and greenhouse gas emissions, and characteristics of regions vulnerable to unusual weather conditions. This study, the first of the three-year study, focuses on establishing a nation-wide greenhouse gas inventory by region, as yet not attempted, as the first step to presenting some solutions.
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1.2 Scope and methods of the study The estimation of greenhouse gas emissions by region was conducted over 232 areas across the nation, using various research methods such as: an understanding of climate change phenomena and trends of countermeasures, through literature and statistical research; reviews of climate change policy trends by country and methods to establish inventories, by consulting external experts; the establishment of basic data on energy consumption with the help of related institutes; commissioning of articles on overseas cases to experts; estimation of greenhouse gas emissions by region and emission source by applying the IPCC (Intergovernmental Panel on Climate Change) method; and suggestion of methods to utilize greenhouse gas inventories through empirical analysis.
Figure 1.2. Research Methods Used in This Study
1.3 Necessity of establishing greenhouse gas inventories by region
For territorial policies to generate a change of human activities, it is important to identify the relationship between the amount of greenhouse gas emissions and the conditions of regions. An analysis of the characteristics of emissions by sector and region (city and county) is required to understand the impact of climate change and establish countermeasures. This is because countermeasures should be executed at the individual or regional level, even if the climate change occurs globally. Therefore, countermeasures should be presented based on an analysis of the characteristics of emissions and vulnerability of each region, which are viable measures.
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In addition, to closely examine the characteristics of emissions, it is necessary to establish basic data for an analysis of emission reduction effects after executing policies. Establishing greenhouse gas inventories is essential for monitoring the execution of policies related to, for example, the introduction of green transport, “Compact City, Smart Growth,” and eco-friendly buildings and the formation of resource saving and resource recycling territorial spatial structures. In particular, estimating greenhouse gas emissions resulting from land use can provide essential grounds for the establishment of sustainable land use systems.
2. Review of Previous Studies
2.1 Review of previous studies
Previous studies include the study of “Analysis of spatial and temporal characteristics of urban energy consumption” by Lee, Gang-guk and Hong, Won-hwa (2006); “A study on the effects of urban form and the commuting and socio-demographic patterns
on road transport-derived CO2 emission” by Wang, Gwang-ik (2005) ; and “A basic plan for natural environment preservation” by the Ministry of the Environment (2006). The study of Lee, Gang-guk and Hong, Won-hwa (2006) examined the spatial and temporal characteristics of energy consumption of regional units smaller than administrative districts. In particular, the method used to analyze the patterns of energy demand and consumption by cell unit of 500m resolutions could be applied in this study for planning urban spatial structures. The study of Wang, Gwang-ik (2005) provides data for establishing greenhouse gas reduction policies suitable for each region by analyzing the correlation between
various urban structures and socio-economic variables and CO2 emissions. However, it has limitations in interpreting any relationship with emissions from other sectors, such as public welfare and industry, as it limits the sector to road traffic. The study of the Policy Research Institute for Land, Infrastructure, Transport, and Tourism (2002, Japan) has set policy directions by performing quantitative analysis by
region for CO2 reduction and predicted the results of executing policies by establishing models and applying policy scenarios which might reduce emissions.
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2.2 Novelty of this study
This study focused on estimating greenhouse gas emissions by region and analyzing regional characteristics. Although this study was conducted based on the methods used in previous studies, such as the methods used to collect data on energy consumption and the methods used to estimate greenhouse gas emissions, the methodology was complemented and then applied to establish greenhouse gas inventories by region (administrative districts). No previous studies have ever attempted to establish a greenhouse gas inventory for the entire nation. This study is also differentiated from other studies in that it analyzed the correlations between greenhouse gas emission characteristics and regional conditions, by using sustainable territorial management indicators that reflect regional characteristics. Moreover, this study is differentiated from previous studies in that it established methodologies to establish various basic data to deal with climate change,
such as estimations of the CO2 emission intensity for each land use type by using energy consumption rate of land parcel or building, and established inventories by using factual data.
3. Methods to Estimate Greenhouse Gas Emissions by Region
3.1 The subjects of greenhouse gas inventories by region
Among the sectors suggested in the IPCC Guidelines, the scope of greenhouse gas emission sources and sinks of this study was limited to the four sectors of energy, agriculture, waste, and change of land use and forests, excluding some sectors such as industrial processes for which it is difficult to establish basic data by area units such as cities, countries, and districts, and consumptions of other products including solvents, whose actual emissions are difficult to measure. The greenhouse gases covered in this
study are three types of gases: carbon dioxide (CO2), methane (CH4), and nitrogen
dioxide (N2O). The years for estimation of greenhouse gas emissions by region were selected as the years 2000, 2003, and 2005, considering the availability of the basic data. The areas selected for the estimation of emissions were 232 local municipalities.
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This study reviewed the IPCC Guidelines, which is the foundation of other guidelines, for the estimation of greenhouse gas emissions. In particular, this review focused on the contents to help develop an understanding of the IPCC greenhouse gas estimation
method for CO2, CH4, and N2O of the energy sector, which assumes a large portion of greenhouse gas emissions. Through the review of the IPCC Guidelines, this study explained the basic direction for estimating greenhouse gas emissions by region and the differences from establishing national level green house gas emission statistics. The purpose is to ease difficulty in obtaining local municipality level basic data for managing end-user demands. After that, it describes in details the method used to estimate greenhouse gas emissions by sector and region, such as energy, agriculture, waste, and use of land and forests, and the method of obtaining and utilizing the basic data. This study also described the limits and problems in the research process, starting from establishment of the basic data to estimation of greenhouse gas emissions by region, by comparing it with the methods used to estimate greenhouse gas emissions at the national level. In the energy sector, the biggest limitation in estimating greenhouse gas emissions by region was the central government-driven, supply plan-based energy management approach. There would be some difficulties in analyzing potential reductions through any execution of policies of local municipalities by sector for the reduction of greenhouse gas emissions by region because energy providers have different standards of classification of sectors, such as industry, commerce, business, the public, and homes. The lack of basic data possessed by local municipalities was one of the largest problems in estimating greenhouse gas emissions by region. It was also found that developing Korea’s own discharge coefficient is one of the most urgent tasks to accomplish. Lastly, to cope with climate change, the most urgent matter at hand is to continue to build greenhouse gas inventories by region, which can be used by local municipalities according to regional conditions.
3.2 Scope of greenhouse gas emissions by region
For estimating greenhouse gas emissions, the IPCC recommends the use of “Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories”1) (hereinafter referred to as the “1996 IPCC Guidelines”). The 1996 IPCC Guidelines divide the list of greenhouse gas emissions, including both sources and sinks, into the six categories of
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energy, industrial process, consumption of solvents and other products, agriculture, change of land use and forests, waste and others. As seen in Table 3.1, there is a difference in the list for the national and the list for the regional level greenhouse gas emissions. As the actual greenhouse gas emissions from the “consumption of solvent and other products” sector is not measurable, it is excluded from the list of greenhouse gas emissions by region, and the “fugitive emissions of the energy sector” and the “industrial process sector” were also excluded, as it is impossible to obtain those data at the level of cities, counties, or districts. Accordingly, this study limited the list of greenhouse gas emissions by region to the four categories of energy, agriculture, change of land use and forests, and waste. The “fuel combustion of the energy sector” in the list of greenhouse gas emissions by region was also established based on the classification of the list of national greenhouse gas emissions. However, the energy industry of the energy sector was excluded from the study because it is a key national industry, wherein the reduction of greenhouse gas emissions cannot be attained through local-level policies. In addition, since the classification of the fuel combustion in the energy sector by fuel and usage varied greatly depending on the energy provider (Korea Electric Power Corporation, Korea National Oil Corporation, gas companies, etc.), it was impossible to generate a common list as the one used for the national level. As a result, as shown in Table 3.2, regional greenhouse gas emissions of the fuel combustion in the energy sector were estimated based on the total emissions and emissions by fuel type and usage. Basically, the aim was to procure eight years’ data from 2000 to 2007. However, in the course of data collection, it was found that not every year’s data is available for each sector, including oil, electricity, gas, agriculture, and waste. For this reason, the years 2000, 2003, 2005, and 2006 where most data could be obtained were selected for the estimation of greenhouse gas emissions by region. The year of data in which the emissions of the whole area were estimated is 2005. In order to establish greenhouse gas inventories by region, over 232 areas2) (7 special/metropolitan cities, 74 counties and districts, 158 cities, counties, and districts) were assessed based on the year 2005.
1) For detailed information, please visit the official website: http://www.ipcc-nggip.iges.or.jp/
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Table 3.1. Comparison Between the Inventory List of the National Level and Regional Level Greenhouse Gas Emissions
The list of national greenhouse gas emissions The list of greenhouse gas emissions (source/sink) by region (source/sink) Energy industry Oil Manufacturing and Electricity construction Transportation Gas Fuel Fuel Energy combustion Mining, agriculture and Energy Combustion fishing, home and Thermal energy commerce, public and others Others Coal Fugitive emissions Excluded Industrial process Mineral industry, chemical industry, etc. Excluded Consumption of solvents and other Excluded products Enteric fermentation Enteric fermentation Excretion decomposition Excretion decomposition Agriculture Agriculture Rice field farming Rice field farming Agricultural soil Agricultural soil Change in the amount of biomass stored Forest tree absorption in forests and other wooden areas Lumbering Change of Change of land use Change of use of forests and grasslands Change of use of forests land use and forests Idle cultivating land and forests Excluded Mineral soil Discharge and absorption of CO2 by soil Use of lime Burial of solid waste Burial of solid waste Waste incineration Waste incineration Waste Waste Domestic sewage treatment Excluded Industrial wastewater treatment
2) Before 2006, the estimation was made for 234 local municipalities.
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3.3 Application of the 1996 IPCC guidelines
In this study, greenhouse gas emission by region was estimated by utilizing current official statistics and regional basic data, based on the 1996 IPCC Guidelines. For the discharge coefficient, the Manual of the Energy Calorie Conversion in the website3) of the Korea Energy Management Corporation (KEMCO) was used as a reference. As for the coefficient regarding the sources and sinks without a nationally unique discharge coefficient, the one provided in the 1996 IPCC Guidelines was used. For the method for the estimation of sources and sinks by sector, reports of domestic research institutes4) were used as references. As the 1996 IPCC Guidelines recommended composing a list of national greenhouse gas emissions, there are limitations in using them to calculate greenhouse gas emissions by region. Firstly, as Korea’s statistics on energy consumption are provider- focused, Korea’s classification system is different from that of the IPCC5). Secondly, in selecting a coefficient to apply the IPCC Guidelines, the classification system (classification of oil and areas of use by fuel type) of the coefficient provided in Korea was different from that of the IPCC6). Thirdly, for the sectors of “industrial process” and “fugitive emission,” it was possible to estimate emissions at the national level, but
Table 3.2. Classification of Fuel Consumption by Type and Usage
Fuel Oil Electricity Gas Thermal Energy Coal
Private house & Private house Private house Private house Private house & commerce Service industry Commerce Commerce commerce Public Public Public Public Public∙Others Usage Transport - Transport - - Farming & Fisheries Industry Mining Industry Industry Industry Manufacturing
3) http://co2.kemco.or.kr/directory/toe.asp 4) Data provided from various institutes. Energy Sector—Korea Energy Economics Institute, Gyeonggi Research Institute, Seoul Development Institute; Agriculture Sector—National Academy of Agricultural Science; Stock Raising Sector—National Institute of Animal Science; Land Use and Forests Sector—Korea Forest Research Institute; Waste Sector—Ministry of Environment
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impossible to estimate emissions by region due to the lack of basic data at urban, county, and district level. When there were problems in applying 1996 IPCC guidelines verbatim because of lack of obtainable basic data for regions and the issues with greenhouse gas coefficients, the methods suggested in previous researches were utilized and professional advices sought. In particular, greenhouse gases produced from fuel combustion in the energy sector, which constitute a large portion of regional greenhouse gas emissions, were calculated using the following methods.
3.3.1 Estimation of CO2 from fuel combustion in the energy sector
The emissions of CO2 from fuel combustion were estimated through six stages: ① estimation of the amount of fuel combustion by fuel product ② conversion of the unique unit of fuel consumption to a common unit ③ selection of carbon emission coefficients by fuel product ④ estimation of the amount of carbon stored in products ⑤ consideration of carbon not oxidized in the course of combustion, and ⑥ conversion of
carbon emissions into CO2.
