iv v CONTENTS ................................ ................................ ................................ ................... ................................ ................................ .................. ................................ .............................. ................................ ................................ .......................... ................................ ....................... ................................ ............... ................................ ................................ .................... ................................ ................................ ................... ...................... ................................ ...................... ................................ ................................ ................ ................................ ................................ ................................ ....... ................................ ................. .... ................................ ................................ ................. vi ........................ ....... ................................ .......... ................................ . ................................ ................................ ................................ ................................ ................. ................................ ................................ ............................... .......... ................................ ................................ . vii ................................ ............................ ............... ................................ ................... ..... ................................ ................................ ................................ ................................ ................. ................................ ................................ ................................ ................................ . .................... ................................ ................................ ................................ ................................ ................. .......... ................................ ............................ ................................ ................... ................................ ................................ ... ................................ ................................ ................................ .......... ................................ ................................ ................................ ...... ................................ .............................. ................................ ................................ ...................... ................................ ................................ ................................ ..................... 1 CHAPTER 1 : INTRODUCTION Land Use and Cover Change. International Project Office & International Human Dimensions Programme on Environmental Change, 1999 2 3 4 5 6 7 8 CHAPTER 2 : STUDY AREA AND DATA 9 10 11 2.2.1 Remote sensing images and processing 12 2.2.2 S ocio - economic data 13 the 14 CHAPTER 3 : METHODOLOGY 15 16 3.3.1 L ogistic regression m odel 17 18 3.3.2 Dependent and explanatory variables of l ogistic regression model 19 20 21 22 23 24 CHAPTER 4 : RESULTS AND D ISCUSSION 25 26 Land Cover Type Grassland Built - Up Water Cropland Forest Bare Land Glacial/Snow Number of Samples Year o f 2001 Overall Accuracy 96.19% Kappa Coefficient Land Cover Type Grassland Built - Up Water Cropland Forest Bare Land Glacial/Snow Number of Samples Year o f 2005 Overall Accuracy 94.99% Kappa Coefficient Land Cover Type Grassland Built - Up Water Cropland Forest Bare Land Glacial/Snow Number of Samples Year o f 2009 Overall Accuracy 95.61% Kappa Coefficient Land Cover Type Grassland Built - Up Water Cropland Forest Bare Land Glacial/Snow Number of Samples Year o f 2013 Overall Accuracy 95.55% Kappa Coefficient Land Cover Type Grassland Built - Up Water Cropland Forest Bare Land Glacial/Snow Number of samples Year of 2017 Overall accuracy Kappa coefficient 27 28 29 Parameter 2001 - 2005 2005 - 2009 2009 - 2013 2013 - 2017 Year 2001 Grassland Built - up Water body Cropland Forest Bare Land Glacial/Snow 2017 Grassland Built - up Water body Cropland Forest Bare land Glacial/Snow 30 31 0 50 100 150 200 250 0 200 400 600 800 1000 1200 2001 2005 2009 2013 2017 Area(km2 for Water) Area(km2 for Built - up) Year Variation in area of urban regions and water bodies in Zhangye City from 2001 - 2017 Built-up Water 32 1500 2000 2500 3000 3500 4000 2001 2005 2009 2013 2017 6000 7000 8000 9000 10000 11000 12000 13000 14000 15000 16000 Area(km2 for Cropland) Year Area/km2 