ZHANG Zengxiang, LIU Fang, ZHAO Xiaoli, WANG Xiao, SHI Lifeng, XU Jinyong, YU Sisi, WEN Qingke, ZUO Lijun, YI Ling, HU Shunguang, LIU Bin. Urban Expansion in China Based on Remote Sensing Technology: A Review[J]. Chinese Geographical Science, 2018, 28(5): 727-743. doi: 10.1007/s11769-018-0988-9
Citation: ZHANG Zengxiang, LIU Fang, ZHAO Xiaoli, WANG Xiao, SHI Lifeng, XU Jinyong, YU Sisi, WEN Qingke, ZUO Lijun, YI Ling, HU Shunguang, LIU Bin. Urban Expansion in China Based on Remote Sensing Technology: A Review[J]. Chinese Geographical Science, 2018, 28(5): 727-743. doi: 10.1007/s11769-018-0988-9

Urban Expansion in China Based on Remote Sensing Technology: A Review

doi: 10.1007/s11769-018-0988-9
Funds:  Under the auspices of National Major Science and Technology Program for Water Pollution Contro and Treatment (No. 2017ZX07101001), International Partnership Program of Chinese Academy of Sciences (No. 131C11KYSB20160061)
More Information
  • Corresponding author: LIU Fang. E-mail:liufang@radi.ac.cn
  • Received Date: 2018-01-16
  • Rev Recd Date: 2018-05-03
  • Publish Date: 2018-10-27
  • Urban areas and its evolution are important anthropogenic indicators and human ecological footprints, and play decisive roles in environmental change analysis, global geo-conditional monitoring, and sustainable development. China has the highest rate of urban expansion and has emerged as an urban expansion hotspot worldwide. In this paper, the progress of studies on Chinese urban expansion based on remote sensing technology are summarized and analyzed from the aspects of urban area definition, remotely sensed imagery applied in urban expansion, monitoring methods of urban expansion, and urban expansion applications. Existing issues and future direc-tions of Chinese urban expansion are discussed and proposed. Results indicate that:1) The fusion of multi-source remotely sensed imagery is imperative to meet the needs of urban expansion with various monitoring terms and frequencies on different scales and dimensions. 2) To guarantee the classification accuracy and efficiency and describe urban expansion and its influences on local land use simultaneously, the combination of visual interpretation and automatic classification is the tendency of future monitoring methods of urban areas. 3) Urban expansion data have become the prerequisite for recognizing the urban development process, excavating its driving forces, simulating and predicting the future development directions, and also is conducive to revealing and explaining urban ecological and environmental issues. 4) In the past decades, Chinese scholars have promoted the application of remote sensing technology in the urban expansion field, with data construction, methods and models developing from the quotation stage to improvement and innovation stage; however, an independent and consistent urban expansion data on the national scale with long-term and high-frequency (such as annual monitoring) monitoring is still lacking.
  • [1] Allen P M, 1997. Cities and Regions as Self-organizing Systems:Models of Complexity. Amsterdam:Gordon and Breach Science Publishers.
    [2] Angel S, Parent J, Civco D L et al., 2011. The dimensions of global urban expansion:estimates and projections for all countries, 2000-2005. Progress in Planning, 75 (2):53-107. doi: 10.1016/j.progress.2011.04.001
    [3] Bajracharya A R, Rai R R, Rana S, 2015. Effects of urbanization on storm water run-off:a case study of Kathmandu Metropoli-tan City, Nepal. Journal of the Institute of Engineering, 11(1):36-49. doi: 10.3126/jie.v11i1.14694
    [4] Baud I, Kuffer M, Pfeffer K et al., 2010. Understanding hetero-geneity in metropolitan India:the added value of remote sensing data for analyzing sub-standard residential areas. International Journal of Applied Earth Observation and Geoinformation, 12(5):359-374. doi: 10.1016/j.jag.2010.04.008
    [5] Bou-Rabee M, Sulaiman S A, Saleh S M et al., 2017. Using arti-ficial neural networks to estimate solar radiation in Kuwait. Renewable and Sustainable Energy Reviews, 72:434-438. doi: 10.1016/j.rser.2017.01.013
    [6] Braud I, Fletcher T D, Andrieu H, 2013. Hydrology of peri-urban catchments:Processes and modelling. Journal of Hydrology, 485:1-4. doi: 10.1016/j.jhydrol.2013.02.045
    [7] Cai B F, Zhang Z X, Liu B et al., 2007. Spatial-temporal changes of Tianjin urban spatial morphology from 1978 to 2004. Jour-nal of Geographical Sciences, 17(4):500-510. doi: 10.1007/s11442-007-0500-4
    [8] Carter H, 1981. The Study of Urban Geography. London:Edward Arnold.