3.3.2 Estimation of CH4 and N2O from fuel combustion in the energy sector
The 1996 IPCC Guidelines suggest the three methodologies of『 Tier 1』,『 Tier 2』, and 『Tier 3』, and among these,『 Tier 1』is the easiest method to apply7), to estimate emissions from fuel consumption without any regard for combustion technologies. The IPCC recommends using『 Tier 1』when the exact discharge coefficient of the country is not known due to a lack of data on fuel type, technology, and operation conditions. This『 Tier 1』method estimates emissions by considering the discharge coefficient of
5) As providers, such as the Korea National Oil Corporation, the Korea Electric Power Corporation, and gas companies, apply different systems for classifying energy usages, it is difficult to apply a single discharge coefficient. 6) The IPCC provides only data commonly used across the world, such as carbon emission coefficients and carbon storage. As for the caloric value by energy source, as countries use different coefficients due to different thermal efficiency levels, a domestic caloric value coefficient should be used. 7) It is difficult to classify『 Tier 2』and『 Tier 3』accurately, but the classification depends on the accuracy and concreteness of the estimation process.『 Tier 2』classifies fuel consumption based on the knowledge and samples of homogeneous technologies to allow for the application of representative coefficients. On the contrary,『 Tier 3』estimates greenhouse gas emissions by using the emission coefficient estimated based on
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the greenhouse gases as well as the type of the fuel by sector. To estimate non-CO2
greenhouse gases (CH4 and N2O), the formula in Table 3.3 was applied.
Table 3.3. The Formula for Estimating Non-CO2 Greenhouse Gases (CH4, N2O) (1996 IPCC Guidelines)
Emission ＝Σ(EFab×ACTIVITYab) EF ＝ Emission Coefficient (kg/TJ), ACTIVITY ＝ Input Energy (TJ) a ＝ Fuel Type, b ＝ Activity by Sector
3.4 The method of estimating greenhouse gas emissions by region
3.4.1 Guideline for estimating greenhouse gas emissions by region
Greenhouse gas emissions by region were estimated using a bottom-up approach based on the regional data. This study attempted to illustrate the regional greenhouse gas emissions status at the urban, country, and district level, for the first time in Korea, by reviewing the 1996 IPCC Guidelines and previous studies, and soliciting advice of professionals8). In addition, the regional greenhouse gas emissions status was established based on the amount used by final consumers. However, it was not easy to identify end-users of mobile sources, such as oil consumed for transportation in the energy sector. To assess accurate amount of greenhouse gas emissions released from transportations, a nation-wide study on the actual transport volume by household, such as household travel surveys, should be conducted. For this reason, it was inevitable to calculate the emissions from transportation using statistics from sellers. The sources of data obtained for the estimation of greenhouse gas emissions by region are stated in
such data as the results of energy activities (e.g, mileage or ton-km in transportation), and the fuel mixture ratio, rather than based on fuel consumption. Hereinafter, the greenhouse gas sources are divided into the two sources of the fixed combustion source and the mobile combustion source. 8) In particular, central government-driven national energy scheme was applied in the energy sector with the focus on supply planning. However, the entities that actually carry out the plans, such as local municipalities, companies, and civilians, should become the principal axes of the energy sector for the reduction of greenhouse gases in the future.
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Table 3.4. Data Sources for Estimation of Regional Greenhouse Gas Emissions by Sector
Category Data Sources Remarks Oil Korean National Oil Corporation Petronet No data for Electricity Korea Electric Power Corporation Petronet year 2000 Fuel Gas Internal data of 33 gas providers Energy combustion Thermal energy 『Annual report of Regional Energy Statistics』 Data at city and Coal 『Annual report of Regional Energy Statistics』 province level Fugitive emissions Excluded Industrial process Excluded Consumption of solvents and other products Excluded Entric fermentation Excretion decomposition Annual reports from cities, counties, and Agriculture districts (statistics by species, area of Rice field farming farming, and amount of fertilizers used) Agricultural soil 『Statistical Annual report of Forestry』 Forest tree absorption (accumulated forest trees) 『Statistical Annual report of Forestry』 Lumbering (lumber production) Change of use of forests Internal data of Forest Services Idle cultivating land Excluded Land use Ministry of Land, Transport and Maritime and Affairs (land area) Mineral soil forests Ministry of Food, Agriculture, Forestry, and Fisheries (area of fields) Korea Fertilizer Industry Association (statistics on the use of lime) Use of lime National Agricultural Cooperative Federation (statistics on the provision of lime fertilizers)
Burial Ministry of Environment (status of the generation and treatment of Incineration waste across the nation) Waste Domestic sewage Excluded Treatment of industrial Excluded wastewater
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Table 3.4. This study is the first of a three-year study. In the second and third year studies, regional conditions will be reviewed in relation to the climate change. The regional inventories obtained from the first year study will be used as basic data for deriving regionalized mitigation and adjustment policy measures against the climate change. Therefore, providing an official statistics on regional greenhouse gases is not the purpose of this study. The Korean government is seeking to produce statistics on regional greenhouse gas emissions in the future, and this study aims to provide guidelines by suggesting problems and limitations of the existing domestic framework data in calculating regional greenhouse gas emissions. The statistics on regional greenhouse gas emissions obtained from this study can also be useful in estimating regional greenhouse gas emissions according to regional emissions scenarios, as well as in developing regional policies for managing greenhouse gases and in establishing nationwide greenhouse gas mitigation plans.
3.4.2 Methods and processes for estimating greenhouse gas emissions by region
■ Energy sector To avoid overlaps in estimating greenhouse gas emissions in the energy sector, some areas of use were excluded from the estimation. The oil used for energy industry was excluded from the estimation because oil is regarded as having been purchased for the production of electricity and thermal energy. Also, the thermal energy sent back and re- purchased by the Korea Electric Power Corporation was deemed to have been used by end-users and therefore, was excluded from the greenhouse gas emissions generated by thermal energy consumption. Figure 3.1 shows the areas excluded from the estimation to avoid overlaps. The greenhouse gas emissions of the oil, gas, and coal sectors were estimated largely by using the five stages described in Figure 3.2. While estimating emissions, it was found that regional greenhouse gas emissions from oil, electricity, thermal energy, gas, and coal cannot be estimated by areas of use (industry, home, commerce, etc.) because of their inconsistent classification.
① Oil To establish the greenhouse gas inventory for oil, the 2000 to 2007 oil sales figure of the
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Figure 3.1. Energy Sources Used for Building Greenhouse Gas Inventories by Region
Korea National Oil Corporation’s Petronet system classified by energy source and sector were used. Data provided by the company were rearranged using the following two steps. Firstly, the sectors were rearranged. The company divided the sectors that use oil into the medium categories of industry, energy industry, transportation, home and commerce, public, and others.『 Tier 1』method in the 1966 IPCC guidelines was applied to calculate the regional greenhouse gas emissions from oil. Energy industries include smaller categories such as other types of energies, generation, oil refining, and gas
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Figure 3.2. The Process of Estimating Regional Greenhouse Gas Emission in the Oil, Gas, and Coal Sectors
manufacturing industries, according to the classification by the Korea National Oil Corporation. However, as it is impossible to obtain energy sales figures of the smaller categories and as energy industry data is likely to overlap with data on sales of thermal energy and gas, all data in the energy industry sector were excluded from the estimation. As for transportation, the smaller categories classified by the Korea National Oil Corporation include 14 kinds of service areas, coming largely under the areas of railway,
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Figure 3.3. Composition of Greenhouse Gas Emissions in the Oil Sector
road, shipping, and air services. However, emissions from the marine transportation by foreign companies, marine transportation operated overseas by domestic companies, air transportation by foreign companies, and air transportation operated overseas by domestic companies, among the 14 types of businesses, were not included in the domestic emissions data as they are considered as using oil overseas, even though they purchase it in Korea. In other words, data was compiled by region and by energy source for 10 sectors out of the 14 transportation sectors, excluding the above mentioned four sectors. Secondly, to apply the carbon emission coefficient, the classification of oil products by the Korea National Oil Corporation was adjusted to match the classification scheme of the IPCC. For the classification of oil, 14 medium categories - gasoline, kerosene, light oil, bunker A, heavy oil, bunker C, naphtha, solvents, jet oil, LPG, asphalt, lube, heavy end oil, and others - obtained from the Korea National Oil Corporation were utilized. Among the 14 categories, the heavy end oil is classified as a separate category by the company, but in reality, it is subdivided into and used as heavy oil and kerosene, so the emissions from the heavy end oil were reassigned to heavy oil and kerosene categories. As for transportation, the heavy end oil consumed by the 10 transport sectors was included in the heavy oil and kerosene category. Finally, regional
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greenhouse gas emissions were calculated by sector and oil type as seen in Figure 3.3.
② Gas Internal sales data by cities, counties, and districts from 33 gas providers across the nation were collected to assess greenhouse gas emissions in the gas sector. The 2000 to 2007 data of gas sold to six areas- home, commerce, industry, transportation, public, and others - were collected9). Gas companies supply both LNG and LPG. As LPG has already been included in the oil sector, it was excluded from the regional greenhouse gas emissions for gas, and only the sales volume of LNG was included in the estimation. In addition, as the LNG classified in the category of “others” is used for combined heat and power generation or the production of integrated energy, it was excluded to avoid overlaps with the thermal energy sector. Among the 33 gas providers from which the basic data were supposed to be collected, 31 provided data. Some of the companies did not provide full data; some periods were missing as they had been scrapped. For such missing data on sales volume of gases by city, county, and district, however, data on gas supply recorded by providers on the website10) of the Korea Gas Association were referred to, and the said data11) were applied to the cities, counties, and districts to which the relevant companies supplied gas. If at least a year’s data could be procured from the supplier and the amount of the gas supply by region could be identified, the amount of supply by city, county, and district was allocated based on this data. Two companies did not provide any data, and in such a case, the populations of the regions to which the companies provided gas were used to
9) Gas providers collect gas sales data by categories—home, general (operational), business, industry, combined heat and power generation, integrated energy, and transportation (as of Dec. 2007). Gas providers’ “general (operational)” and “business” categories were regarded as “commerce,” and their “combined heat and power generation” and “integrated energy” categories were regarded as “others.” Currently, the gas in the “public use” category is included in the gas providers’ “general (operational)” or “industrial use,” without a separate classification code. Therefore, for the “public” category, gas providers were asked to provide separate data. The category of the gas for the “public use” was classified based on the judgment of gas providers as there were no national guidelines to define the category of the “public use.” Due to obscurity of the category of the “public use,” some gas providers sent data that did not include the “public use” category. 10) http://www.citygas.or.kr 11) Data provided by 33 companies include the total gas supply by year, sector, purpose of use, and the region to which the gas is supplied (city, country, and district).
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determine the gas sales volume. For estimating regional greenhouse gas emissions in the gas sector, the『 Tier 1』methodology of the 1996 IPCC Guidelines was applied.
③ Coal There is no data on the coal consumption (anthracite & bituminous coal) by cities, counties, or districts. Therefore, greenhouse gas emissions from the consumption of coal were estimated using the data in the “Annual Report of Regional Energy Statistics,” which includes data on the consumption of anthracite and bituminous coal, respectively, classified by sector and by region (metropolitan cities and provinces). Like thermal energy, the statistical data of the years 2000, 2003, 2005, and 2006 were used from the said annual report. For the estimation of greenhouse gas caused by coal consumption, the classification of sectors described in the Annual Report of Regional Energy Statistics was used. Figure 3.4 outlines the greenhouse gas produced from coal by sector. Among the sectors, coal for generation is coal used to generate power or thermal energy, and to avoid overlaps, it was excluded from the estimation. As the data on coal consumption were available only for metropolitan cities and provinces, the emissions of greenhouse gases at only the metropolitan
Figure 3.4. Greenhouse Gas Emissions in the Coal Sector
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city and province levels were estimated. For estimation of the greenhouse gases from coal consumption, the『 Tier 1』methodology of the 1996 IPCC Guidelines was applied.
