A Preliminary Mapped Summary of Holocene Pollen Data for Northeast China
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Crop Systems on a County-Scale
Supporting information Chinese cropping systems are a net source of greenhouse gases despite soil carbon sequestration Bing Gaoa,b, c, Tao Huangc,d, Xiaotang Juc*, Baojing Gue,f, Wei Huanga,b, Lilai Xua,b, Robert M. Reesg, David S. Powlsonh, Pete Smithi, Shenghui Cuia,b* a Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China b Xiamen Key Lab of Urban Metabolism, Xiamen 361021, China c College of Resources and Environmental Sciences, Key Laboratory of Plant-soil Interactions of MOE, China Agricultural University, Beijing 100193, China d College of Geography Science, Nanjing Normal University, Nanjing 210046, China e Department of Land Management, Zhejiang University, Hangzhou, 310058, PR China f School of Agriculture and Food, The University of Melbourne, Victoria, 3010 Australia g SRUC, West Mains Rd. Edinburgh, EH9 3JG, Scotland, UK h Department of Sustainable Agriculture Sciences, Rothamsted Research, Harpenden, AL5 2JQ. UK i Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen AB24 3UU, UK Bing Gao & Tao Huang contributed equally to this work. Corresponding author: Xiaotang Ju and Shenghui Cui College of Resources and Environmental Sciences, Key Laboratory of Plant-soil Interactions of MOE, China Agricultural University, Beijing 100193, China. Phone: +86-10-62732006; Fax: +86-10-62731016. E-mail: [email protected] Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen 361021, China. Phone: +86-592-6190777; Fax: +86-592-6190977. E-mail: [email protected] S1. The proportions of the different cropping systems to national crop yields and sowing area Maize was mainly distributed in the “Corn Belt” from Northeastern to Southwestern China (Liu et al., 2016a). -
Estimating Frost During Growing Season and Its Impact on the Velocity of Vegetation Greenup and Withering in Northeast China
remote sensing Article Estimating Frost during Growing Season and Its Impact on the Velocity of Vegetation Greenup and Withering in Northeast China Guorong Deng 1,2 , Hongyan Zhang 1,2,*, Lingbin Yang 1,2, Jianjun Zhao 1,2 , Xiaoyi Guo 1,2 , Hong Ying 1,2, Wu Rihan 1,2 and Dan Guo 3 1 Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, School of Geographical Sciences, Northeast Normal University, Changchun 130024, China; [email protected] (G.D.); [email protected] (L.Y.); [email protected] (J.Z.); [email protected] (X.G.); [email protected] (H.Y.); [email protected] (W.R.) 2 Urban Remote Sensing Application Innovation Center, School of Geographical Sciences, Northeast Normal University, Changchun 130024, China 3 College of Resources and Environment, Jilin Agricultural University, Changchun 130024, China; [email protected] * Correspondence: [email protected]; Tel.: +86-431-8509-9550 Received: 31 March 2020; Accepted: 23 April 2020; Published: 25 April 2020 Abstract: Vegetationphenology and photosynthetic primary production have changed simultaneously over the past three decades, thus impacting the velocity of vegetation greenup (Vgreenup) and withering (Vwithering). Although climate warming reduces the frequency of frost events, vegetation is exposed more frequently to frost due to the extension of the growing season. Currently, little is known about the effect of frost during the growing season on Vgreenup and Vwithering. This study analyzed spatiotemporal variations in Vgreenup and Vwithering in Northeast China between 1982 to 2015 using Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (GIMMS 3g NDVI) data. -
Surface Modelling of Human Population Distribution in China
