Use the Ncov2019 R Package to Obtain Latest and Historical Data on the Coronavirus Outbreak

Total Page:16

File Type:pdf, Size:1020Kb

Use the Ncov2019 R Package to Obtain Latest and Historical Data on the Coronavirus Outbreak Supplementary document #1: Use the nCov2019 R package to obtain latest and historical data on the coronavirus outbreak Tianzhi Wu1, Xijin Ge2,*, Guangchuang Yu1,* 1Department of Bioinformatics, School of Basic Medical Science, Southern Medical University, Guangzhou, China 2Department of Mathematics and Statistics, South Dakota State University, Brookings, SD 57007, USA. Corresponding: Guangchuang Yu ([email protected]); Xijin Ge ([email protected]) Part I— Quickstart You can easily install the package by running the following in R: Install.packages("remotes") remotes::install_github("GuangchuangYu/nCov2019") The geographical name is Chinese by default, and users can use the argument lang = 'en' as in this example to set the name in English. To get the latest data, you can load it in with get_nCov2019(); print the object x, it will show the total number of confirmed cases in China: library('nCov2019') x <- get_nCov2019(lang='en') x ## China (total confirmed cases): 77269 ## last update: 2020-02-24 23:58:45 Note: if you would like to use the Chinese version, you can remove the lang='en' argument. To look at the global data, you can run the code x['global', ]: head(x['global', ]) ## name confirm suspect dead deadRate showRate heal healRate ## 1 China 77269 3434 2596 3.36 FALSE 24854 32.17 ## 2 Republic of Korea 833 0 8 0.96 FALSE 12 1.44 ## 3 Diamond Princess 691 0 3 0.43 FALSE 0 0.00 ## 4 Italy 230 0 6 2.61 FALSE 2 0.87 ## 5 Janpan 159 0 1 0.63 FALSE 1 0.63 ## 6 Singapore 90 0 0 0.00 FALSE 53 58.89 1 ## showHeal ## 1 TRUE ## 2 TRUE ## 3 TRUE ## 4 TRUE ## 5 TRUE ## 6 TRUE And view provincial data within China easily with x[]. head(x[]) ## name confirm suspect dead deadRate showRate heal healRate showHeal ## 1 Hubei 64287 0 2495 3.88 FALSE 16738 26.04 TRUE ## 2 Guangdong 1345 0 6 0.45 FALSE 772 57.40 TRUE ## 3 Henan 1271 0 19 1.49 FALSE 930 73.17 TRUE ## 4 Zhejiang 1205 0 1 0.08 FALSE 765 63.49 TRUE ## 5 Hunan 1016 0 4 0.39 FALSE 721 70.96 TRUE ## 6 Anhui 989 0 6 0.61 FALSE 692 69.97 TRUE Or get the data of specific province head(x['Hubei', ]) # you can replace Hubei with any province ## name confirm suspect dead deadRate showRate heal healRate showHeal ## 1 Wuhan 46607 0 1987 4.26 FALSE 8946 19.19 TRUE ## 2 Xiaogan 3465 0 108 3.12 FALSE 1177 33.97 TRUE ## 3 Huanggang 2904 0 103 3.55 FALSE 1659 57.13 TRUE ## 4 Jingzhou 1574 0 42 2.67 FALSE 734 46.63 TRUE ## 5 Ezhou 1383 0 40 2.89 FALSE 465 33.62 TRUE ## 6 Suizhou 1303 0 33 2.53 FALSE 551 42.29 TRUE Use the argument by='today' to view the number of newly added cases head(x['Hubei', by='today'][,c(1,2,4)]) ## name confirm isUpdated ## 1 Wuhan 0 FALSE ## 2 Xiaogan 0 FALSE ## 3 Huanggang 0 FALSE ## 4 Jingzhou 0 FALSE ## 5 Ezhou 0 FALSE ## 6 Suizhou 0 FALSE # And the below command is the same head(x['Hubei', by='today'][,c(1,2,4)]) ## name confirm isUpdated ## 1 Wuhan 0 FALSE ## 2 Xiaogan 0 FALSE ## 3 Huanggang 0 FALSE ## 4 Jingzhou 0 FALSE 2 ## 5 Ezhou 0 FALSE ## 6 Suizhou 0 FALSE Another method to extract information is the summary function. It outputs daily statistics of cumulative (default) or newly (using the parameter by = "today") cases in China. Such information is