④ Electricity For the estimation of greenhouse gas emissions for electricity by city, county, and district, the sales figures of each sector provided by the statistics team of KEPCO were used. To obtain data prior to 2003, the sales figure of each seller had to be accessed individually and the data thus obtained, rearranged because the electricity industry went through a structural reform in 2001. For this reason, only data after 2003 were used. In case of electricity, the green house gases produced by end users are linked with energy demand management measures by region. As power generation plants, which are emission sources, are managed by the central government, this study intended to estimate regional greenhouse gas emissions based on the consumption of electricity by cities, counties, and districts, which are the end users of electricity. In other words, this study intended to estimate greenhouse gas emissions based on final consumption destinations by city, country, district, to develop a bottom-up approach. However, it is difficult to trace the source of electricity at its final destination because the electricity generated from power plants, which are the direct emission sources, is collected at the Korea Power Exchange and distributed to each region by KEPCO. A case in point is electricity from nuclear power plants even though they do not discharge greenhouse gases. In case of nuclear power plants, it is difficult to identify the end-users of the electricity generated from nuclear power plants. Therefore, instead of the consumption of electricity by end users, this study used the sales volume of electricity to estimate greenhouse gas emissions. For the emission coefficient in the sector of electricity, the national average
Table 3.5. Method of Calculating Regional Greenhouse Gas Emissions in the Electricity Sector
Greenhouse gas emission from the electricity sector (kgCO2eq/yr) = Σ used electricity (kWh/yr)×the emission intensity of greenhouse gas in the generation sector (CO2eq/kWh)
※ The CO2 emission intensity of the generation sector: 0.436kgCO2/kWh ※ The CH4 emission intensity of the generation sector: 0.00021kgCO2eq/kWh ※ The N2O emission intensity of the generation sector: 0.00078kgCO2eq/kWh ※ Electricity sales by sector: home, public, service, farming and fisheries, mining, and manufacturing
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Figure 3.5. Process of Calculating Regional Greenhouse Gas Emissions in the Electricity Sector
emission intensity in the sector of generation as suggested by the Korea Energy Economic Institute12) was used. Among the study report of the Korea Energy Economic
Institute, that in which the coefficient of CO2, CH4, and N2O emission intensity of the generation sector could all be applied was the 2004 report. Therefore, coefficients used in 2004 report were applied for 2003, and using the method outlined in Table 3.5 and the process described in Figure 3.5, the sales volume of the electricity of each sector was translated into regional greenhouse gas emissions. Although the basic framework is based on the 1996 IPCC Guidelines, Korea’s unique emission coefficient suggested by the Korea Energy Economic Institute was applied for the emission coefficient.
12) A study on the establishment of mid and long term policies and strategies in preparation for the United Nations Framework Convention on Climate Change (the 3rd year): A plan for the improvement of greenhouse gas inventories and statistics preparation systems, 2006, Korea Energy Economic Institute (KEEI).
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⑤ Thermal energy It is impossible to identify the consumption of thermal energy by cities, counties, and districts, with the current basic data. Therefore, the greenhouse gas emissions by cities, counties, and districts, were estimated using the statistics on thermal energy of the 「Annual Report of Regional Energy Statistics」. The annual report provides data on fuel consumption and thermal energy generated by each local heating system and facilities in industrial complexes, and the sales of thermal energy by production facility and use. However, the「 Annual Report of Regional Energy Statistics 2001」, which includes data for 2000, does not contain data on thermal energy for the industrial complex sector, but only data for the local heating system. Consequently, the sales figure of the total thermal energy, which is a sum of the sales of thermal energy by local heating systems and industrial complexes, is smaller than in other years. Therefore, in comparing annual greenhouse gas emissions according to the sales of thermal energy, it is necessary to be aware of the fact that the 2000 data does not include the sales figure of thermal energy for industrial complexes.
Figure 3.6. Composition of Greenhouse Gas Emissions in the Thermal Energy sector
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To estimate greenhouse gases released from the thermal energy, the thermal energy and electricity sales volume of「 Annual Report of Regional Energy Statistics」were used. Figure 3.6 shows greenhouse gas emissions by category in the thermal energy sector. Among the electricity sold by thermal energy generating facilities, the electricity sent to KEPCO is the electricity sold to KEPCO. As it is already included in the electricity sector, it was excluded from the estimation of greenhouse gas emissions from the consumption of thermal energy to avoid overlaps. As「 Annual Report of Regional Energy Statistics」only contains sales volume data of each thermal energy production facility, it is difficult to identify where the thermal energy is consumed. In other words, due to the provider-focused statistics, it is difficult to identify the place at which the actual energy is consumed, or the place where the consumption of thermal energy is discharging greenhouse gases. Therefore, in this study, the consumption of thermal energy at each city, county, and district was estimated by allocating the sales volume of each production facility to areas where the facilities supplied thermal energy. To identify the areas to which each facility supplied thermal energy, data on sales to each city, county, and district, classified by year and facility, were obtained from the Korea District Heating Corporation, a major local heating provider, and the sales volume by facility was allocated to relevant cities, counties, and
Figure 3.7. Greenhouse Gas Emissions Assessment Process for Thermal Energy by Region
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districts, based on that data. As for the thermal energy from facilities other than the Korea District Heating Corporation, all was assumed to be consumed in the city, county, or district where each facility (local heating system, industrial complex) is located in. Currently, the official greenhouse gas emission coefficient for thermal energy from local heating system and industrial complex is not available in Korea. Therefore, in this study, data on the fuel consumption and the total production and sales volume of the thermal energy by production facility stated in the annual report are used and the comprehensive steps outlined in Figure 3.7 are applied to estimate regional greenhouse gases from thermal energy. A study of the Gyeonggi Research Institute (2007) used a similar approach. Each local heating system and thermal energy producing facilities in industrial complexes use various fuels (bituminous coal, B-C, LSWR, light oil, kerosene, LNG, and Off-gas) to produce thermal energy. Therefore, greenhouse gas emission from the production of thermal energy was estimated based on the fuel consumption of each facility. For an estimation of greenhouse gas emission, the『 Tier 1』methodology of the 1996 IPCC Guidelines was used. However, for the fuel and energy whose caloric values and emission coefficients were not provided by IPCC Guidelines, emissions were estimated on the following assumptions. Firstly, LSWR is regarded as Bunker C, as fuel oil of low sulfur and high pour point. Secondly, the value of heating oil is used as the oil conversion coefficient for kerosene. Thirdly, LFG is excluded from the estimation of greenhouse gas emissions from the consumption of fuel, as it in itself is greenhouse gas. Finally, the source of thermal energy for KEPCO and incineration and others was assumed to be LNG, and the thermal energy conversion efficiency is assumed to be 85%. The assumptions for the estimation of greenhouse gas emissions by facility at industrial complexes are as follows: First, LSWR is regarded as Bunker C, as fuel oil of low sulfur and high pour point. Secondly, the value of heating oil is used as the oil conversion coefficient for kerosene. Thirdly, as the caloric values and emission coefficients of off-gas are not known, it was regarded as natural gas. The greenhouse gas emission intensity of each facility was estimated by dividing the greenhouse gas emission of each facility by the total output (heat and electricity) of thermal energy of each facility. Table 3.6 shows the 2005 data of the greenhouse gas emissions of each facility at industrial complexes, total output of thermal energy, and greenhouse gas emission intensity, and Table 3.7 shows the 2005 data of greenhouse gas emissions of each local heating system, total output of thermal energy, and greenhouse gas emission intensity. The indirect greenhouse gas emission from the consumption of
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Table 3.6. Greenhouse Gas Emission, Total Output, and Emission Intensity of Each Facility at Industrial Complexes (2005)
Greenhouse gas Greenhouse gas emission intensity emission Total (1000 Gcal) output 10,000 (1000G Ton CO2 Ton Ton Ton CO2 Ton CH4 Ton N2O Ton eq. CH4 N2O cal) intensity intensity intensity CO2 intensity National 1,257 310 127 56,806 221.0 0.0055 0.0022 221.8 Sinpyeong/ Busan 20 2 3 617 324.6 0.0036 0.0047 326.1 Jangnim Daegu dyeing Daegu industrial 80 9 12 2,321 321.2 0.0035 0.0048 322.8 complex Daejun Daejun 3 & 4 44 18 4 1,909 228.2 0.0095 0.0019 229.0 Total 373 105 38 16,384 226.7 0.0064 0.0023 227.5 Ulsan Ulsan Mipo 335 101 32 14,919 224.7 0.0068 0.0021 225.5 Onsan 38 4 6 1,465 245.9 0.0027 0.0037 247.1 Total 252 67 28 9,435 286.9 0.0076 0.0032 288.1 Banwol 131 19 18 4,425 301.1 0.0044 0.0042 302.5 Gyeonggi Osan 21 8 2 881 235.6 0.0092 0.0018 236.3 Icheon 88 35 7 3,402 298.9 0.0117 0.0023 299.9 Shihwa 12 5 1 727 202.1 0.0079 0.0016 202.7 South Daesan 95 31 5 6,845 153.4 0.0049 0.0007 153.7 Chungcheong North Jeolla Iksan 24 3 4 917 261.0 0.0028 0.0039 262.3 South Yeocheon 223 48 15 13,633 150.3 0.0033 0.0010 150.6 Jeolla North Gumi 111 13 16 3,183 346.8 0.0042 0.0051 348.5 Gyeongsang South Jinju/ 36 14 3 1,562 242.7 0.0095 0.0019 243.5 Gyeongsang Sangpyeong
thermal energy was estimated by multiplying the thermal energy sales volume of each local heating system and thermal energy producing facilities at industrial complexes thus gathered, by the greenhouse gas emission intensity of each facility. The indirect greenhouse gas emission by region from the consumption of thermal energy was
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Table 3.7. Greenhouse Gas Emission, Total Output, and Greenhouse Gas Emission Intensity of Each Local Heating System (2005)
Greenhouse gas Total Greenhouse gas emission intensity (1000 emission output Gcal) (1000 10,000 Ton Ton Ton CO2 Ton CH4 Ton N2O Ton CO2 eq. Ton CO2 CH4 N2O Gcal) intensity intensity intensity intensity National 468 120 19 22,713 206.1 0.0053 0.0008 206.5 Seoul 97 25 4 5,545 174.0 0.0044 0.0007 174.4 Namseoul 0.0234 0 0 942 0.2 0.0000 0.0000 0.2 Gangnam 44 15 3 2,069 212.4 0.0073 0.0014 212.9 (Ilwon & Songpa) Sangam 0.0040 0 0 245 0.2 0.0000 0.0000 0.2 Gangseo 29 5 1 1,263 231.9 0.0042 0.0004 232.1 Nowon 23 4 0 1,027 226.4 0.0041 0.0004 226.6 Haeundae, Busan 57 1 0 361 156.1 0.0028 0.0003 156.2 Daegu 24 9 2 854 282.7 0.0111 0.0022 283.6 Incheon 21 4 0 711 298.3 0.0053 0.0005 298.6 Incheon Int'l Airport 20 4 0 665 300.7 0.0054 0.0005 300.9 Songdo 0.9 0 0 34 256.4 0.0046 0.0005 256.6 Nonhyeon 0.3 0 0 12 285.2 0.0051 0.0005 285.4 Sangmudae, Gwangju 0.2 0 0 28 7.6 0.0001 0.0000 7.6 Gyeonggi 246 64 10 14,148 173.8 0.0045 0.0007 174.1 Bundang 2 1 0 3,009 7.9 0.0003 0.0001 7.9 Goyang 2 1 0 2,243 10.4 0.0004 0.0001 10.4 Suwon 36 14 3 1,291 280.9 0.0106 0.0021 281.7 Yongin 22 8 2 1,321 167.9 0.0060 0.0012 168.4 Hwaseong (Dongta) 4 2 0 130 314.1 0.0132 0.0026 315.2 Ansan 17 7 1 646 262.4 0.0103 0.0021 263.3 Anyang 82 16 2 2,849 287.4 0.0056 0.0007 287.8 Bucheon 80 16 2 2,660 300.2 0.0059 0.0007 300.5 Cheongju, 22 9 2 639 344.6 0.0135 0.0027 345.7 North Chungcheong Pohang, 0.0035 0 0 140 0.2 0.0000 0.0000 0.2 North Gyeongsang South Gyeongsang 5 1 0 286 183.8 0.0033 0.0003 184.0 Gimhae 3 1 0 210 162.8 0.0029 0.0003 162.9 Yangsan 2 0 0 76 242.0 0.0043 0.0004 242.2
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estimated by allocating the greenhouse gas emission by sector thus obtained, to the regions to which each facility supplied thermal energy.
■ Agriculture The greenhouse gas emissions in the agriculture sector are the sum of greenhouse gases from the excretion and breath of livestock, from the consumption of fertilizers, and from rice fields. To estimate greenhouse gas emissions, statistics and data on arable acreage and consumption of fertilizers, classified by city, county, district and species of livestock were used. For statistics on the species of livestock and arable acreage, data of the annual report of each city, county, and district were used as the basic source. The greenhouse gases from the agriculture sector are divided into those from excretion decomposition, enteric fermentation, and agricultural soil.