Ecological Modelling 181 (2005) 461–478 Surface modelling of human population distribution in China Tian Xiang Yuea,∗, Ying An Wanga, Ji Yuan Liua, Shu Peng Chena, Dong Sheng Qiua, Xiang Zheng Denga, Ming Liang Liua, Yong Zhong Tiana, Bian Ping Sub a Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 917 Building, Datun, Anwai, Beijing 100101, China b College of Science, Xi’an University of Architecture and Technology, Xi’an 710055, China Received 24 March 2003; received in revised form 23 April 2004; accepted 4 June 2004 Abstract On the basis of introducing major data layers corresponding to net primary productivity (NPP), elevation, city distribution and transport infrastructure distribution of China, surface modelling of population distribution (SMPD) is conducted by means of grid generation method. A search radius of 200 km is defined in the process of generating each grid cell. SMPD not only pays attention to the situation of relative elements at the site of generating grid cell itself but also calculates contributions of other grid cells by searching the surrounding environment of the generating grid cell. Human population distribution trend since 1930 in China is analysed. The results show that human population distribution in China has a slanting trend from the eastern region to the western and middle regions of China during the period from 1930 to 2000. Two scenarios in 2015 are developed under two kinds of assumptions. Both scenarios show that the trends of population floating from the western and middle regions to the eastern region of China are very outstanding with urbanization and transport development. -
R Graphics Output
China China LEGEND Previously sampled Malaise trap site Ecoregion Alashan Plateau semi−desert North Tibetan Plateau−Kunlun Mountains alpine desert Altai alpine meadow and tundra Northeast China Plain deciduous forests Altai montane forest and forest steppe Northeast Himalayan subalpine conifer forests Altai steppe and semi−desert Northern Indochina subtropical forests Amur meadow steppe Northern Triangle subtropical forests Bohai Sea saline meadow Northwestern Himalayan alpine shrub and meadows Central China Loess Plateau mixed forests Nujiang Langcang Gorge alpine conifer and mixed forests Central Tibetan Plateau alpine steppe Ordos Plateau steppe Changbai Mountains mixed forests Pamir alpine desert and tundra Changjiang Plain evergreen forests Qaidam Basin semi−desert Da Hinggan−Dzhagdy Mountains conifer forests Qilian Mountains conifer forests Daba Mountains evergreen forests Qilian Mountains subalpine meadows Daurian forest steppe Qin Ling Mountains deciduous forests East Siberian taiga Qionglai−Minshan conifer forests Eastern Gobi desert steppe Rock and Ice Eastern Himalayan alpine shrub and meadows Sichuan Basin evergreen broadleaf forests Eastern Himalayan broadleaf forests South China−Vietnam subtropical evergreen forests Eastern Himalayan subalpine conifer forests Southeast Tibet shrublands and meadows Emin Valley steppe Southern Annamites montane rain forests Guizhou Plateau broadleaf and mixed forests Suiphun−Khanka meadows and forest meadows Hainan Island monsoon rain forests Taklimakan desert Helanshan montane conifer forests -
World Bank Document
Document of The World Bank Public Disclosure Authorized Report No: 21860 Public Disclosure Authorized PROJECT APPRAISAL DOCUMENT ON A PROPOSED LOAN IN THE AMOUNT OF USS100 MILLION TO THE PEOPLE'S REPUBLIC OF CHINA Public Disclosure Authorized FORA LIAO RIVER BASIN PROJECT May 21, 2001 Urban Development Sector Unit East Asia and Pacific Region Public Disclosure Authorized CURRENCY EQUIVALENTS (Exchange R.ate Effective May 1, 2001) Currency Unit = Yuan (Y) Y 1.00 = US$0.12 USSLOO = Y8.3 FISCAL YEAR January 1 -- Decernber 31 ABBREVIATIONS AND ACRONYMS AIC Average IncrementalCost LFD LiaoningProvincial Finance Department CAS Country AssistanceStrategy LIEP Liaoning IntegratedEnvironment Program CITC China InternationalTendering I.P LiaoningProvince Company LPG LiaoningProvincial Government CNAO China National Audit Office LRB Liao River Basin COD ChemicalOxygen Demand LRBP Liao River Basin Project DRA DesignReview & Advisory LUCRPOLiaoning Urban Construction& Renewal Project (Consultancy) Office EA EnvironmentalAssessment MOC Ministryof Construction EMP EnvironmentalManagement Plan MOF Ministry of Finance EPB EnvironmentalProtection Bureau i NCB National CompetitiveBidding ERSF Environment Revolving Subloan NGO NongovernmentalOrganization Facility OED Operations EvaluationDepartment ES EnvironmentSubloans PAP Project-AffectedPersons EU EuropeanUnion PDMC Panjin MunicipalDrainage ManagementCompany FMS Financial ManagementSystem PMO Project ManagementOffice GPN GeneralProcurement Notice PRC People's Republicof China ICB InternationalCompetitive -