useful to draw a daily growth curve. See supplementary document 1 for more detailed tutorial. The daily data output by summary function is only available for the whole country of China. Getting daily data of each province and city is described in the following session. To get a cumulative summary of the daily data, you could use the summary function on x . head(summary(x)) ## confirm suspect dead heal nowConfirm nowSevere deadRate healRate date ## 1 41 0 1 0 0 0 2.4 0.0 01.13 ## 2 41 0 1 0 0 0 2.4 0.0 01.14 ## 3 41 0 2 5 0 0 4.9 12.2 01.15 ## 4 45 0 2 8 0 0 4.4 17.8 01.16 ## 5 62 0 2 12 0 0 3.2 19.4 01.17 ## 6 198 0 3 17 0 0 1.5 8.6 01.18 Similarly, if you wanted to view the new daily cases, you could use the by="today" argument: head(summary(x, by="today")) ## confirm suspect dead heal deadRate healRate date ## 1 77 27 0 0 0.0 0.0 01.20 ## 2 149 53 3 0 2.0 0.0 01.21 ## 3 131 257 8 0 6.1 0.0 01.22 ## 4 259 680 8 6 3.1 2.3 01.23 ## 5 444 1118 16 3 3.6 0.7 01.24 ## 6 688 1309 15 11 2.2 1.6 01.25 Here is A quick visulization example for Anhui province in China. library(forcats) library(ggplot2) d = x['Anhui',] # you can replace Anhui with any province d$confirm=as.numeric(d$confirm) d$name = fct_reorder(d$name, d$confirm) ggplot(d, aes(name, confirm)) + geom_col(fill='steelblue') + coord_flip() + geom_text(aes(y = confirm+2, label=confirm), hjust=0) + theme_minimal(base_size=14) + scale_y_continuous(expand=c(0,10)) + xlab(NULL) + ylab(NULL) 3 If you wanted to visualize the cumulative summary data, an example plot could be the following: ggplot(summary(x), aes(as.Date(date, "%m.%d"), as.numeric(confirm))) + geom_col(fill='firebrick') + theme_minimal(base_size = 14) + xlab(NULL) + ylab(NULL) + labs(caption = paste("accessed date:", time(x))) Part II — Historical Data You can use load_nCov2019() to access detailed historical data. x <- load_nCov2019(lang='en') head(x[]) ## time province city cum_confirm cum_heal cum_dead ## 1 2020-01-25 Guangxi Wuzhou 1 0 0 ## 2 2020-01-25 Hubei Enshi 11 0 0 4 ## 3 2020-01-25 Guangdong Shaoguan 3 0 0 ## 4 2020-01-25 Chongqing Hechuan District 2 0 0 ## 5 2020-01-25 Chongqing Bishan District 2 0 0 ## 6 2020-01-25 Chongqing Fuling District 1 0 0 ## suspected ## 1 0 ## 2 0 ## 3 0 ## 4 0 ## 5 0 ## 6 0 Similar to get_nCov2019(), you are also able to call the summary() function on the data. head(summary(x)) ## time province cum_confirm ## 1 2020-01-25 Guangxi 23 ## 2 2020-01-25 Hubei 761 ## 3 2020-01-25 Guangdong 78 ## 4 2020-01-25 Chongqing 57 ## 12 2020-01-25 Hunan 43 ## 33 2020-01-25 Zhejiang 62 And you can get historical provincial & City Details in China: head(x['Hubei']) ## time province city cum_confirm cum_heal cum_dead suspected ## 2 2020-01-25 Hubei Enshi 11 0 0 0 ## 107 2020-01-25 Hubei Jingzhou 10 0 0 0 ## 109 2020-01-25 Hubei Suizhou 5 0 0 0 ## 167 2020-01-25 Hubei Wuhan 572 32 38 0 ## 168 2020-01-25 Hubei Huanggang 64 0 0 0 ## 169 2020-01-25 Hubei Huangshi 31 0 1 0 You can then use this data for visualizations: library(ggplot2) ggplot(summary(x, 'Hubei'), aes(time, as.numeric(cum_confirm))) + geom_col() 5 library(ggrepel) d <- x['Hubei'] ggplot(d, aes(time, as.numeric(cum_confirm), group=city, color=city)) + geom_point() + geom_line() + geom_text_repel(aes(label=city), data=d[d$time == time(x), ], hjust=1 ) + theme_minimal(base_size = 14) + theme(legend.position='none') + xlab(NULL) + ylab(NULL) ## Warning: Removed 1 rows containing missing values (geom_text_repel). 