① Excretion decomposition
The greenhouse gases resulting from excretion decomposition are methane (CH4) and
nitrous oxide (N2O). The livestock discharging greenhouse gases include cattle, (divided into milk cows and beef cattle), pigs, chickens, (layer chickens and meat chickens), sheep, goats, and horses. Their excretions all discharge methane and nitrous oxide. However, in case of excretions of sheep, goats, and horses, methane gases are produced in the process of treatment, but unlike the excretions from other cattle, their excretions do not release nitrous oxide. Greenhouse gas emission is calculated by multiplying the number of each species of livestock by the emission coefficient, and to convert methane and nitrous oxide into carbon dioxide, the estimated emissions were multiplied by the global warming potential (GWP) of “21” and “310,” respectively.
② Enteric fermentation As more than three-fourths of the greenhouse gas from enteric fermentation of livestock comes from beef cattle and milk cows, cattle is divided into beef cattle and milk cows to apply the『 Tier 2』methodology of the 1996 IPCC Guidelines, while the emissions of livestock other than cattle, such as sheep, goats, pigs, and horses, were estimated by applying the emission coefficient of the IPCC Guidelines based on its 『Tier 1』methodology. As greenhouse gas coming from enteric fermentation is
methane, it was converted to CO2 by multiplying it by GWP “21.”
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③ Rice field farming Methane gases are emitted from rice fields during the growth of rice, and the emission coefficient varies with climates, water management methods, and farming periods. The integrated emission coefficient is gained by multiplying the period of growth of rice (days) by the emission coefficient, and methane emission is estimated by multiplying the integrated emission coefficient by the rice cultivation acreage.
④ Agricultural soil
The emission of N2O from agricultural soil was converted into CO2 by multiplying the
amount of used nitrogenous fertilizer by 0.0125kg N2O-N/kg, which is the emission coefficient of the 1996 IPCC Guidelines, and again multiplying it by 44/28.
■ Waste In the waste sector, greenhouse gases are emitted during waste burial, incineration, and
sewage treatment. The gases for estimation in this sector include CH4 for burial, CO2
and N2O for incineration, and CH4 and N2O for sewage treatment. For statistics on waste, the report of the annual “Status of National Waste Generation and Treatment” issued by the Ministry of the Environment was used. In estimating greenhouse gas emissions in the waste sector, it was assumed that there were no greenhouse gases emitted in the process of waste treatment if the waste was recycled or thrown away into the sea. The greenhouse gases released in the process of burial, incineration, and sewage by city, county, and district, were assumed as being emitted from the relevant city, county, and district even if they were not processed in those areas.
Figure 3.8. Processes Producing Greenhouse Gases in the Waste Sector
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① Waste burial
CH4 is the only gas used in the assessment of the greenhouse gas from waste burial, and the estimation methods include『 Tier 1』and『 Tier 2』from the 1996 IPCC Guidelines. However,『 Tier 2』is difficult to apply without specific data because it is a method of obtaining greenhouse gases directly from the amount of carbon stored in organic wastes at waste landfill sites. For this reason, this study used the『 Tier 1』 methodology instead. As in Table 3.8, the basic framework of the calculation method is to apply the 1996 IPCC Guidelines, and as for coefficients, the unique coefficients of the Ministry of the Environment, the National Institute of Environmental Research (NIER), and the Korea Energy Economics Institute were used.
Table 3.8. Method of Calculating Methane from Waste Burial (1996 IPPC Guidelines)
: ratio of dissolvable organic carbon (0.082, Ministry of Environment 2000) : ratio of which can be assimilated by microorganisms (0.77, IPCC 1996) : ratio of volume assumed by methane in landfill gases (0.5, NIER) : methane gas collected and returned among generated gases (assuming the ratio of methane return rate as 0, KEEI 2004) : ratio of oxidation of methane gas, uncollected and unreturned, while passing through the landfill layers (0, IPCC 1996)
② Waste incineration
The greenhouse gases emitted from waste incineration are CO2, CH4, and N2O, but
CH4 was excluded as the released amount is very small. In CO2 emissions, only CO2 resulting from the incineration of abiotic waste was regarded as greenhouse gas, and
13) CO2 from the incineration of organic waste was excluded, as it was regarded as being
recycled in nature. The method of calculating CO2 from the incineration of waste is based on the 1996 IPCC Guidelines and is described in Table 3.9. The previous studies of the Seoul Development Institute (2006) and the Gyeonggi
Research Institute (2007) used the average value of N2O emission density in 2000 and
13) They consist of plastic waste, rubbers, leather, fibers, and other combustibles.
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Table 3.9. Method of Calculating CO2 From Waste Incineration (1996 IPPC Guidelines)
: the emission coefficient of incinerating waste (ton Co2/ton) : annual amount of incineration of type waste (households, businesses, discharge facility of businesses, construction) : Incineration efficiency (97%, applied by the Ministry of Environment and other previous studies) : Type of waste (domestic, businesses, and construction wastes)
Table 3.10. Emission Coefficient of Abiotic Waste Incineration
(Unit: ton CO2/ton) Plastic Rubber and Synthetic Synthetic Leather Other Classification waste leather fiber waste rubber waste waste combustibles Emission 2.347 2.094 1.408 2.299 1.870 1.045 coefficient
Note. From Survey and Statistics on Greenhouse Gas Emission in the Environment Sector, by the Ministry of Environment, 2002, and from A Study on the Characteristics of the Emission of Greenhouse Gases of the Local Municipalities of Gyeonggi Province, by Gyeonggi Research Institute, 2007.
Table 3.11. Method of Calculating N2O From Waste Incineration (1996 IPCC Guidelines)
: The emission coefficient of abiotic N2O by incineration : Annual amount of incineration of type waste : Type of waste (domestic, businesses, and construction wastes)
Table 3.12. N2O Emission Coefficient by Waste Incineration
(Unit: N2Og/ton) Emission coefficient Classification 2000 2002 (average) Sludge 323 408.42 365.71 Domestic waste 90 39.80 64.9 Business waste 149 109.57 129.24
Note. From A Survey on the Greenhouse Gas Emissions From Basic Environment Facilities, by Seoul Development Institute, 2006, and from A Study on the Characteristics of the Emission of Greenhouse Gases of the Local Municipalities of Gyeonggi Province, by Gyeonggi Research Institute, 2007.
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2002 in the Ministry of the Environment’s “Survey and Statistics on Greenhouse Gas Emissions in the Environment Sector” as the emission coefficient. This study also used the same emission coefficient as the previous studies for comparison purpose.
③ Sewage treatment Greenhouse gases are emitted during the treatment of domestic sewage (home and business sewage) and industrial sewage, and the type of greenhouse gases released during
the industrial sewage treatment are CH4 and N2O. As not enough data exist for greenhouse gases from sewage treatment by each city and county and as the weight of these gases within the national greenhouse gas emissions is very small,14) their emissions were not included in the estimation. As for domestic sewage treatment, not enough data by cities, counties, and districts are available for the estimation of recapture and treatment rate (in previous studies, Seoul applied 100% and Gyeonggi applied 0%) of methane, which is produced during the anaerobic treatment of sludge, and as for greenhouse gases from industrial sewage treatment, there are no statistics on the chemical oxygen demand (COD) of sewage by industry and amount of sewage, classified by city and county and type of business.
■ Land Use and Forests
① Forest tree absorption The amount of annual increase of biomass varies depending on whether it is a coniferous, latifolius, or mixed forest. Therefore, to estimate emissions accurately, statistics by forest type are required. However, as the statistics at the level of city, county, and district were not classified by forest type, there were limits in the accuracy of estimation. The amount of forest tree absorption of greenhouse gases was estimated by multiplying the net increase of the entire biomass by the carbon conversion factor (0.5).
14) According to the 2004 statistical data on trends of national greenhouse gas emissions (Korea Energy Economics Institute), domestic sewage treatment and industrial sewage treatment assumed 0.19% and 0.05% of the total emissions of greenhouse gases of the nation (the entire waste was 2.6%). In the waste sector, as domestic sewage treatment and industrial sewage treatment accounted for 7.3% and 1.9%, respectively, the weighting thereof in the emission of greenhouse gases is very small.
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② Lumbering The amount of commercial lumbering is based on the amount of production of timber reported in the Annual Report of Forestry Statistical. It is difficult for local administrative institutes to trace the amount of lumbering statistically by city, county, and district, but the statistical error of carbon emissions resulting from other lumbering activities should be conceded. The emission of greenhouse gases from lumbering was estimated by multiplying the total amount of consumption of biomass by the carbon conversion factor (0.5).
③ Conversion of forests The emission of greenhouse gases is estimated based on the amount of biomass decreased during the conversion of forests into other types of land, such as farming land, grassland, or others. If more accurate data is established regarding land use after any conversion of forests, a more accurate estimation of greenhouse gas emission will be made possible. For example, as new towns or residential areas under development included in the “others” category contain parks, greenery and land spaces used for other purposes, the “others” category needs to be subdivided, which is currently regarded simply as land without buildings.
④ Mineral Soil Greenhouse gas released from mineral soil is the emission caused by the long-term use of land. In this study, the emission was estimated based on the changes in land use from 2000 to 2005. In principle, the change of carbon storage resulting from the change of land use should be estimated after 20 years, which is the period of time required for land to be stabilized after land use change. However, due to time constraints, this study made estimations based on the changed amount after five years. Estimations are made by multiplying the emission coefficient (coefficient for rice field: 60.5 Cton/ha) for each type of changed land (farm, field, forest, others).
⑤ Use of lime Nonghyup is in charge of the distribution of lime for fertilizers across the nation. The lime fertilizers produced by institutes other than Nonghyup were left out of the data. Greenhouse gas released from the use of lime in agricultural soil was estimated by multiplying the amount of the supply of lime by the carbon emission conversion factor (0.120).
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4. Status and Characteristics of Greenhouse Gas Emissions by Region
Until now, greenhouse gas Figure 4.1. Change in the Total Amount of emissions had been examined Emissions as follows: i) emission by year (Unit: 1m tonCO2eq.) and source/sink, ii) emission by city/province and city/county/ district, and iii) emission by urban population size. Firstly, the total emissions by year and by sources/sinks show a gentle increase from 2000 to 2006 (refer to Figure 4.1). In the emission by sources/sinks, the greenhouse gases from the energy sector are increasing whereas those from the agriculture and waste sectors are decreasing. At the national level, the amount of absorption has been declining. This proves that political support should be placed not only on reducing greenhouse gases by controlling their sources, especially through energy saving activities, but also on the protection and management of greenhouse gas sinks. In the energy sector, which accounts for most of the greenhouse gas emissions in Korea, the weight placed on oil is decreasing, while both the size and the weight placed on electricity are increasing. This proves that the type of energy most consumed in Korea is electricity. As for the status of emissions by region, Gyeonggi Province had the largest amount of emissions, while Jeju showed the least (Figure 4.2). As for the emission per capita with the population of the cities and provinces considered, South Jeolla Province showed the highest, while Jeju was the lowest. In the analysis of over 232 cities/counties/districts across the nation, the regions with large industrial complexes, such as Yeosu, South Jeolla Province; Namgu, Ulsan; Ulju-gun; Seosan, South Chungcheong Province; and Ansan, Gyeonggi Province ranked highest (refer to Figure
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Figure 4.2. Emission by City/Province and by Source/Sink (2005)
(Unit: 100,000 ton CO2eq.)