for Green Area) Variation of Cropland and Green areas (Grassland and Forest) in Zhangye City from 2001 - 2017 Green Cropland 33 34 35 36 37 38 39 0 50 100 150 200 250 300 350 400 450 20 20.5 21 21.5 22 22.5 23 23.5 24 24.5 25 2001 2005 2009 2013 2017 100 million RMB 100 million Ton Year Variation of the GDP, and water resources in Zhangye from 2001 to 2017 water usage/ 100 million ton GDP/ 100 million RMB 40 0 50 100 150 200 250 300 350 400 450 2001 2005 2009 2013 2017 10 million RMB Year Zhangye's different source of income and GDP from 2001 to 2017 GDP Agricultural production Tourist income Industrial added value above designated size 41 42 43 Bureau of Statistics of Zhangye, 2002,2012 ; 0 20 40 60 80 100 120 140 2001 2005 2009 2013 2017 1000 Person Year Zhangye's Population and people who holds high school diploma from 2001 - 2017 Population People with high school diploma 44 0 2 4 6 8 10 12 2001 2005 2009 2013 2017 100,000 Person Year Zhangye's Resident Hukou Change During 2001 - 2017 City resident Non-city Resident 45 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 City resident Non-city Resident City resident Non-city Resident City resident Non-city Resident City resident Non-city Resident City resident Non-city Resident 2001 2005 2009 2013 2017 100,000 Person Year Zhangye's Resident Change in Different Counties Ganzhou Shandan Gaotai Linze Minle Sunan 46 0 5000 10000 15000 20000 25000 2001 2005 2009 2013 2017 Per Capita Disposable (RMB) Year Per Capita Disposable in Zhangye City city residents non-city residents 47 48 Name 2001 - 2017 2001 - 2009 2009 - 2017 Constant parkD waterD GoverD roadD railD RailSD BusSD UrbanD AvailD IGDP IITV IAG Plan 1.100 0.060 18.195 0 0 49 50 51 52 CHAPTER 5 : CONCLUSION S 53 54 55 56 57 BIBLIOGRAPHY 58 BIBLIOGRAPHY Belgiu, M., & Csillik, O. (2018). Sentinel - 2 cropland mapping using pixel - based and object - based time - weighted dynamic time warping analysis. Remote Sensing of Environment, 204, 509 - 523. doi:10.1016/j.rse.2017.10.005 Braimoh, A. K., & Onishi, T. (2007). Spatial determinants of urban land use change in Lagos, Nigeria. Land Use Policy, 24(2 ), 502 - 515. doi:10.1016/j.landusepol.2006.09.001 Bureau of Natural Resources of Zhangye. (2004). Zhangye Masterplan 2004 - 2020. Bureau of Natural Resources of Zhangye. (2014). Zhangye Masterplan 2012 - 2020. Bureau of Statistics of Zhangye. (2002). Zhangye St atistical Yearbook 2001. Bureau of Statistics of Zhangye. (2006). Zhangye Statistical Yearbook 2005. Bureau of Statistics of Zhangye. (2010). Zhangye Statistical Yearbook 2009. Bureau of Statistics of Zhangye. (2014). Zhangye Statistical Yearbook 2013. Bur eau of Statistics of Zhangye. (2018). Zhangye Statistical Yearbook 2017. Cao, Q., Chen, X., Shi, M., & Yao, Y. (2014). Land use/cover changes and main - factor driving force in Heihe middle reaches. Transactions of the Chinese Society of Agricultural Enginee ring, 30(5), 2014. Chen, D., Guan, X., & Tang, X. (2006). Investigation Report on the Follow - up Industry Development Situation of Returning Farmland to Forest in Zhangye City. Inner Mongolia Forestry Investigation and Design, 29(1). Chen, R. (2018). Monito ring agricultural land use change in the oasis of middle reaches of Heihe River based on remote sensing (Master's thesis, Hebei Normal University, Shijiazhuang, China). Cheng, G., Li, X., Zhao, W., Xu, Z., Feng, Q., Xiao, S., & Xiao, H. (2014). Integrated study of the water ecosystem economy in the Heihe river basin. National Science Review, 1(3), 413 - 428. doi:10.1093/nsr/nwu017 59 Cheng, J., & Masser, I. (2003). Modelling urban growth patterns: A Multiscale perspective. Environment and Planning A: Economy and Space, 35(4), 679 - 704. doi:10.1068/a35118 Chinese Ecological Protection and Restoration Department. (2018, July 9). The last round of returning farmland to forest project in Zhangye City, Gansu Province has achieved significant results. Retrieved April 7, 2020, from https://www.forestry.gov.cn/zlszz/4258/20180710/094021914330812.html Chinese National Development and Reform Commission. (2006). The 11th Five - Year Plan for the Large - scale development of western China. Chinese National Development and Reform C ommission. (2011). The 12th Five - Year Plan for the Large - scale development of western China. Chinese National Development and Reform Commission. (2016). The 13th Five - Year Plan for the Large - scale development of western China. Congalton, R. G. (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37(1), 35 - 46. doi:10.1016/0034 - 4257(91)90048 - b Dong, J., Xiao, X., Menarguez, M. A., Zhang, G., Qin, Y., Thau, e, B. (2016). Mapping Paddy rice planting area in northeastern Asia with Landsat 8 images, phenology - based algorithm and Google earth engine. Remote Sensing of Environment, 185, 142 - 154. doi:10.1016/j.rse.2016.02.016 ESRI. ( 2018 ). ArcGIS 10.6 Software. Red lands, California, USA. Foody, G. M. (2002). Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80(1), 185 - 201. doi:10.1016/s0034 - 4257(01)00295 - 4 Friedl, M., & Brodley, C. (1997). Decision tree classification of land co ver from remotely sensed data. Remote Sensing of Environment, 61(3), 399 - 409. doi:10.1016/s0034 - 4257(97)00049 - 7 Gansu Development Yearbook. (2018). Gansu Development Yearbook Editorial Board. Retrieved from https://tjj.gansu.gov.cn/tjnj/2018/indexch.htm Gansu Provincial People's Congress. (2001). The 10th Five - Year Plan for National Economic and Social Development of Gansu Province. 60 Gansu Provincial People's Congress. (2006). The 11th Five - Year Plan for National Economic and Social Development of Gansu Province. Gansu Provincial People's Congress. (2011). The 12th Five - Year Plan for National Economic and Social Development of Gansu Province. Gansu Provincial People's Congress. (2016). T he 13th Five - Year Plan for National Economic and Social Development of Gansu Province. Google. (n.d.). Google Ea rth Engine software. Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google earth engine: Planetary - scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18 - 27. doi:10.1016/j.rse.2017.06.031 Hall - Beyer, M. (2017). GLCM Texture: A Tutorial v. 3.0 March 2017. Retrieved from Hu, X., Lu, L., Li, X., Wang, J., & Guo, M. (2015). Land use/Cover change i n the middle reaches of the Heihe river basin over 2000 - 2011 and its implications for sustainable water resource management. PLOS ONE, 10(6), e0128960. doi:10.1371/journal.pone.0128960 Huang, H., Chen, Y., Clinton, N., Wang, J., Wang, X., Liu, Z . (2017). Mapping major land cover dynamics in Beijing using all Landsat images in Google earth engine. Remote Sensing of Environment, 202, 166 - 176. doi:10.1016/j.rse.2017.02.021 Jacobson, A., Dhanota, J., Godfrey, J., Jacobson, H., Rossman, Z., Stanish, A J. (2015). A novel approach to mapping land conversion using Google earth with an application to East Africa. Environmental Modelling & Software, 72, 1 - 9. doi:10.1016/j.envsoft.2015.06.011 Kuang, W., Liu, J., Dong, J., Chi, W., & Zhang, C. (20 16). The rapid and massive urban and industrial land expansions in China between 1990 and 2010: A CLUD - based analysis of their trajectories, patterns, and drivers. Landscape and Urban Planning, 145, 21 - 33. doi:10.1016/j.landurbplan.2015.10.001 61 Land Use and Cover Change. International Project Office, & International Human Dimensions Programme on Environmental Change. (1999). Land - use and land - cover change: Implementation strategy. Li, X., Cheng, G., Liu, S., Xiao, Q., Ma, M., Jin, Z. (2013). Heihe watershed allied telemetry experimental research (HiWATER): Scientific objectives and experimental design. Bulletin of the American Meteorological Society, 130121120822004. doi:10.1175/bams - d - 12 - 00154 Li, X., Cheng, G., Ge, Y., Li, H., Han, F., Hu, ai, X. (2018). Hydrological cycle in the Heihe river basin and its implication for water resource management in Endorheic basins. Journal of Geophysical Research: Atmospheres, 123(2), 890 - 914. doi:10.1002/2017jd027889 Liao, J., Wang, T., & Xue, X. (2012). Oasis Evolution in the Heihe River Basin during 1956 2010. Journal of Desert Research, 32(5). Liu, Y., Yue, W., & Fan, P. (2011). Spatial determinants of urban land conversion in large Chinese cities: A case of Hangzhou. Environment and Planning B: Plannin g and Design, 38(4), 706 - 725. doi:10.1068/b37009 Ma, R., Huang, Y., Zhou, W., Zhou, J., Bai, Z., Guan, L. (2019). Exploration and practice of ecological protection and restoration about mountains - rivers - forests - farmlands - lakes - grasslands in the Qilian Mountains. Acta Ecologica Sinica, 39(23), 8990 - 8997. Retrieved from DOI: 10 5846 /stxb201906111231 Maimaitijiang, M., Ghulam, A., Sandoval, J. O., & Maimaitiyiming, M. (2015). Drivers of lan d cover and land use changes in St. Louis metropolitan area over the past 40 years characterized by remote sensing and census population data. International Journal of Applied Earth Observation and Geoinformation, 35, 161 - 174. doi:10.1016/j.jag.2014.08.020 Moran, E. F., Skole, D. L., & Turner, B. L. (2012). The development of the international land - use and land - - cover and land - use change (LCLUC) initiative. Land Change Science, 1 - 15. doi:10.10 07/978 - 1 - 4020 - 2562 - 4_1 National Bureau of Statistics of