Harbin Information Pack Harbin, Also Known As the 'Paris of the East'
Harbin Information Pack Harbin, also known as the ‘Paris of the East’. Content Page About Harbin- History Local amenities and facilities – Health, leisure and shopping. Expat – What it is and groups. Climate and lifestyle. Cost of living. Local attractions. Tourist attractions- Harbin and other cities Public transport. About Harbin Harbin is the capital of Heilongjiang Province and located in the northeast of the northeast China Plain. Harbin is famous as a historical and cultural city and renowned for its snow and ice culture. Harbin is also well known for its large number of European-style buildings. Harbin is also known as the ice city. Through the winter Harbin displays thousands of ice sculptures and has hundreds of ice-related activities. Harbin’s History Harbin’s history isn’t as long as some cities. The city is around 110 years old and has become the biggest city in the north-eastern section of China with currently over 10 million people. Harbin was originally a fishing village until the Russians started to build a railroad into the area in1897. Local amenities and facilities Harbin has many shops and leisure facilities available. There are many different places to go shopping but the most famous shopping streets are: Zhongyang Dajie (Central street)- Full of new shopping malls such as Euro Plaza, Parksons, and Lane Crawford that carry international brands and are expensive. There are Nike stores, KFC and interesting Russian thrift stores. The streets are lined with beer gardens during the summer as Harbin is the 3rd biggest city for beer consumption. Guogeli Dajie- The area around here is dotted with Russian buildings and large shopping complexes. -
Monitoring Population Evolution in China Using Time-Series DMSP/OLS Nightlight Imagery
remote sensing Article Monitoring Population Evolution in China Using Time-Series DMSP/OLS Nightlight Imagery Sisi Yu 1,2, Zengxiang Zhang 1 and Fang Liu 1,* 1 Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China; [email protected] (S.Y.); [email protected] (Z.Z.) 2 University of Chinese Academy of Sciences, Beijing 100049, China * Correspondence: [email protected]; Tel.: +86-10-6488-9205; Fax: +86-10-6488-9203 Received: 16 November 2017; Accepted: 26 January 2018; Published: 28 January 2018 Abstract: Accurate and detailed monitoring of population distribution and evolution is of great significance in formulating a population planning strategy in China. The Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) nighttime lights time-series (NLT) image products offer a good opportunity for detecting the population distribution owing to its high correlation to human activities. However, their detection capability is greatly limited owing to a lack of in-flight calibration. At present, the synergistic use of systematically-corrected NLT products and population spatialization is rarely applied. This work proposed a methodology to improve the application precision and versatility of NLT products, explored a feasible approach to quantitatively spatialize the population to grid units of 1 km × 1 km, and revealed the spatio-temporal characteristics of population distribution from 2000 to 2010. Results indicated that, (1) after inter-calibration, geometric, incompatibility and discontinuity corrections, and adjustment based on vegetation information, the incompatibility and discontinuity of NTL products were successfully solved. Accordingly, detailed actual residential areas and luminance differences between the urban core and the peripheral regions could be obtained. -
Monitoring Spatio-Temporal Changes of Terrestrial Ecosystem Soil Water Use Efficiency in Northeast China Using Time Series Remote Sensing Data