4.2). These regions are those in which greenhouse gas emissions from energy consumption is large. This shows that the regions with large energy-consuming industries discharge much of the greenhouse gases in Korea. The cities with small emissions of greenhouse gases include Inje-gun and Hwacheon-gun, Gangwon Province; and Uljin- gun, Yeongyang-gun, and Cheongsong-gun, North Gyeongsang Province. As these regions absorb more volume of greenhouse gases than are released, their emission values are negative. As for the emission per capita with the population of the regions considered, Ulju-gun, Nam-gu, and Buk-gu of Ulsan, as well as Yeosu and Seosan where the total amount of emissions is large, ranked high, indicating that Ulsan is an area with a large amount of greenhouse gas emissions for its population. In the energy sector, which accounts for most emissions, Yeosu, South Jeolla Province; Nam-gu, Ulsan; Ulju-gun; and Gumi, North Gyeongsang Province, where large industrial complexes are located, ranked highest in the total emission category. On the contrary, Ulreung-gun and Yeongyang-gun of North Gyeongsang Province, Ongjin- gun of Incheon, Shinan-gun of South Jeolla Province, and Gyeryong-si of South Chungcheong Province were regions with small amount of emissions from the energy sector. Usually, the regions that ranked high in terms of the greenhouse gas emissions per capita were regions with high total emissions. However, when it comes to the regions with small emission levels per capita, they included the metropolitan areas of Seoul and
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Busan, belying their status in terms of Figure 4.3. Total Emissions by City/County/ District (2005) absolute amount of emissions. (Unit: 10,000 ton CO2eq.) Although Seoul and Busan do not have low absolute emission levels, their levels per capita are low. When it comes to the status of greenhouse gas emission by the population size, the mid-large-sized cities ranked highest, followed by the mid-sized cities, large-sized cities, mid- small-sized cities, and small cities (refer to Table 4.1). In other words, mid- large-sized cities with a population of 0.3-0.5 million have a larger total amount of greenhouse gas emissions per capita than large-sized cities with larger populations. Mid-large-sized cities and mid-sized cities showed total emissions per capita higher than the national average, while large-sized cities, mid-small-
Table 4.1. Emission per Capita by City Size
(Unit: tonCO2eq/person) National Mid large Mid small Small Large city Mid city avg. city city city Total emission (A+B) 8.4 7.4 11.7 9.4 6.1 1.5 Emission Total (A) 9.0 7.5 12.0 10.1 8.7 8.7 Energy 8.4 7.1 11.3 9.0 6.6 6.5 Oil 2.6 2.4 5.6 4.2 3.2 2.9 Electricity 3.0 3.3 4.0 4.0 3.3 3.6 Gas 0.8 0.9 0.8 0.5 0.1 0.0 Thermal 0.3 0.4 0.9 0.3 0.0 0.0 Agriculture 0.3 0.0 0.2 0.7 1.4 1.7 Waste 0.3 0.3 0.5 0.5 0.7 0.5 Land use and forest (B) -0.5 - 0.1 -0.3 -0.8 -2.5 -7.2
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sized cities, and small cities showed smaller amounts of emissions per capita than the national average. As for the amount of absorption per capita, smaller cities, or cities with a smaller population, showed higher absorption levels per capita. This indicates that regions with smaller populations have a larger spread of sinks. On the contrary, the greenhouse gases produced from farming increased as the cities became smaller. The specific reasons for these emission characteristics among cities of different sizes will be understood through an analysis of correlations between regional conditions or characteristics and regional greenhouse gas emission levels.
5. Utilization of Inventories for Sustainable Land Management
To suggest CO2 reduction policies customized for each region , the correlation between
the CO2 per capita produced from the inventory and the regional characteristics of 39 areas were analyzed. The result of the analysis showed that the regional factors demonstrating a positive (+) relationship with greenhouse gas emissions include urbanized areas per 10,000 persons, ratio of industrialized areas, and numbers of vehicles registered per 10,000 persons. The factors that showed a negative (-) relationship included population density and area (ratio) of greens. This indicates that protecting and expanding sinks, such as parks and green areas, are essential for any reduction of greenhouse gas emissions. In addition, this makes it possible to generate factors that are effective for reducing greenhouse gas emissions for cities of each size. Lastly, it was found that the factors relating to area size, land use, and transportation sector are more related to the amount of greenhouse gas emissions than any socio- economic factors. These factors are related to physical spatial plans such as urban development and land use and imply that it is possible to reduce greenhouse gas emissions by complementing spatial plans, such as housing, commerce, industry, and green areas, according to the size of the city.
Next, the CO2 emission intensity was estimated by using the greenhouse gas
inventory. Given that CO2 is produced by various human production activities, the level
of CO2 emissions can vary depending on how the land is used. The CO2 emission
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Figure 5.1. Framework for Estimating and Utilizing CO2 Emission Intensity by Land Use
intensity by land use types identified through this study can be useful in realizing a low- carbon society in preparation for climate change. Figure 5.1 shows the process used in
this study to estimate and utilize CO2 emission intensity by land use types. For case study, the GIS data was compiled by collecting the amount of energy consumed and the land parcel information by address in some parts of Daegu Metropolitan City. For micro analysis, the information on the building use stated in building ledgers were reclassified
and used in estimating the CO2 emission intensity by use, and the GIS-based spatial
analysis method was applied. For the estimation of CO2 emissions by region, the bottom- up or top-down approach can be adopted depending on availability of energy consumption data by land use types. With the bottom-up method, a more accurate and microscopic analysis can be conducted, as it uses the information of the energy consumed by end users.
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According to the results of averaging and integrating CO2 emission intensity by use of land, the emission intensity of central commercial facilities was the highest (315.9kg/㎡∙yr) based on the lot factor, while the emission intensity of industrial and distribution facilities was the highest (193.6kg/㎡∙yr) based on the floor area factor. As for residential buildings, the detached housing unit was 63.3 (kg/㎡∙yr) and the apartment housing unit was 48.5 (kg/㎡∙yr). This means apartment houses have a
smaller CO2 emission intensity per unit area than detached housing. As for commercial facilities, the general commercial facilities was 163.4 (kg/㎡∙yr), while the central commercial facilities was 83.0 (kg/㎡∙yr). Central commercial facilities showed a
smaller CO2 emission intensity compared to general commercial facilities because of their higher density land use characteristics. As for public facilities, welfare facilities or pressure facilities among neighborhood public facilities showed a high energy use level and quite a high emission intensity of 147.0 (kg/㎡∙yr). The emission intensity for industrial facilities was estimated at 193.6 (kg/㎡∙yr), which is the highest based on the floor area size. It can be assumed that industrial and distribution facilities show low density land use. Based on data from the energy consumption at the micro level, this
analysis identified the spatial distribution pattern of CO2 and regional characteristics. They are expected to be used in making energy-saving and low carbon land use plans. There are limitations in utilizing the case studies on greenhouse gas inventories in terms of data or analysis methods, but this study is significant in that it suggests the possibility of utilizing greenhouse gas inventories. In addition to the two abovementioned cases, the inventories could be utilized in various forms for forming policies on sustainable land management. For example, the transport sector can use them in setting greenhouse gas emission restriction zones, while the industrial sector can use them for the control of industrial processes through the mapping of greenhouse gas emissions, as well as for the management of floor space indices by analyzing the degree of emissions by housing density. In the construction sector, they could be used to forecast the amount of greenhouse gas when establishing suitable land use plans, because the inventories facilitate the estimation of greenhouse gas emissions according to the ratio of housing, commerce, industry, and green areas.
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6. Conclusion
6.1 The significance of this study
The first year study to establish sustainable land management strategies in preparation for climate change is significant largely from three standpoints. Firstly, this study was the first to make estimations of greenhouse gas emissions at local municipalities level across the nation, paving the way for devising various strategies and measures to combat emissions. Secondly, it took the first steps towards examining the dominant factors affecting greenhouse gas emissions by analyzing the correlation between
greenhouse gas emissions and local conditions. Lastly, the study assessed CO2 emission intensity by land use and thereby, made it possible to review the methods to reduce greenhouse gases by each land use type. More specifically, the significance of this study is as follows:
6.1.1 Estimation of greenhouse gas emissions of each local municipality across the nation
This study estimated the greenhouse gas emissions of 232 local municipalities across the nation for the first time in Korea. The data on the status of greenhouse gas emissions for each region demonstrated the necessity of establishing different policies for regions when ministries, departments, and local municipalities establish policies for mitigating greenhouse gases against climate change. If some local municipalities exhibit differences in greenhouse gas emissions even though their regional characteristics and sizes are similar to other regions, it is necessary to identify the reasons and develop different policies suitable for those regions. At the national level as well, estimation of regional greenhouse gases will make it easy to determine the degree of influence such systems as emission trading system or carbon taxes will have on each region and supporting measures.
6.1.2 The attempt to analyze the correlations between greenhouse gas emissions and local conditions
The factors affecting the amount of greenhouse gas emissions include the density of
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carbon dioxide, size of forests, urbanized areas, population size, amount of livestock, and size of buildings. To identify the factors affecting greenhouse gas emissions more specifically, it is necessary to analyze the correlations between greenhouse gas emissions for each region or corporation and the characteristics of the region or corporation. This study outlined the factors affecting greenhouse gas emissions through an analysis of the correlations between 39 factors related to local conditions and greenhouse gas emissions by region. It is possible to prepare plans to reduce greenhouse gases by identifying the dominant causes for the differences among the areas where greenhouse gas emissions are over the average, the areas with no emissions of greenhouse gases, and the areas where the amount of absorption is larger than that of emission, and control such differences and factors.
6.1.3 Estimation of CO2 emission intensity for each land use type
Once the CO2 emission volume by land use types are identified, it becomes possible to make suitable land management plans. Although there were some previous studies that
estimated CO2 emissions by building use type, this study attempted to estimate the CO2 emission intensity for each land use type, taking into account the land, building type, and floor area size for the first time. The results of the estimation can be used in preparing land use plans that take into consideration the proper size of the land by land use types and their potential greenhouse gas emissions.
6.2 Implications for policy
As this study is the first year result of a three-year study entitled “Climate Change and Sustainable Land Management Strategies in Korea,” it does not have a large number of policy implications. However, a few policy implications were derived while preparing
data that shows the CO2 emission status of each city, county, and district at a glance and while analyzing their correlation with local characteristics. Firstly, the data on the status of greenhouse gas emissions by region suggest various implications for policies according to the method of comparison among regions. If data on the status of greenhouse gas emissions for 16 cities and provinces, for 232 cities, counties, and districts, for different city sizes, between cities and farming towns, and for different population densities, are analyzed, the directions and countermeasures to
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mitigate greenhouse gases against climate change according to the characteristics of each region can be established. However, if time series data for greenhouse gas emissions by region are established and the characteristics of each region are analyzed in a more detailed way, more concrete policy alternatives can be established. The status of greenhouse gas emissions in forest areas reminds us of the importance of the role of forests as sinks and shows us that the policy initiative of top priority for the greenhouse gas reduction is expansion of forests. For instance, this study can be used to numerically show the actual effects of policy implementation, when the government tries to prevent the change of use of forests and increase biomass by growing forests. Also, since it is shown that the greenhouse gas absorption rate per capita is superbly high in small cities and countries, policies that take into account this fact can be suggested. For example, this study can be used as grounds to reinforce support for cities and counties with higher absorption capabilities, or used as the basic information and grounds in pushing ahead the policy to grant economic incentives to cities and counties with higher absorption capabilities. The analysis of the correlations between greenhouse gas emissions for each region and local conditions could provide us with the foundations for executing policies for the reduction of greenhouse gas emissions for each local municipality. By gaining an understanding on the sources that emit the most greenhouse gas in each region, local municipalities can set up measures that are tailored to each region. It will also be used as the framework data to judge the effectiveness of a policy after it is executed. Once the “greenhouse gas emissions prediction model” is prepared in the 2nd year of the study, it will be possible for local municipalities to identify more specifically the sources that require emission reductions and accordingly, establish customized measures. The most important implication for policy is that the study has shown the necessity of applying different greenhouse gas mitigation policies by region, by suggesting the greenhouse gas emissions status for each region.
Thirdly, the CO2 emission intensity by land use can be utilized in making land use plans in the future to prepare for the climate change. In case of existing cities, greenhouse gas emission scenario can be made by land use plan when making urban regeneration plans. When making regeneration plans, obviously, various factors (the result of the analysis on the correlations between local conditions and the amount of greenhouse gas
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emissions) related to the amount of greenhouse gas emissions should be considered. In
case of new towns, they can be used to assess the amount of CO2 to be released according to land use change and therefore, as a standard for selecting alternatives when choosing sites for the development of new towns. In other words, they can be used in regenerating existing cities as well as in making land use plans for new cities. Fourth, the classification by energy source will ultimately become instrumental in setting the direction of statistical data related to the climate change. However, it is not easy to establish a greenhouse gas inventory because the classification system is different by energy sector and data are not sorted by cities, counties, and districts. Above all, statistics generating method should be improved in order for each local municipality to establish measures against the climate change. The classification standards and division of regions attempted in this study will be helpful not only for relevant ministries and departments but also for relevant institutes related to each type of energy and municipalities in preparing alternatives.