6 ggplot(subset(x['Hubei'], city='Huanggan'), aes(time, as.numeric(cum_co nfirm))) + geom_col() Part III— Map Plotting We provide several parameters to adjust the final effect of the map, including font.size to adjust label size, continuous_scale = FALSE to a discrete color scale (continuous color scale at log space was used by default), and palette to adjust the color palette (e.g., palette='blue' for setting color from dark blue to light blue). Getting a plot of the world map is really simple. There are only three lines needed: require(nCov2019) x = get_nCov2019(lang='en') plot(x) 7 And with more detailed in China region: remotes::install_github("GuangchuangYu/chinamap") require(chinamap) cn = get_map_china() cn$province <- trans_province(cn$province) plot(x, chinamap=cn, palette="Purples") Note: The provinces must be translated by using trans_province() while in English version. To get a closer look at what the situation is in China, add a region = 'china' argument to the plot x <- get_nCov2019(lang='en') cn = get_map_china() cn$province <- trans_province(cn$province) plot(x, region='china', chinamap=cn, continuous_scale=FALSE, palette='Blues', font.size = 2) 8 To get a map for a specific province in in China x = get_nCov2019(lang='en') m = sf::st_read("PATH/TO/GIS file.shp") plot(x, region='Hubei', chinamap=m) In addition, you can draw historical maps on specific date 9 y <- load_nCov2019(lang = 'en') cn = get_map_china() cn$province <- trans_province(cn$province) plot(y, region='china', chinamap=cn, date='2020-02-01', font.size=2) 10 .
Recommended publications
  • Landscape Analysis of Geographical Names in Hubei Province, China
    Entropy 2014, 16, 6313-6337; doi:10.3390/e16126313 OPEN ACCESS entropy ISSN 1099-4300 www.mdpi.com/journal/entropy Article Landscape Analysis of Geographical Names in Hubei Province, China Xixi Chen 1, Tao Hu 1, Fu Ren 1,2,*, Deng Chen 1, Lan Li 1 and Nan Gao 1 1 School of Resource and Environment Science, Wuhan University, Luoyu Road 129, Wuhan 430079, China; E-Mails: [email protected] (X.C.); [email protected] (T.H.); [email protected] (D.C.); [email protected] (L.L.); [email protected] (N.G.) 2 Key Laboratory of Geographical Information System, Ministry of Education, Wuhan University, Luoyu Road 129, Wuhan 430079, China * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel: +86-27-87664557; Fax: +86-27-68778893. External Editor: Hwa-Lung Yu Received: 20 July 2014; in revised form: 31 October 2014 / Accepted: 26 November 2014 / Published: 1 December 2014 Abstract: Hubei Province is the hub of communications in central China, which directly determines its strategic position in the country’s development. Additionally, Hubei Province is well-known for its diverse landforms, including mountains, hills, mounds and plains. This area is called “The Province of Thousand Lakes” due to the abundance of water resources. Geographical names are exclusive names given to physical or anthropogenic geographic entities at specific spatial locations and are important signs by which humans understand natural and human activities. In this study, geographic information systems (GIS) technology is adopted to establish a geodatabase of geographical names with particular characteristics in Hubei Province and extract certain geomorphologic and environmental factors.