    [9] Che Xiuzhen, Shang Jincheng, 2004. Strategic environmental assessment for sustainable development in urbanization process in China. Chinese Geographical Science, 14(2):148-152. doi: 10.1007/s11769-004-0024-0
    [10] Chen J, Ban Y F, Li S N, 2014. China:open access to earth land- cover map. Nature, 514(7523):434. doi: 10.1038/514434c
    [11] Chen M X, Liu W D, Lu D D, 2016. Challenges and the way forward in China's new-type urbanization. Land Use Poli-cy, 55:334-339. doi: 10.1016/j.landusepol.2015.07.025
    [12] Chen Xuegang, Wei Jiang, Ren Quan et al., 2013. Effects of the urban expansion on the spatially varying trends of distribution in air pollutants concentration:a case study of Urumqi. Ecology and Environmental Sciences, 22(6):1015-1019. (in Chinese)
    [13] Chen Youchuan, 2003. Study on the reasons and policies towards the rapid expansion of large cities. City Planning Review, 27(4):33-36, 94. (in Chinese)
    [14] CIESIN, IFPRI, CIAT, 2011. Global Rural-Urban Mapping Pro-ject, Version 1 (GRUMPv1):Urban Extents Grid. Palisades:NASA Socioeconomic Data and Applications Center (SEDAC).
    [15] Clarke K C, Hoppen S, Gaydos L, 1997. A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B:Urban Analytics and City Science, 24(2):247-261. doi: 10.1068/b240247
    [16] Cockerill K, Anderson Jr W P, Harris F C et al, 2017. Hot, salty water:A confluence of issues in managing storm water runoff for urban streams. Jawra Journal of the American Water Re-sources Association, 53(3):707-724. doi:10.1111/1752-1688. 12528
    [17] Couclelis H, 1987. Cellular dynamics:How individual decisions lead to global urban change. European Journal of Operational Research, 30(3):344-346. doi:10.1016/0377-2217(87) 90080-4
    [18] Cui Xiuping, 2017. Curve fitting of urbanization and air pollution in economic development of Hohhot city, Inner Mongolia. Journal of Arid Land Resources and Environment, 31(11):44-49. (in Chinese)
    [19] Dell'Acqua F, Gamba P, 2003. Texture based characterization of urban environments on satellite SAR images. IEEE Transac-tions on Geoscience and Remote Sensing, 41 (1):153-159. doi: 10.1109/TGRS.2002.807754
    [20] Department of Economic and Social Affairs, 2009. Population Division. New York:United Nations
    [21] Dong Y, Liu Y, Chen J N, 2014. Will urban expansion lead to an increase in future water pollution loads? A preliminary inves-tigation of the Haihe River Basin in northeastern China. Envi-ronmental Science and Pollution Research, 21(11):7024-7034. doi: 10.1007/s11356-014-2620-6
    [22] Ellefsen R, Swain P, Wray J, 1973. Urban Land-use Mapping by Machine Processing of ERTS-1 Multispectral Data:a San Francisco Bay Area Example. Indiana:Purdue University
    [23] Estoque R C, Murayama Y, 2015. Intensity and spatial pattern of urban land changes in the megacities of Southeast Asia. Land Use Policy, 48:213-222. doi:10.1016/j.landusepol.2015. 05.017
    [24] Fan Zuojiang, Cheng Jicheng, Li Qi, 1997. Urban expansion based on remote sensing and GIS technology. Remote Sensing Information, (3):12-16. (in Chinese)
    [25] Feng Y J, Liu Y, Tong X H et al., 2011. Modeling dynamic urban growth using cellular automata and particle swarm optimization rules. Landscape and Urban Planning, 102(3):188-196. doi: 10.1016/j.landurbplan.2011.04.004
    [26] Foley J A, Defries R, Asner G P et al., 2005. Global consequences of land use. Science, 309(5734):570-574. doi: 10.1126/science.1111772
    [27] Gao Z Y, Kii M, Nonomura A, 2017. Urban expansion using re-mote-sensing data and a monocentric urban model. Computers, Environment and Urban Systems. doi: 10.1016/j.compenvurbsys.2017.05.002
    [28] Haase D, Nuissl H, 2007. Does urban sprawl drive changes in the water balance and policy? Case of Leipzig (Germany) 1870-2003. Landscape and Urban Planning, 80(1-2):1-13. doi: 10.1016/j.landurbplan.2006.03.011
    [29] He C Y, Gao B, Huang Q X et al., 2017. Environmental degrada-tion in the urban areas of China:evidence from multi-source remote sensing data. Remote Sensing of Environment, 193:65-75. doi: 10.1016/j.rse.2017.02.027
    [30] Heiden U, Segl K, Roessner S et al., 2007. Determination of robust spectral features for identification of urban surface materials in hyperspectral remote sensing data. Remote Sensing of Envi-ronment, 111(4):537-552. doi: 10.1016/j.rse.2007.04.008
    [31] Hu Jianbo, Li Xiaoyu, Chen Wei et al., 2008. Cityscape pattern of Shenyang based on Quickbird image and GIS. Chinese Journal of Ecology, 27(5):809-815. (in Chinese)