6.3 Limitations of this study
As mentioned in the characteristics of this study, there are some limitations herein, as the study has attempted some methods and collected and arranged data for the first time. Firstly, there is a limitation in the appropriateness of the methods and processes used. The methods, processes, and emission coefficients used in the course of estimating greenhouse gas emissions for each region across the nation were arbitrarily determined by the researchers of this study after consulting experts and relevant literature. Due to limited research period, there were limitations in applying other methods and emission coefficients and therefore, some limitations in the suitability of the methods and emission coefficients used in this study. The second limitation is the arbitrary composition of data. In the process of collecting data for establishing a greenhouse gas inventory, when the statistics by sector were in different formats or if they were in formats that were not compatible with the framework suggested by the IPCC, the collected data were reclassified and some data combined with others to compose the basic data. In particular, the basic data related to sources and sinks were in different formats and had to be arbitrarily reclassified, and thus, there were limitations, but it appears that such trials and errors would provide help to conducting similar type of researches.
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Thirdly, there are limitations in the accuracy of data on the status of greenhouse gas emissions by region due to the limitations of methodologies and data collection. It is unavoidable to have limitations in comparing and interpreting greenhouse gas estimations among regions. In particular, the correlation analysis between greenhouse gas emissions and local conditions provides useful information, but it has limitations in that it does not provide sufficient data on the relative importance of individual indicators. However, given the exclusion of the industrial process sector from the inventory, when the greenhouse gas emissions by region are added up, they are close to the national greenhouse gas emission estimates. Therefore, even if the results of this study should be used carefully for academic purposes, there are no significant problems in using them for preparing policy alternatives.
Lastly, as only parts of Daegu Metropolitan City were used in establishing the CO2 emission intensity for each land use type, naturally, there are limitations in interpretation
and extrapolation. It is also necessary to analyze the characteristics of CO2 emissions of city and non-city areas by dividing the regions for case studies.
6.4 Conclusion
Recently, green growth has become a major issue in Korea. Each central government and local municipality is making an effort to develop new policies. Green growth is suggested as a national growth strategy, capable of changing the energy crisis and climate change threats into opportunities. Developed countries have already made efforts to secure green industries and green technologies as new growth engines. The competition to attain an edge in dealing with climate change and in securing growth engines is called the “Green Race,” and this implies that nations consider green growth not as an option but as an essential agenda for national prosperity. Green growth responds to the problems of energy and climate change by combining environmental preservation and economic growth. However, current green growth initiatives have a tendency of focusing on economic growth by securing growth engines. This is not different from the gray growth concept, which focuses on quantitative growth. For green growth to be successful, the focus should be on achieving a low carbon society by reducing greenhouse gas emissions. In the process, new growth engines should be developed based on the development of new renewable energy and innovation of green technologies, and they in turn, should be made into catalysts for reducing greenhouse gases.
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Therefore, to promote more intensive green growth, it is most important to discover and practice viable policies to reduce greenhouse gas emissions. The effects of any executed policies should be measured and, based on the results, more effective policies and means should be developed. In addition, customized greenhouse gas reduction plans should be suggested for each region. In this context, it can be said that data on the status of greenhouse gas emissions are the most essential information in pushing successful green growth. Establishing database to support and drive the policies is as important as developing the policies themselves. This is the role of policy research institutes.
Figure 6.1. Data on Greenhouse Gas Emissions by Region, the Basis of Green Growth
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WMO & UNEP 3. (2007). Climate change 2007: Impacts, adaptation and vulnerability. Working Group II Contribution to the Fourth Report. WMO & UNEP 4. (2007). Climate change 2007: Mitigation of climate change. Working Group III Contribution to the Fourth Assessment. World Commission on Environment and Development. (1987). Our common future. Oxford Paperbacks, ISBN 0-19-282080-X.
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KRIHS SPECIAL REPORT 2010
�Eun-sun Im �Kirl Kim �Dae-jong Kim �Yoon-young Jeong �Gyoung-ju Lee �Jong-duk Park �Young-joo Lee 0709-SpecialReport vol 16 2010.7.20 9:46 AM 페이지90 열림4 HP-LaserJet-A3
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Applications of KOPSS (KOrea Planning Support Systems)
Eun-sun Im et al.
1. Overview
1.1 Background
Recently, the national territorial environment has changed significantly both internally and externally, mainly due to the global economic crisis and climate change. Korea has been implementing various large-scale national projects to respond to these changes and to strengthen territorial competitiveness. Project examples include planning of the super-regional economic zone, energy-saving land utilization in response to climate change, supporting provincial cities, and water resource management. Once these national projects are carried out fully, there may be significant irreversible changes to the national spatial structure. Therefore, it is urgently required that Korea develop a system that can forecast the future through simulation or diagnose the effects of those projects in advance. Several advanced countries have been utilizing GIS to comprehensively review several issues that may arise while establishing national spatial planning, and to evaluate any necessary alternatives for objective decision-making. UrbanSim, MetroScope, and PECAS are examples of Planning Support Systems (PSS) that support spatial planning based on GIS. Since the late 1990’s, Korea also has been accumulating various national territorial spatial data through the National Geographic Information System (NGIS) project. As a result, the foundation has been set to develop and apply a planning support system similar
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to what has been observed overseas. Against this backdrop, the Korea Research Institute for Human Settlements (KRIHS) has been implementing the development of Korea Planning Support Systems (KOPSS) with funds from the Ministry of Land, Transport and Maritime Affairs (MTLM) since 2006.
1.2 Objective
KOPSS is a Korean-style planning support system that can assist in various spatial planning outcomes, such as national territorial, regional, and urban planning. This system utilizes data such as land, building, administration, and statistics, accumulated by the central government and local governments. KOPSS consists of spatial analysis models and has been developed based on GIS technology to support the scientific and rational implementation of land use, regeneration, facilities, and landscape planning.
1.3 Components of KOPSS
Generally, the spatial planning is implemented as follows: It reviews existing systems and statistical data at the initial stages in order to understand the spatial problems. At the next stage, the planning objective is established and various indices and alternatives are identified based on the understanding of the situation. Then, we run a simulation to forecast the changes the plan would bring about if it is implemented. KOPSS supports all the information required for a series of spatial planning processes. KOPSS targets spatial planning businesses that require an analysis model. The upper-level of spatial planning provides the specific direction and guidelines to lower- level planning. Korea also has been establishing the spatial plans systematically in accordance with the National Territory Law and the Act on National Territorial Planning (Law Regarding National Territorial Use and Planning). Based on Korea’s spatial planning business, we have developed a Regional Status Analysis Model, Urban Regeneration Planning Support Model, Landscape Planning Support Model, Urban Public Facility Planning Support Model, and Land Use Planning Support Model as components of KOPSS (See Figure 1.1). KOPSS provides data processing, spatial analysis, and analysis result presentation functions. Figure 1.2 shows the system configuration of KOPSS. KOPSS requires integrated database that is similar to the data warehouse in characteristics,
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Figure 1.1. Components of KOPSS
which effectively collects and manages the large amounts of data from various sources such as land, building, and facilities. Meanwhile, the government is implementing a national integrated spatial database building (NISD) project. The goal of this project is to collect all kinds of data that need to be shared and make them accessible in various ways. Therefore, we now are implementing the KOPSS project jointly with the NISD project. KOPSS also has data management tools, knowledge management tools, and interested party opinion collection tools for the analysis model.
1.4 Development strategies
KOPSS uses the data mart to implement analytical models that integrate diverse spatial databases dispersed across several systems. KOPSS’s data mart is created by linking and utilizing the data of relevant systems, such as the Korea Land Information Systems (KLIS), and Architectural Information Systems (AIS) (See Figure 1.3). As the databases of the native systems are for specific business activities, it needs to be processed properly for the data mart. As a general rule, however, KOPSS uses the original data structure as much as possible, considering data updates in the future. In addition, KOPSS places an emphasis on “compliance with international standards,” “securing inter-operability among systems,” and “development of open systems based on various engines.” It aims to build a foundation that can encourage the
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Figure 1.2. System Configuration of KOPSS
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participation of domestic GIS engine vendors and linkage with and utilization of relevant systems, such as the national spatial information system, KLIS, and UPIS. An open Application Programming Interface (API) development project has been underway since 2009. As part of the development project, we are designing the open API to comply with the Open Geospatial Consortium (OGC) service standard (See Figure 1.4). The KOPSS open API conforms to the OGC standard interface, and consists of four services, as shown in Figure 1.4. Map and data services are provided with the interface defined by Web Map Service (WMS), Web Feature Service (WFS), and Web Coverage Service (WCS). Analysis services are provided by utilizing the analysis results of WMS, WFS, WCS, and WPS as a resource, based on Web Processing Service (WPS). This means that any client from web to desktop, can access this service if the client conforms to the standards. When designing the WPS process, an emphasis was placed on scalability and inter-operability rather than business processes. As a result, the unit of WPS is basic GIS functions corresponding to the minimal business. We have also considered linkage with related systems in the future.
Figure 1.3. Development of KOPSS Data Mart
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Figure 1.4. Open Application Programming Interface
Web Client Desktop Client Thin Client Rich Client Thick Client Editing Simple Image AJAX Sophisticated ActiveX RIA Advanced GIS App.
Geo task Advanced analysis Client task based based task Java Applet Flex/Silverlight GIS Object
Standard Channel - Http Get(KVP)/POST(XML, SOAP)
OGC Web Service(OWS) Web Procesing Services Geometry Service Vector Anaysis Grid Coverage Statistical Analysis KOPSS Model Services Anaysis Services Services Service Service Web Map Service Web Feature Service Web Coverage Service Server Features Display Object Basic Feature & Grid Coverage Processing Application GIS WAS Web Engine
Server Spatial Objects Coordinate Ref.Sys Grid Coverage Objects Application Data Provider
ArcSDE Tibero ZEUS PostGIS Commercial File-based Data Altibase GMS 4G MySQL
Server RDMS
1.5 Future plans and expected effects
The number of local governments wanting to adopt the developed KOPSS model has increased with changes in the paradigm or conditions of the spatial planning. Only a few local governments, including pilot and collaborative local governments have been adopting the system until the fourth project. However, as the development of the open API has seen some progress, we are planning to let more governments adopt the system from the fifth project, which will be launched in early 2010. The core of KOPSS is the analysis models. We will keep verifying and advancing the models to provide highly reliable information for spatial planning. In addition, the KOPSS open API is expected to promote the domestic GIS industry because it allows various standard-based GIS engines to be used for KOPSS application. It will also pave the avenue for sharing data and analysis functions among application systems in the public sector. Consequently, domestic GIS vendors can improve their competitiveness in the global market, and local governments can reduce cost for the project from the
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participation of numerous vendors. KOPSS as a planning support system expects to advance spatial planning work processes by comprehensively utilizing the achievement of the NGIS projects to date. We will describe five major models in detail in the following sections.
2. Regional Planning Support Model: REPSUM
2.1 Business processes and goals
The government is implementing various development projects for underdeveloped regions throughout its ministries and offices to achieve balanced development of the national territory. The Ministry of Land, Transportation and Maritime Affairs (MTLM) has been designating development promotion districts and supporting regional development projects every year. The implementation status of these projects is managed using the Regional Information System (RIS) by MLTM, and the Comprehensive Management System for the Regional Industry Promotion Project by the Ministry of the Knowledge Economy (MKE). However, relevance among individual projects or synergy effects is not being reviewed in detail, as several central agencies implement projects in accordance with their own applicable laws and regulations. Consequently, it has been pointed out that national finances are being wasted due to the duplicated implementation of similar projects or ineffective project implementation. The Regional Planning Support Model (REPSUM) identifies the distribution characteristics of nation-wide regional development projects that are being implemented and managed by each central office, and supports the regional development project planning by reviewing the potential characteristics of the region. This model is designed to provide a range of basic information required for the regional development planning by providing the regional development status and national territory index data in the form of GIS spatial data.