    [Show full text]
  • Download Article
    Advances in Economics, Business and Management Research, volume 70 International Conference on Economy, Management and Entrepreneurship(ICOEME 2018) Research on the Path of Deep Fusion and Integration Development of Wuhan and Ezhou Lijiang Zhao Chengxiu Teng School of Public Administration School of Public Administration Zhongnan University of Economics and Law Zhongnan University of Economics and Law Wuhan, China 430073 Wuhan, China 430073 Abstract—The integration development of Wuhan and urban integration of Wuhan and Hubei, rely on and Ezhou is a strategic task in Hubei Province. It is of great undertake Wuhan. Ezhou City takes the initiative to revise significance to enhance the primacy of provincial capital, form the overall urban and rural plan. Ezhou’s transportation a new pattern of productivity allocation, drive the development infrastructure is connected to the traffic artery of Wuhan in of provincial economy and upgrade the competitiveness of an all-around and three-dimensional way. At present, there provincial-level administrative regions. This paper discusses are 3 interconnected expressways including Shanghai- the path of deep integration development of Wuhan and Ezhou Chengdu expressway, Wuhan-Ezhou expressway and from the aspects of history, geography, politics and economy, Wugang expressway. In terms of market access, Wuhan East and puts forward some suggestions on relevant management Lake Development Zone and Ezhou Gedian Development principles and policies. Zone try out market access cooperation, and enterprises Keywords—urban regional cooperation; integration registered in Ezhou can be named with “Wuhan”. development; path III. THE SPACE FOR IMPROVEMENT IN THE INTEGRATION I. INTRODUCTION DEVELOPMENT OF WUHAN AND EZHOU Exploring the path of leapfrog development in inland The degree of integration development of Wuhan and areas is a common issue for the vast areas (that is to say, 500 Ezhou is lower than that of central urban area of Wuhan, and kilometers from the coastline) of China’s hinterland.
    [Show full text]
  • Chongqing Urban–Rural Infrastructure Development Demonstration II Project — Resettlement External Monitoring Report (No
    Resettlement External Monitoring Report #7 June–December 2018 January 2019 People’s Republic of China: Chongqing Urban–Rural Infrastructure Development Demonstration II Project — Resettlement External Monitoring Report (No. 7) Prepared by the Halcrow (Chongqing) Engineering Consulting Co. Ltd. for the People’s Republic of China and the Asian Development Bank. This resettlement external monitoring report is a document of the borrower. The views expressed herein do not necessarily represent those of ADB's Board of Directors, Management, or staff, and may be preliminary in nature. In preparing any country program or strategy, financing any project, or by making any designation of or reference to a particular territory or geographic area in this document, the Asian Development Bank does not intend to make any judgments as to the legal or other status of any territory or area. ADB-Financed Chongqing Urban–Rural Infrastructure Development Demonstration Project II Resettlement External Monitoring Report (No. 7) (Jun 2018---Dec 2018) Halcrow (Chongqing) Engineering Consulting Co. Ltd. Jan 2019 I Contents Contents ................................................................................................................................................. II 1. Introduction ........................................................................................................................................ 1 1.1 Brief Introduction of the Project ..................................................................................................................
    [Show full text]
  • A Simple Model to Assess Wuhan Lock-Down Effect and Region Efforts
    A simple model to assess Wuhan lock-down effect and region efforts during COVID-19 epidemic in China Mainland Zheming Yuan#, Yi Xiao#, Zhijun Dai, Jianjun Huang & Yuan Chen* Hunan Engineering & Technology Research Centre for Agricultural Big Data Analysis & Decision-making, Hunan Agricultural University, Changsha, Hunan, 410128, China. #These authors contributed equally to this work. * Correspondence and requests for materials should be addressed to Y.C. (email: [email protected]) (Submitted: 29 February 2020 – Published online: 2 March 2020) DISCLAIMER This paper was submitted to the Bulletin of the World Health Organization and was posted to the COVID-19 open site, according to the protocol for public health emergencies for international concern as described in Vasee Moorthy et al. (http://dx.doi.org/10.2471/BLT.20.251561). The information herein is available for unrestricted use, distribution and reproduction in any medium, provided that the original work is properly cited as indicated by the Creative Commons Attribution 3.0 Intergovernmental Organizations licence (CC BY IGO 3.0). RECOMMENDED CITATION Yuan Z, Xiao Y, Dai Z, Huang J & Chen Y. A simple model to assess Wuhan lock-down effect and region efforts during COVID-19 epidemic in China Mainland [Preprint]. Bull World Health Organ. E-pub: 02 March 2020. doi: http://dx.doi.org/10.2471/BLT.20.254045 Abstract: Since COVID-19 emerged in early December, 2019 in Wuhan and swept across China Mainland, a series of large-scale public health interventions, especially Wuhan lock-down combined with nationwide traffic restrictions and Stay At Home Movement, have been taken by the government to control the epidemic.