sensors Article Monitoring Spatio-Temporal Changes of Terrestrial Ecosystem Soil Water Use Efficiency in Northeast China Using Time Series Remote Sensing Data Hang Qi, Fang Huang * and Huan Zhai School of Geographical Sciences, Northeast Normal University, Renmin Street No. 5268, Changchun 130024, China; [email protected] (H.Q.); [email protected] (H.Z.) * Correspondence: [email protected]; Tel.: +86-431-8509-9550 Received: 19 February 2019; Accepted: 21 March 2019; Published: 26 March 2019 Abstract: Soil water use efficiency (SWUE) was proposed as an effective proxy of ecosystem water use efficiency (WUE), which reflects the coupling of the carbon–water cycle and function of terrestrial ecosystems. The changes of ecosystem SWUE at the regional scale and their relationships with the environmental and biotic factors are yet to be adequately understood. Here, we aim to estimate SWUE over northeast China using time-series Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary productivity data and European Space Agency climate change initiative (ESA CCI) soil moisture product during 2007–2015. The spatio-temporal variations in SWUE and their linkages to multiple factors, especially the phenological metrics, were investigated using trend and correlation analysis. The results showed that the spatial heterogeneity of ecosystem SWUE in northeast China was obvious. SWUE distribution varied among vegetation types, soil types, and elevation. Forests might produce higher photosynthetic productivity by utilizing unit soil moisture. The seasonal variations of SWUE were consistent with the vegetation growth cycle. Changes in normalized difference vegetation index (NDVI), land surface temperature, and precipitation exerted positive effects on SWUE variations. The earlier start (SOS) and later end (EOS) of the growing season would contribute to the increase in SWUE. -
Cropland Heterogeneity Changes on the Northeast China Plain in the Last Three Decades (1980S–2010S)
Cropland heterogeneity changes on the Northeast China Plain in the last three decades (1980s–2010s) Xiaoxuan Liu1,2, Le Yu1,2,3, Qinghan Dong4, Dailiang Peng5, Wenbin Wu6, Qiangyi Yu6, Yuqi Cheng1,2, Yidi Xu1,2, Xiaomeng Huang1,2, Zheng Zhou1, Dong Wang1,7, Lei Fang8 and Peng Gong1,2 1 Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Tsinghua University, Beijing, China 2 Joint Center for Global Change Studies, Beijing, China 3 Ministry of Education Ecological Field Station for East Asian Migratory Birds, Beijing, China 4 Department of Remote Sensing Boeretang 200, Flemish Institute of Technology (VITO), Mol, Belgium 5 Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences, Key Laboratory of Digital Earth Science, Beijing, China 6 Ministry of Agriculture and Rural Affairs/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Key Laboratory of Agricultural Remote Sensing (AGRIRS), Beijing, China 7 National Supercomputing Center in Wuxi, Wuxi, China 8 Chinese Academy Sciences, CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Shenyang, China ABSTRACT The Northeast China Plain is one of the major grain-producing areas of China because of its fertile black soil and large fields adapted for agricultural machinery. It has experienced some land-use changes, such as urbanization, deforestation, and wetland reclamation in recent decades. A comprehensive understanding of these changes in terms of the total cropping land and its heterogeneity during this period is important for policymakers. In this study, we used a series of cropland products at the 30- m resolution for the period 1980–2015. -
The Causes of Soil Alkalinization in the Songnen Plain of Northeast China
Paddy Water Environ DOI 10.1007/s10333-009-0166-x REVIEW The causes of soil alkalinization in the Songnen Plain of Northeast China Li Wang Æ Katsutoshi Seki Æ T. Miyazaki Æ Y. Ishihama Received: 7 October 2008 / Revised: 29 April 2009 / Accepted: 17 May 2009 Springer-Verlag 2009 Abstract The causes of soil alkalinization in the Songnen Introduction Plain of Northeast China were mainly analyzed from two aspects, natural and anthropogenic. Natural factors of Songnen Plain covers an area of about 17.0 9 106 ha in the alkalinization are parent materials, topographic positions, central part of northeastern China (43 300–48 400N; freeze-thaw action, wind conveyance, water properties and 121 300–127 000E), and is a big basin that is surrounded by semi-arid/sub-humid climate. Some of them were always Changbai Mountain (east), Xiaoxing’an Mountain Ranges being neglected, such as freeze-thaw