2.2 Components
The REPSUM consists of four analysis components: the Regional Development
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Project Analysis, Regional Index Analysis, Regional Spatial Structure Analysis, and Regional Industry Analysis (See Figure 2.1). The Regional Index Analysis tool analyzes representative indexes that diagnose regional characteristics and issues. It analyzes statistical changes and spatial patterns of each regional index, and presents the analysis results in a thematic map. A spatial statistical analysis function is also provided for advanced users. This tool can analyze various distribution characteristics of spatial autocorrelation, spatial clustering, and spatial segregation. The Regional Spatial Structure Analysis tool analyzes spatial interaction using trip data such as commutation and school attendance among regions. Inter-regional trip volume by origin-destination is important information in analyzing the spatial structure of the region. In addition, the ripple effects of a regional development project (industry sector) implemented in a specific region can be estimated using the industry linkage structure analysis function. The Regional Industry Analysis tool consists of the industry distribution function that analyzes the spatial distribution or distribution density of the individual factory, the industry specialization function that identifies the spatial agglomeration patterns of the industrial location, and the industry development potential functions that identify
Figure 2.1. Components of REPSUM
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accessibility to cities, major arterial roads, or railway stations around the industrial complex. Lastly, the Regional Development Project Analysis tool analyzes the status of district designation for regional development project by project type. The interested site can be easily determined using the location information of the project district.
2.3 Case studies This section describes an example of using the REPSUM. Figure 2.2 shows the “population by administrative district” and “distribution of population over 65 years old” by city, county, and district. Areas that have relatively higher proportion of elderly population can be identified easily. These areas should be reviewed to determine whether the welfare facilities for the elderly are being supplied appropriately. In addition, we should recognize that these areas require support policies for the elderly at a broad level. As described above, the model can analyze various index changes and distributions to develop an understanding of the regional development status. We can identify the structure of inter-regional trips using the Regional Spatial Structure Analysis tool. According to the factor analysis using inter-regional traffic volumes by origin-destination, small and large trip zones are formed, based on the central city in the region. Figure 2.3 classifies the daily trip zone using the commutation volume
Figure 2.2. Population by Region
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Figure 2.3. Inter-Regional Trip Volume
Figure 2.4 Spatial Distribution Pattern of All Industrial Locations in North Gyeongsang Province
Automobile and trailer manufacturing business
Thematic map
Spatial specialzation Verified spatial specialization index (10,000m) index (10,000m)
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data, which shows the structure of the Seoul Metropolitan area. The population size of the city in question is expressed by the size of a circle, and inter-regional trip volume is illustrated by the thickness of the connection line. Next, we describe an example of analyzing the location and spatial scope of an industrial cluster using the Regional Industry Analysis function. Spatial agglomeration of individual factories in all sectors for the entire North Gyeongsang Province was analyzed. The degree of spatial concentration among relevant industries can be analyzed when a specific target industry and related industries are selected. Figure 2.4 illustrates the distribution of industries related to automobile and trailer manufacturing in North Gyeongsang Province. In addition, the degree of spatial specialization of the target industry was analyzed using a spatial location quotient, by testing the statistical significance of the industrial cluster verified by converting the spatial specialization index to the standard normal distribution variate. This function can be utilized to support a regional industry support plan by providing various data, such as overall characteristics of the regional industry, spatial distribution, and industrial growth potential.
Figure 2.5. Regional Development Project Analysis
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As shown in Figure 2.5, the Regional Development Project Analysis function can identify designated development promotion districts for developing depressed regions, and analyze the distribution characteristics of development projects being implemented within the region according to their types.
3. Land Use Planning Support Model
3.1 Business processes and goals
The land size of Korea is small and the proportion of land available for human settlements is very low. The core of national territory planning is how to make best use of the limited land resources. Land use planning is an activity designed to promote rational use of land resources. It determines the spatial structure. Almost all spatial plans employs land use planning, from long-term plans such as the Comprehensive National Territorial Plan and Comprehensive City Plan to the New Town Development Plan, Urban Regeneration Plan, and the District Unit Plan for small-scale project districts. In general, there are several steps to land use planning: “environment analysis,” “land demand prediction,” “suitability analysis,” and “land use allocation.” Each step requires expert knowledge and analysis. Also, various decisions are made in the process of land use planning, requiring analyses of vast amounts of data. In addition, land use planning tends to develop an “alternative” that is dependent on the policy direction, which is determined by the situation or circumstances, rather than any “correct answer” according to pre-defined laws or guidelines. Therefore, several alternatives should be reviewed for any single issue. However, most of those in charge of city planning in local governments are generally public officials rather than specialists. As a result, planning is frequently commissioned to an external expert or a specialized company. This sometimes causes several problems, such as non-transparent planning processes and uncertainty in decision- making, which results in a rejection of the costly land use plan by citizens. Advanced foreign countries have been using planning support systems for years, which can support land use planning, for metropolitan planning and policy-making.
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However, R&D in this area is not yet well-developed in Korea. Considering that various development projects and land use plans are burgeoning throughout the country, securing a means to carry out land use planning more rationally and scientifically is required. Korea has been implementing the national GIS project since the late 1990’s, and various attribute data and spatial data have been accumulated as a consequence. If the data can be utilized actively in the process of land use planning, more reasonable and objective results can be obtained.
3.2 Components
The Land Use Planning Support Model of KOPSS comprises the functions that provide information for the planning process - from basic environment analysis to alternatives comparison (See Figure 3.1). It can perform environment analysis, development potential analysis, candidate site analysis for development, land area calculation for land demand, land suitability analysis by type, land use allocation by type, and alternatives comparison required in land use planning process.
Figure 3.1. Components of Land Use Planning Support Model
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3.3 Case studies
Figure 3.2 illustrates the procedures for utilizing the Land Use Planning Support Model. The following section suggests its application on the analysis of potential sites for land development. We have conducted a case study with a scenario that we needed a site for developing a new complex city of an area approximately 3㎢ in Dalseong-gun, Daegu Metropolitan City. Dalseong-gun has a green belt area of 194,620㎢ and a preservative green zone of 25,150. The site inventories of this area are analyzed from the perspectives of the physio-ecological environment and socio-economic environment, as shown in Figure 3.3. The maps show standardized results for computing suitability scores. The standardization process aims to evaluate the score of each variable into a value between 0 and 1, using a fuzzy function and a linear function. Weight is given to each variable at the stage of development potential analysis in order to calculate suitability scores. Table 3.1. shows weights that are obtained through interviews
Figure 3.2. Procedures for Utilizing Land Use Planning Support Model
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Figure 3.3. Site Inventory
Physical Factors
Elevation Slope Ecological and Green Environment
Physio- ecological Environment
Degree of Ecological Naturality Degree of Green Naturality Hydrological Environment
River Lake Accessibility
Socio- Accessibility to Road Accessibility to Commercial Zone economic Environment Population Density
Population Density
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Table 3.1. Weights Given to Each Variable
Category Analysis Factors Priority Ranking Weight Altitude 1 0.1652 Inclination 1 0.1652 Physio-ecological Grade criterion for ecological naturalness 2 0.1583 Factor Grade criterion for green potential 2 0.1583 Distance to river 5 0.0814 Distance to lake 6 0.0668 Population density 3 0.0984 Socio-economic Accessibility to road 4 0.0831 Factor Accessibility to commercial area 5 0.0233 Consistency Ratio (CR) 0.04
with public officials at central ministries and offices, as well as those who are in charge of city planning at Daegu Metropolitan City Hall. Weights were calculated using the AHP (Analytic Hierarchy Process) method. Figure 3.4 illustrates the suitability scores. When extracting potential sites for development, we have considered two factors: suitability scores and minimum area. The average value of all pixels is 49.7 and the standard deviation is
10. Among potential sites, the Figure 3.4. Suitability Scores areas that have a pixel value (top 10%) of over 60 and the area size of over 3㎢ were selected. The results are the part of two areas (Nongong- Land Development eup and Hyeonpung-myeon), Potential as shown in Figure 3.5. Lastly, we have compared the shape index, rough land compensation, and rough land clearing amount of potential sites to analyze overall project feasibility (See Table 3.2).
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Figure 3.5. Distribution of Pixel Values and Potential Sites
Among the two potential sites selected by the analysis, Hyeonpung-myeon is recently designated as a future complex city. This result suggests that the Land Development Potential Site Analysis function of KOPSS can support actual land development planning business activities, and that the analysis result is highly reliable. In addition, we can simulate to see how the potential site changes with a different scenario. Figure 3.6 shows the simulated results, according to land use regulations in the region. Figure 3.6 (scenario 1) displays the result when the regulations were completely excluded, Figure 3.6 (scenario 2) illustrates the result when weights were applied to each regulation, and Figure 3.6 (scenario 3) shows the result where only socio-economic and physio-ecological factors were applied, without any consideration for regulations. As described above, alternatives derived by various scenarios can be used in the
Table 3.2. Comparison of Potential Sites for Land Development
Area Shape Rough land Rough clearing No. Name of potential site (㎢) index compensation (KRW) size (㎦) 1 Hyeonpung-myeon 5.9 0.11 250,000,000 21 2 Nongong-eup 9.7 0.13 350,000,000 50
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Figure 3.6. Alternative Scenarios and Potential Site
Alternative Scenario 1 Alternative Scenario 2 Alternative Scenario 3 Only socio-economic and Legal and institutional factors Weights by degree of physio-ecological environment excluded regulation applied factors considered
decision-making process for planners or stakeholders. In the meantime, we are trying to enhance the model in terms of both theory and practice.
4. Urban Regeneration Planning Support Model
4.1 Business processes and goals
Cities in Korea have experienced rapid urbanization since the 1960’s and suburbanization from the 1990’s. Nowadays, however, cities grow slowly and are entering into a mature stage. As a result, internal urban spatial improvement or re- improvement based on the “regeneration” concept emerged as a social issue, ahead of new city development, based on the “new-born” concept. Due to the necessity of urban regeneration, it became necessary to establish a way to perform regeneration activities efficiently in accordance with the Act on Urban and Residential Environment Improvement. In July 2006, the Special Act on Facilitating Urban Regeneration came into effect. Therefore, the PSS needs to be developed to support the regeneration activities of local governments efficiently, reasonably, and objectively.
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Accordingly, the Urban Regeneration Planning Support Model was designed. It provides the information required for regeneration activities using GIS spatial analysis technique. The detailed objectives of the model are as follows. Firstly, the model is designed to develop techniques that search for renewal area candidate in the city according to the characteristics of the renewal project, and provide information on the candidate site in question. By providing functions such as space use analysis, renewal area analysis, and renewal alternative analysis based on a maintenance standard, this model aims to support a fundamental study accurately and quickly prior to establishing a policy or plan. Secondly, it is designed to identify a candidate site that can support the designation of the renewal area for a residential environment improvement project, housing redevelopment project, housing reconstruction project, or urban environment improvement project in accordance with the Act on Urban and Residential Environment Improvement. Thirdly, it aims to support decision-making among public officials in charge of urban regeneration in local governments by developing a system that searches urban regeneration area candidate through the analysis of information such as construction, traffic, real estate, and population in the city center. Lastly, this model is designed to minimize regeneration project outsourcing costs through development potential analysis.
4.2 Components
As shown in Figure 4.1, the Urban Regeneration Planning Support Model has five main functions: space use analysis, renewal area analysis, renewal alternative analysis based on a maintenance standard, regeneration area analysis, and development potential analysis. The five functions of the model are divided into three stages according to the business procedure—the status analysis stage, candidate site analysis and selection stage, and regeneration area analysis stage. Functions at the status analysis stage identify “space use analysis,” and provide a degree of building deterioration and a proportion of irregular parcels of the existing city by city/country/district and block/block group/census. As a pre-stage process of selecting the regeneration candidate site, this function enables the person in charge to understand the basic status of the target area promptly and accurately. Candidate sites are analyzed and selected at the next stage. “Renewal area analysis” and “renewal alternative analysis based on a maintenance standard” belong to
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Figure 4.1. Components of Urban Regeneration Planning Support Model
this function. The “renewal area analysis” function searches for the regeneration project designation criteria in an integrated manner stipulated in the ordinance or basic regeneration plan of each local government. These include declining housing, household density by parcel, irregular parcels, and road length ratio by width. Then, it analyzes renewal area analysis targets through the spatial clustering process. The “renewal alternative analysis based on a maintenance standard” function analyzes the status of renewal project designation criteria in order to draw the boundaries of the area that the person in charge has an interest in, or retrieve the existing boundaries for analysis. According to the analysis results, a report can be prepared, or a time series simulation can be performed regarding the date the maximum declining rate is reached. “Regeneration area analysis” is the last stage. This stage comprises the “regeneration area analysis” function and the “development potential analysis” function. “Regeneration area analysis” expands individual renewal planning candidate sites, which were analyzed at the previous stage, to more than two project areas, and integrates time. The “development potential analysis” function provides information on accessibility to subway stations and major roads, and enables officials to determine the marketability of
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the regeneration facilitation project indirectly, by providing information on the regeneration area, such as the lowest, highest, and average land values, and land price per square meter.