    [Show full text]
  • EMR: PRC: Wuhan Wastewater And
    Environmental Monitoring Report Project Number: 39228 January 2010 PRC: Wuhan Wastewater and Stormwater Management Project Prepared by H&J, Inc. USA. & Wuhan Hongshan District Environmental Monitoring Station Hubei Province, PRC This report has been submitted to ADB by the Wuhan Municipal Government Project Management Office and is made publicly available in accordance with ADB’s public communications policy (2005). It does not necessarily reflect the views of ADB. ADB FINANCED WUHAN WASTEWATER AND STORM WATER MANAGEMENT PROJECT Loan No. 2240-PRC ENVIRONMENTAL MONITORING REPORT No.3 To be submitted to Asian Development Bank & Wuhan Urban Construction Utilization of Foreign Investment Project Management Office H&J, Inc. USA. & Wuhan Hongshan District Environmental Monitoring Station January 2010 Environmental Monitoring Report(2009-03) ADB WWSMP CONTENTS 1. BACKGROUND OF PROJECT ................................................................................................1 2. OBJECTIVE OF MONITORING..............................................................................................6 3. IMPLEMENTATION STATUS FOR ENVIRONMENTAL MITIGATION MEASURES DURING CONSTRUCTION.....................................................................................................7 4. ENVIRONMENT PROTECTION TARGETS .......................................................................12 5. MONITORING DURING CONSTRUCTION........................................................................13 6. CONCLUSION AND RECOMMENDATION........................................................................20
    [Show full text]
  • Jingzhou Tao
    Curriculum Vitae of Jingzhou Tao Floor 28th, South Tower, Beijing Kerry Centre 1 Guanghua Road, Chaoyang District Beijing 100020, PRC D: (86-10) 5829 1303 F: (86-10) 5829 1313 M: 86 1380-120-8873 E: [email protected] Jingzhou Tao is the Managing Partner at Dechert LLP responsible for developing the firm’s Asian practice. He has more than 30 years of experience advising Fortune 500 companies on China-related matters. He has acted as counsel, chief arbitrator or party-nominated arbitrator in over one hundred international arbitration proceedings. International arbitration related positions currently held by Jingzhou include: . Member of the Court, ICC International Court of Arbitration; . Member of the Advisory Committee of China International Economic and Trade Arbitration Commission; . Member of the International Advisory Board of China International Economic and Trade Arbitration Commission; . Member of the Board of Trustee of Foundation International for Arbitration Advocacy; . Member of the Board of Global Arbitration Review; . Fellow of the Chartered Institute of Arbitrators. He is a listed arbitrator for: . the Court of Arbitration for Sport; . the American Arbitration Association; . the Hong Kong International Arbitration Centre; . the Singapore International Arbitration Centre; . the Vienna International Arbitral Centre; . the Kuala Lumpur Regional Centre for Arbitration; . the China International Economic and Trade Arbitration Commission; . the Shanghai International Economic and Trade Arbitration Commission; and . the Beijing Arbitration Commission. Mr. Tao is a frequent speaker among the legal world and has also published many articles in Chinese and international legal and business publications. He is also an adjunct professor at Peking University Law School, East China University of Political Science and Law, China University of Political Science and Law for the MBA program, and a specially-invited professor of law for the International Arbitration Program at Tsinghua University School of Law.