action and wind (north) and Daxing’an Mountain Ranges (west). Its south conveyance. Anthropogenic causes are mainly population border is Liao River Plain. Songhua River and Nen River pressure, overgrazing and improper agricultural and eco- are streaming through the central part of the region nomic policies. In recent decades, overgrazing played a (Fig. 1). Also, there are many branch rivers originated from main role in secondary soil alkalinization, which led to the surrounding mountains. Inside the region, many closed- decline of Leymus chinensis grasslands. Now, the alkalin- flow areas and ephemeral rivers are distributed, which ization is very severe, and more than 3.2 9 106 ha area has caused a lot of wetlands. -
Observed Vegetation Greening and Its Relationships with Cropland Changes and Climate in China
land Article Observed Vegetation Greening and Its Relationships with Cropland Changes and Climate in China Yuzhen Zhang 1,* , Shunlin Liang 2 and Zhiqiang Xiao 3 1 Beijing Engineering Research Center of Industrial Spectrum Imaging, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China 2 Department of Geographical Sciences, University of Maryland, College Park, MD 20740, USA; [email protected] 3 State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; [email protected] * Correspondence: [email protected] Received: 25 July 2020; Accepted: 14 August 2020; Published: 16 August 2020 Abstract: Chinese croplands have changed considerably over the past decades, but their impacts on the environment remain underexplored. Meanwhile, understanding the contributions of human activities to vegetation greenness has been attracting more attention but still needs to be improved. To address both issues, this study explored vegetation greening and its relationships with Chinese cropland changes and climate. Greenness trends were first identified from the normalized difference vegetation index and leaf area index from 1982–2015 using three trend detection algorithms. Boosted regression trees were then performed to explore underlying relationships between vegetation greening and cropland and climate predictors. The results showed the widespread greening in Chinese croplands but large discrepancies in greenness trends characterized by different metrics. Annual greenness trends in most Chinese croplands were more likely nonlinearly associated with climate compared with cropland changes, while cropland percentage only predominantly contributed to vegetation greening in the Sichuan Basin and its surrounding regions with leaf area index data and, in the Northeast China Plain, with vegetation index data. -
World Bank Document
.M * 7 1/b.2 - & Document of The World Bank FOR OFFICIAL USE ONLY Public Disclosure Authorized Pi,,por t No. :11 147- Ct-hA Type: (SAfR) - I t I- AGRICULTURfAL SUPPf10 Sf-RVIE t-'j I ReportNo. 11147C& Aiuthor: 12LI. U-"'lCARATNAM STAFF APPRAISAL REPORT CHNA Public Disclosure Authorized AGRICULTURALSUPPORT SERVICES PROJECT JANUARY22, 1993 Public Disclosure Authorized Agriculture Operations Division Public Disclosure Authorized Country Department II East Asia and Pacific Regional Office This documenthas a restdded distibution and may be used by recipiens ony in the perfonranc of tbeir official duties. Its contents may not otewise be disclosed whout World Bank authorization. CURRENCY EQUIVALENTS (As of June 1992) Currency Unit Yuan (Y) $1.00 = Y 5.45 Y 1.00 = $0.183 FISCAL YEAR January 1 - December31 WEIGHTS AND MEASURES 1 meter (m) = 3.28 feet (ft) 1 kilometer(ICm) = 0.62 miles 1 hectare (ha) = 15 mu 1 ton (t) = 1,000 kg = 2,205 pounds 1 kilogram (kg) = 2.2 pounds - 2jin ACRONYMSAND ABBREVIATIONS ATEC AgrotechnicalExtension Center BAU Beijing AgriculturalUniversity CAAS Chinese Academy of AgriculturalSciences CABTS China AgriculturalBroadcasting and TelevisionSchool CAS Chinese Academyof Sciences CATEC County Agro-TechnicalExtension Center CNCQSTF China NationalCenter for QualitySupervision and Test of Feed CNBTS China NationalBureau for TechnicalSupervision CNSC China NationalSeed Corporation DAH Departmentof AnimalHusbandry DEER Departmentof ExternalEconomic Relations DOA Departmentof Agriculture LAE Institute of AgriculturalEconomics