4.3 Case studies
The Urban Regeneration Planning Support Model selects candidate sites by analyzing the targeted renewal area after analyzing the space utilization status in the city, and provides an analysis function for the selected candidate sites. These functions support the shared utilization of data by linking current business systems, and provide synergy effects by combining the system link with policy establishment and spatial planning business activities. Without quick data support and analysis technique support when performing the process that searches for suitable regions and meeting the criteria for urban regeneration and improvement projects such as residential environment improvement projects,
Figure 4.2. Result of Renewal Area Analysis and Regeneration Area Analysis
▶ Status of irregular parcel ▶ Status of declined housing
▶ Status of road length ratio by width ▶ Status of household density
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housing redevelopment projects, housing reconstruction projects, and urban environment improvement projects, the information on real estate development can be disclosed to the private sector in advance, and smooth project implementation can be hampered. However, when the Urban Regeneration Planning Support Model is used, businesses can proceed more efficiently and promptly. In addition, the legal verification procedures can be presented scientifically against civil complaints when implementing projects. To provide an example of utilizing this model, renewal area analysis and regeneration area analysis were performed for Seongbuk-gu in Seoul and Jung-gu in Daegu Metropolitan City, respectively. To analyze the renewal area candidate, irregular parcels, declining ratios, road length ratio by width, and household density by parcel around the Jung-gu area in Daegu Metropolitan City were analyzed, and the results were compared with the renewal criteria in the city ordinance. Figure 4.2 marks the results on a map, helping the person in charge to understand the status of the concerned area more intuitively. Figure 4.3 shows the result of analyzing the renewal candidate site through spatial clustering after searching the renewal project designation criteria in an integrated manner. An analysis was performed on Seongbuk-gu in Seoul, and several candidate sites could
Figure 4.3. Candidate Sites Selected Through Analysis
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be selected, as shown in Figure 4.3. When compared with the actual renewal planned site at Seongbuk-gu, the center of all candidate sites was consistent, and it was proven that no significant error was found when compared with physical criteria, such as manually calculated declined housing ratios. Figure 4.4 shows the results of simulating the dilapidation reaching date regarding the area selected by the user. Various visual presentations such as tables, graphs, drawings, and animations are available, so that the user can identify the declining status of the area in question conveniently. This helps the staff in charge to quickly respond to any complaints. Figure 4.5 is an example of analyzing a regeneration area and its potential. In Figure 4.5, the target area is restructured, the regeneration acceleration area is selected, and development potential is analyzed based on the renewal area in Jung-gu, Daegu Metropolitan City. As described above, the Urban Regeneration Planning Support Model can identify the status of the area requested by the user and select the renewal area and regeneration area. It can also be utilized to determine its marketability.
Figure 4.4. Result of Simulating Dilapidation Reaching Date
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Figure 4.5 Result of Regeneration Area Analysis
5. Application of the Urban Public Facility Planning Support Model
5.1 Processes and goals
Urban facilities are essential public goods for city residents to maintain their daily life. However, rapid urbanization in Korea has created overcrowding especially around Seoul Metropolitan Areas, causing overall deficit of essential urban public facility services. This phenomenon is often criticized as a consequence of unplanned urban development. For a city to properly function, it is important to balance the amount of public facility service with the size of demand population. Therefore, the balance between supply and demand needs to be critically considered when devising public facility plans in the schemes of comprehensive city plans, city management plans, and district unit plans, etc. In this instance, the importance of building systematic tools for supporting public facility planning processes cannot be overemphasized.
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Public Facility Planning Support Model (PFPSM) has been developed to support decision-making in facility planning processes so that urban residents can be reasonably provided with essential facility services. This model produces spatial information on densely populated regions with poor facility services. Planners especially in the urban planning committee can identify where facility services are underprovided relative to population size and estimate how deficit the services may be if any. Those regions with high residential density, if not provided with corresponding facility services, may be highlighted as top priority areas for considering the establishments of new facilities in planning processes. In this regard, it is expected that the model can play a critical role in supporting decision-making while establishing public facility plan, and this properly follows the principle of planned development founded upon in the Act on National Territorial Planning of Korea.
5.2 Constitutions of functions
PFPSM consists of two sub models. One is Facility Service Provision Suitability Assessment Model and the other is Facility Location Analysis Model. Figure 5.1 shows the sub models of PFPSM. Each sub-model has some functions. Those functions are executed in sequence. For “Facility Service Provision Suitability Assessment” sub model, users first need to select the facility and the region for analysis and then, demand and supply analysis for the selected facility (e.g., neighborhood park), followed by facility service provision suitability analysis. Then, we are ready for running “Facility Location Analysis” sub model to find out detailed information on new establishment sites. First, sites for new facility are searched and parcel information on and around candidate sites are tabulated to make sure the sites are actually available. In some cases, best location may not be suitable for setting up new facility due to various constraints such as too high land price, non-vacant land, complicated ownership problem, etc. In addition, accessibility to other major facilities is also summarized into a table. Facility Service Provision Suitability Assessment Model is to assess if facility services are properly provided to residents. To carry out the assessment, the planned amount of facility service is compared with the actual one. The planned amount is defined as the minimum level of service provision. If, for example, it is prescribed in a relevant ordinance or regulation that per capita amount of
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Figure 5.1. Sub Models of PFPSM
park services in m2 unit is 3, and when 100 residents are in a region, at least 300 m2 of park service should be provided in that region. Therefore, planned amount in a region is estimated based on the level of per capita service and the size of population in demand there. On the other hand, the actual amount is estimated by building the model founded upon Probabilistic Gravity Model (Huff model). The basic idea on building this model is that residents in the areas adjacent to large urban parks may be given more park service benefits than those in the regions farther apart. The unit of service estimation is same as that of planned amount (m2) so that quantitative comparison by region is made possible. The difference between the two estimates is assessed as the level of facility service provision suitability. The assessment results provide planning information for identifying the areas potentially worth receiving more attention in facility planning processes. The assessment information is especially critical when considerable shift in population size is expected. If, for example, new residential buildings are massively constructed in urban regeneration districts, the number of residents there and nearby regions will increase and consequently, facility services will be probably deficit in those areas. In this instance, it may be useful to see how the increase of residents may change the overall supply- demand structure in the redeveloped district and neighboring regions as well using the assessment model in planning process. Once the facility deficit areas are identified, it is reasonable to establish new facilities in those areas with a priority and then, the next task is to find out where the best
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locations for new facilities are. Facility Location Analysis Model is to identify the optimal locations for new facility establishments. This analysis is performed based on the suitability assessment results. That is, if users specify the facility deficit regions on the map derived from the assessment results, Facility Location Analysis Model finds out the detailed locations on road networks which are most suitable for constructing new facility. This task is carried out based on some location allocation models. Currently, p-median, minimax, maximin models are adopted for performing optimal location searching tasks. In addition, nearby parcel linformation such as officially assessed individual land prices, landuse, etc. are summarized into a table to check if the new candidate sites are actually available for facility establishment.
5.3 Cases for application
Figure 5.2 through 5.5 illustrate overall analysis procedures. For the illustration, urban parks in the city of Daegu, Korea was analyzed using PFPSM. Figure 5.2 shows the planned amount of facility service by region. In this figure, it is clear that southwestern parts of the city are densely populated areas. In reality, Jung-gu where a city hall is located is an old city center and many residents live in and around the
Figure 5.2. Planned Amount of Facility Service by Region
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center. Now, we can infer that a considerable level of urban park service needs to be supplied in those areas where a lot of residents are concentrated. Figure 5.3 shows the distribution of the actual amount of service. In this figure, we can see that park services are distributed around center and southeastern areas of the city as well as old city center. Visually, we may decide that residents in the high density areas may be overall satisfied with the massive amount of urban park services. However, we may need some quantitative data to confirm if our decision based on visual information is appropriate. Figure 5.4 provides such data. As shown in this figure, red-colored areas are presented as regions deficient in urban park services. This is where more services need to be supplied, considering the number of residents there. Figure 5.5 shows a map summarizing previous results (demand-supply analysis, provision suitability assessment) in sequence. In the lower-right figure, three candidate sites for new urban park construction are marked as stars. The sites are marked by optimality rank which is defined as the degree satisfying the search criteria in ascending order. That is, in case of p-median model, the location that minimizes total travel distances of residents in a region is the first candidate.
Figure 5.3. Distribution of the Actual Amount of Service
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Figure 5.4. Provision Suitability Assessment
Figure 5.5. Summary of Assessment Results
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6. Applications of the Landscape Planning Support System
6.1 Processes and goals
Most urban development pursues economic prosperity whereby more houses are built to maximize the profitability of developers. As a result, high-rise buildings tend to be intensively constructed in a city center within a short period of time, without considering the overall urbanscapes. Furthermore, reckless destruction of green land due to intensive development in urban periphery has been another primary driver of deteriorating urban landscape. Therefore, it is critical to scrutinize how development projects change urban landscapes in terms of harmonizing surrounding environment, prior to the implementation of development projects. To this end, landscape change simulation tool is necessary. The Landscape Planning Support Model is a tool that helps to plan and manage urban landscape efficiently by providing a variety of 3D simulation functions to make beautiful cities pleasant to live. As expected, this model is fruitfully used by architectural design review committee in each local government in the building plan review process among other landscape planning processes.
6.2 Constitution of functions
The Landscape Planning Support Model consists of Landscape Resource Analysis Model, Landscape Index Analysis Model, and Landscape Simulation Analysis Model (Figure 6.1). Landscape Attraction Analysis Model helps to analyze the overall landscape resources distributed over urban areas to determine landscape management zone and identify the locations of aesthetic zone, scenic zone, etc. specified in comprehensive city plans or management plans. It also aids to select landscape management zones where landscapes need to be systematically protected. Landscape Index Analysis Model provides various functions of skyline analysis, visibility analysis, average height analysis, solar access analysis, diagonal plane control analysis, blockage ratio analysis, and façade area analysis. They produce various landscape information useful in a building plan review process. For example, skyline analysis shows the visible areas and viewshafts seen from a predetermined viewpoint, and blockage ratio
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Figure 6.1. Landscape Planning Support Model
analysis helps to assess the overall sense of openness by quantifying the blockage area ratio. Landscape Simulation Analysis Model provides a variety of information relevant to topographic change by plan, 3D conversion of 2D draft, right-of-view registration/review, walking/driving view, plan change review, etc.
6.3 Cases for application
The following section describes how to use the Landscape Planning Support Model for architectural design review based on the actual case which is about building an apartment complex on 256 Yeon-dong, Jeju City. Firstly, as shown in Figure 6.2, various components comprising landscapes such as topography, geological feature, climate, river, green zone, historical heritage, industry, land use, public facility, primary viewpoint, among others, are surveyed and their distributions are examined to understand the overall landscape structure. Topographic map and land registration map are some examples of relevant data sources available to this end. Next, the way the construction of a new building changes the landscape is analyzed by converting a 2D draft of the building plan into a 3D model (Figure 6.3). The building plan is drafted to 2D using Computer Aided Design (CAD) tool. And the 2D draft of a new building is converted into a 3D model using 3D modeling tool such as 3D Studio. Based on the 3D model data, it is possible to examine how the new building affects the surrounding landscape.
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Figure 6.2. Application of Landscape Planning Support Model
Figure 6.3. Conversion into 3D Model
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A skyline analysis and a viewshaft analysis were conducted, targeting a parasitic volcano in Jeju Island. Skyline analysis aims to analyze how the overall skyline that buildings and mountains draw looks like from a view point. Viewshaft analysis is
Figure 6.4. Skyline Analysis and Viewshaft Analysis
Figure 6.5. Original 3D Model vs. Modified 3D Model
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conducted to investigate the ratio of parasitic volcano blocked by buildings from a viewpoint to entire area. This analysis produces information that is especially useful to architectural design review committees; it helps them decide whether the heights of buildings are controlled in the relevant reviewing process. Figure 6.4 shows viewshafts of parasitic volcanoes drawn by an apartment building complex from a viewpoint. Various factors affecting viewshaft change such as the locations of viewpoints, viewing angle, etc. may be easily modified by users, and any building that destroys the overall landscape can be identified and marked in red. Users can easily change the heights or locations of the buildings that may negatively affect the skyline or viewshaft. The left picture in Figure 6.5 shows the 3D model of a plan, while the right picture presents modified 3D version of the original plan. Landscape simulation analysis makes it possible to compare the original landscape with the simulated one on a screen.
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