    [Show full text]
  • Verification of Wind Field Retrieval of Doppler Radar Velocity-Azimuth
    5.8 VERIFICATION OF WIND FIELD RETRIEVAL OF DOPPLER RADAR VELOCITY-AZIMUTH PROCESSING METHOD Zheng Yongguang1 Liu Shuyuan1 Bai Jie2 Tao Zuyu1 (1 Department of Atmospheric Sciences, School of Physics, Peking University, Beijing 100871, P. R. China; 2 Beijing Aviation Meteorological Institute, Beijing 100085, P. R. China) 1 PRINCIPLE OF VAP METHOD direction and the radar beam. The VAP (Velocity-Azimuth Processing) method was put forward for retrieving the horizontal wind field from single Doppler radar data by Tao Zuyu (1992). Assume that the horizontal wind vectors are uniform in L a very small azimuth interval (i. e., the local uniformity of wind field) and neglect the vertical fall speed of the r L’ particles of low elevation scan, the formula of horizontal wind retrieval based on the distribution of Doppler velocity profiles with azimuth are as follows Figure 1 A schematic diagram of the relation (see Fig. 1): between the wind vectors and the radial velocities on Wind speed: local uniform wind assumption. v − v v = hr1 hr 2 , 2sinα sin ∆θ Because spatial and temporal resolutions of the Wind direction: Doppler radar data are higher than all of other winds v − v observations, it is difficult to obtain the detail tanα = − hr1 hr 2 cot ∆θ = an vhr1 + vhr 2 information of wind field for objectively evaluating the results derived by VAP method. To prove the validity of α = arctan an, vhr1 − vhr 2 > 0,vhr1 + vhr 2 > 0 the meso-β-scale characteristics on the retrieved wind α = arctan an +π , vhr1 − vhr 2 > 0,vhr1 + vhr 2 < 0 fields by VAP method, Choi et.
    [Show full text]
  • Geographical Overview of the Three Gorges Dam and Reservoir, China—Geologic Hazards and Environmental Impacts
    Geographical Overview of the Three Gorges Dam and Reservoir, China—Geologic Hazards and Environmental Impacts Open-File Report 2008–1241 U.S. Department of the Interior U.S. Geological Survey Geographical Overview of the Three Gorges Dam and Reservoir, China— Geologic Hazards and Environmental Impacts By Lynn M. Highland Open-File Report 2008–1241 U.S. Department of the Interior U.S. Geological Survey U.S. Department of the Interior DIRK KEMPTHORNE, Secretary U.S. Geological Survey Mark D. Myers, Director U.S. Geological Survey, Reston, Virginia: 2008 For product and ordering information: World Wide Web: http://www.usgs.gov/pubprod Telephone: 1-888-ASK-USGS For more information on the USGS—the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment: World Wide Web: http://www.usgs.gov Telephone: 1-888-ASK-USGS Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Although this report is in the public domain, permission must be secured from the individual copyright owners to reproduce any copyrighted materials contained within this report. Suggested citation: Highland, L.M., 2008, Geographical overview of the Three Gorges dam and reservoir, China—Geologic hazards and environmental impacts: U.S. Geological Survey Open-File Report 2008–1241, 79 p. http://pubs.usgs.gov/of/2008/1241/ iii Contents Slide 1...............................................................................................................................................................1
    [Show full text]
  • Sanctuary Yangzi Explorer2.03Mb
    SANCTUARY YANGZI EXPLORER CHINA Experience the mighty, mysterious Yangtze River with Sanctuary Retreats LUXURY, NATURALLY Awe-inspiring natural beauty, iconic World Heritage sites and cultures enhanced over centuries – these are the riches around as you sail China’s legendary waterway. The guiding philosophy of all Sanctuary cruises and safari lodges is ‘Luxury, naturally’, and Sanctuary Yangzi Explorer gets you as close as possible to central China’s most captivating landscapes amid authentic charm and unrivalled comfort. This unique cruise steers you to dramatic destinations old and new, and gives glimpses of remote riverside life while you take pleasure in a relaxing journey with unrivalled amenities. Explore the largest man-made cave in the world, admire forest-cloaked peaks and feel personally introduced to time-tested traditions thanks to time on Sanctuary Yangzi Explorer – it’s a boutique hotel with five-star service floating on the Golden River. The carefully curated itineraries combine fascinating history-steeped cities with soul-uplifting rural stories along Asia’s longest river. The port of Chongqing, a Municipality located in the Sichuan Province - is the gateway to the 3,915-mile Yangtze. Meander through the Three Gorges, which extend 120 miles into the river’s middle reaches; discover the mountains of the Fuling district; take a whirl on a wooden sampan along the Shennong Stream as Tujia boatmen spill local secrets. Learn about each beguiling destination from small-group excursions and English-speaking experts. And wake
    [Show full text]
  • Social Monitoring Report PRC: Chongqing-Lichuan Railway