China. (2019). China statistical yearbook 2018. China Statistics Press. OpenStreatMap. (2020). OpenStreetMap. Retrieved from https://www.openstreetmap.org 62 Petropoulos, G. P., Kalaitzidis, C., & Prasad Vadrevu, K. (2012). Support vector machines and object - based classification for obtaining land - use/cover cartography from Hyperion hyperspectral imagery. Computers & Geosciences, 41, 99 - 107. doi:10.1016/j.cageo.2011.08.019 Petropoulos, G. P., Kalaitzidis, C., & Prasad Vadrevu, K. (2012). Support vector machines and object - based classification for obtaining land - use/cover cartography from Hyperion hyperspectral imagery. Computers & Geosciences, 41, 99 - 107. doi:10.1016/j.cageo.2011.08.019 Publications, U. N. (2019). World population prospects 2019: Highlights. New York: Population Division of the UN Department of Economic and Social Affairs. Qi, C., Chen, X., Shi, M., & Yao, Y. (2014). Land use/cover changes and main - factor driving forces in Heihe middle reac hes. Transactions of the Chinese Society of Agricultural Engineering, 30(5), 221 - 227. Rodriguez - Galiano, V., Ghimire, B., Rogan, J., Chica - Olmo, M., & Rigol - Sanchez, J. (2012). An assessment of the effectiveness of a random forest classifier for land - cover classification. ISPRS Journal of Photogrammetry and Remote Sensing, 67, 93 - 104. doi:10.1016/j.isprsjprs.2011.11.002 Seto, K. C., & Kaufmann, R. K. (2003). Modeling the drivers of urban land use change in the Pearl River Delta, China: Integrating remote se nsing with socioeconomic data. Land Economics, 79(1), 106 - 121. doi:10.2307/3147108 Teluguntla, P., Thenkabail, P. S., Oliphant, A., Xiong, J., Gumma, M. K., Congalton, R. Huete, A. (2018). A 30 - m Landsat - derived cropland extent product of Australia a nd China using random forest machine learning algorithm on Google earth engine cloud computing platform. ISPRS Journal of Photogrammetry and Remote Sensing, 144, 325 - 340. doi:10.1016/j.isprsjprs.2018.07.017 Verburg, P. H., Ritsema van Eck, J. R., M de Nijs , T. C., Dijst, M. J., & Schot, P. (2004). Determinants of Land - Use Change Patterns in the Netherlands. Environment and Planning B: Planning and Design, 31, 125 - 150. Retrieved from DOI:10.1068/b307 Wang, J., Gai, C., Zhao, J., & Hu, X. (2014). Landuse/Land cover data in the middle reaches of the Heihe River Basin in 2011. Heihe Plan Science Data Center. doi:10.1068/b307 Wang, J., Hu, X., & Li, X. (2011). Landuse/Landcover data of Zhangye city in 2007. Heihe Plan Science Data Center. doi:10.3972/heihe.018.201 3.db 63 Wang, T., Gao, F., Wang, B., Wang, P., Wang, Q., Song, H., & Yi, C. (2017). Status and suggestions on ecological protection and restoration of Qilian Mountains. Journal of Glaciology and Geocryology, 39(2), 229 - 234. Retrieved from DOI:10.7522/j.issn.1 000 - 0240.2017.0026 Watson, F. G., Becker, M. S., Milanzi, J., & Nyirenda, M. (2014). Human encroachment into protected area networks in Zambia: Implications for large carnivore conservation. Regional Environmental Change, 15(2), 415 - 429. doi:10.1007/s10113 - 014 - 0629 - 5 World Bank. (2019). World Development Indicators 2019. Retrieved from https://data.worldbank.org /country/china Wu, F. (1998). Polycentric urban development and land - use change in a transitional economy: The case of Guangzhou. Environment and P lanning A: Economy and Space, 30(6), 1077 - 1100. doi:10.1068/a301077 Xiao, S., & Xiao, H. (2003). Influencing Factors of Oasis Evolution in Heihe River Basin. Journal of Desert Research, 23(4). Xiong, J., Thenkabail, P. S., Gumma, M. K., Teluguntla, P., Poe hnelt, J., Congalton, R. Thau, D. (2017). Automated cropland mapping of continental Africa using Google earth engine cloud computing. ISPRS Journal of Photogrammetry and Remote Sensing, 126, 225 - 244. doi:10.1016/j.isprsjprs.2017.01.019 Zhangye City P eople's Congress. (2001). The 10th Five - Year Plan for National Economic and Social Development in Zhangye Prefecture. Zhangye City People's Congress. (2006). The 11th Five - Year Plan for National Economic and Social Development in Zhangye Prefecture. Zhangy e City People's Congress. (2011). The 12th Five - Year Plan for National Economic and Social Development in Zhangye Prefecture. Zhangye City People's Congress. (2016). The 13th Five - Year Plan for National Economic and Social Development in Zhangye Prefecture . Zurqani, H. A., Post, C. J., Mikhailova, E. A., Schlautman, M. A., & Sharp, J. L. (2018). Geospatial analysis of land use change in the Savannah River basin using Google earth engine. International Journal of Applied Earth Observation and Geoinformation, 69, 175 - 185. doi:10.1016/j.jag.2017.12.006