    Social Monitoring Report Project Number: 39153 March 2010 PRC: Chongqing-Lichuan Railway Development – Resettlement Action Plan Monitoring Report No. 1 Prepared by: CIECC Overseas Consulting Co., Ltd Beijing, PRC For: Ministry of Railways Chongqing Lichuang Railway Joint Venture Company This report has been submitted to ADB by the Ministry of Railways and is made publicly available in accordance with ADB’s public communications policy (2005). It does not necessarily reflect the views of ADB. ADB LOAN EXTERNAL Monitoring Report– No. 1 TABLE OF CONTENTS SUMMARY.........................................................................................................................................................................4 1. PROJECT OVERVIEW .....................................................................................................................................................6 2. PROGRESS OF PROJECT CONSTRUCTION AND RESETTLEMENT ............................................................................................7 2.1. PROGRESS OF PROJECT ENGINEERING CONSTRUCTION................................................................................................7 2.2. PROGRESS OF LAND ACQUISITION, BUILDING DEMOLITION AND RESETTLEMENT.............................................................10 3. MONITORING AND EVALUATION WORK ........................................................................................................................15 4. WORKING SITUATION OF RESETTLEMENT AGENCY...........................................................................................................16
    [Show full text]
  • CHN33885 – Three Gorges Dam – Protests – Bilharzia
    Refugee Review Tribunal AUSTRALIA RRT RESEARCH RESPONSE Research Response Number: CHN33885 Country: China Date: 16 October 2008 Keywords: China – CHN33885 – Three Gorges Dam – Protests – Bilharzia This response was prepared by the Research & Information Services Section of the Refugee Review Tribunal (RRT) after researching publicly accessible information currently available to the RRT within time constraints. This response is not, and does not purport to be, conclusive as to the merit of any particular claim to refugee status or asylum. This research response may not, under any circumstance, be cited in a decision or any other document. Anyone wishing to use this information may only cite the primary source material contained herein. Questions 1.What is the measurement “mu”? 2. Information about the Three Gorges Dam, and forced acquisition of land, including compensation payable to displaced migrants. 3. Information about the worm parasite – Bilharzia. 4. Information about Hong Yunzhou, Tan Guotai, Chen Yichun, Zhou Zhirong and Fu Xiancai. 5. Is there any record of protests re the displaced migrants? RESPONSE 1.What is the measurement “mu”? A mu is a land measure equal to 0.067 hectares. Thus 100,000 mu is 6,700 hectares (‘China quintuples arable land use tax’ 2006, China Daily, 6 December http://www.chinadaily.com.cn/china/2007-12/06/content_6303895.htm – Accessed 16 April 2008 – Attachment 1). 2. Information about the Three Gorges Dam, and forced acquisition of land, including compensation payable to displaced migrants. The Three Gorges Dam, located in Hubei Province, is the world’s largest dam and will be fully operational in 2009.
    [Show full text]
  • Research on Sustainable Land Use Based on Production–Living–Ecological Function: a Case Study of Hubei Province, China
    sustainability Article Research on Sustainable Land Use Based on Production–Living–Ecological Function: A Case Study of Hubei Province, China Chao Wei 1, Qiaowen Lin 2, Li Yu 3,* , Hongwei Zhang 3 , Sheng Ye 3 and Di Zhang 3 1 School of Public Administration, Hubei University, Wuhan 430062, China; [email protected] 2 School of Management and Economics, China University of Geosciences, Wuhan 430074, China; [email protected] 3 School of Public Administration, China University of Geosciences, Wuhan 430074, China; [email protected] (H.Z.); [email protected] (S.Y.); [email protected] (D.Z.) * Correspondence: [email protected]; Tel.: +86-185-7163-2717 Abstract: After decades of rapid development, there exists insufficient and contradictory land use in the world, and social, economic and ecological sustainable development is facing severe challenges. Balanced land use functions (LUFs) can promote sustainable land use and reduces land pressures from limited land resources. In this study, we propose a new conceptual index system using the entropy weight method, regional center of gravity theory, coupling coordination degree model and obstacle factor identification model for LUFs assessment and spatial-temporal analysis. This framework was applied to 17 cities in central China’s Hubei Province using 39 indicators in terms of production–living–ecology analysis during 1996–2016. The result shows that (1) LUFs showed an overall upward trend during the study period, while the way of promotion varied with different dimensions. Production function (PF) experienced a continuous enhancement during the study period. Living function (LF) was similar in this aspect, but showed a faster rising tendency.
    [Show full text]