    [32] Imhoff M L, Zhang P, Wolfe R E et al., 2010. Remote sensing of the urban heat island effect across biomes in the continental USA. Remote Sensing of Environment, 114(3):504-513. doi: 10.1016/j.rse.2009.10.008
    [33] Jia Kun, Li Qiangzi, Tian Yichen et al., 2011. A review of classi-fication methods of remote sensing imagery. Spectroscopy and spectral analysis, 31(10):2618-2623. (in Chinese)
    [34] Jiang Zhifa, Lei Bo, Zhang Wenkai, 2007. Comparison of GM (1, n) and BP neural network model in predicting the construction lands in Fuzhou City. Journal of Water Resources and Water Engineering, 18(5):100-103. (in Chinese)
    [35] Jiang Zhihong, Li Yang, Huang D L, 2016. Impact of urbanization in different regions of eastern China on precipitation and its uncertainty. Journal of Tropical Meteorology, 22(43):382-392. doi: 10.16555/j.1006-8775.2016.03.012
    [36] Kantakumar L N, Kumara S, Schneiderb K, 2016. Spatiotemporal urban expansion in Pune metropolis, India using remote sens-ing. Habitat International, 51:11-22. doi:10.1016/j.habitatint. 2015.10.007
    [37] Kareiva P, Watts S, Mcdonald R et al., 2007. Domesticated nature:shaping landscapes and ecosystems for human welfare. Science, 316 (5833):1866-1869. doi:10.1126/science. 1140170
    [38] Le Q B, Park S J, Vlek P L G et al., 2008. Land use dynamic sim-ulator (LUDAS):a multi-agent system model for simulating spatio-temporal dynamics of coupled human-landscape system. I. Structure and theoretical specification. Ecological Informatics, 3(2):135-153. doi: 10.1016/j.ecoinf.2008.04.003
    [39] Lei Bo, 2008. The comparison of multi-regression analysis model and BP neural network model in predicting the urban con-struction land area-a case study of Fuzhou City. Urban Stud-ies, (1):24-26. (in Chinese)
    [40] Li Chunlin, Liu Miao, Hu Yuanman et al., 2014. Driving forces analysis of urban expansion based on boosted regression trees and logistic regression. Acta Ecologica Sinica, 34(3):727-737. (in Chinese)
    [41] Li Li, Chi Yaobin, Wang Zhiyong et al., 2009. The spatio-temporal dynamic characteristics in expansion of major cities in China in 30 years since the reform and opening-up. Journal of Natural Resources, 24(11):1933-1943. (in Chinese)
    [42] Li Wenliang, Zhang Lijuan, Chen Hong et al., 2010. Study on the relationship between urban expansion and land surface thermal environment change in Harbin city. Areal Research and De-velopment, 29(2):49-53, 58. (in Chinese)
    [43] Li Xia, Yeh A G O, 1999. Constrained cellular automata for mod-elling sustainable urban forms. Acta Geographica Sinica, 54(4):289-298. (in Chinese)
    [44] Li Xia, Yeh A G O, 2002. Integration of principal components analysis and cellular automata for spatial decisionmaking and urban simulation. Science in China Series D:Earth Sciences, 45(6):521-529. (in Chinese)
    [45] Li Xia, Yeh A G O, 2002. Neural network based cellular automata for realistic and idealized urban simulation. Acta Geographica Sinica, 57(2):159-166. (in Chinese)
    [46] Li Xia, Yeh A G O, 2005. Cellular automata for simulating com-plex land use systems using neural networks. Geographical Research, 24(1):19-27. (in Chinese)
    [47] Li Xia, Yeh A G O, Liu Tao et al., 2007. Analysis of error propa-gation and uncertainties in urban cellular automata. Geo-graphical Research, 26(3):443-451. (in Chinese)
    [48] Li X, Chen Y M, Liu X P et al., 2017a. Experiences and issues of using cellular automata for assisting urban and regional plan-ning in China. International Journal of Geographical Infor-mation Science, 31(8):1606-1629. doi:10.1080/13658816. 2017.1301457
    [49] Li X M, Zhou Y Y, Asrar G R et al., 2017b. The surface urban heat island response to urban expansion:a panel analysis for the conterminous united states. Science of the Total Environment, 605-606:426-635. doi: 10.1016/j.scitotenv.2017.06.229
    [50] Li Y Y, Zhang H, Kainz W, 2012. Monitoring patterns of urban heat islands of the fast-growing shanghai metropolis, china:Using time-series of Landsat TM/ETM+ data. International Journal of Applied Earth Observation and Geoinformation, 19:127-138. doi: 10.1016/j.jag.2012.05.001
    [51] Liao Heping, Peng Zheng, Hong Huikun et al., 2007. Research on dynamic mechanism and model of urban spatial expansion since the establishment of Chongqing Municipality. Geographical Research, 26(6):1137-1146. (in Chinese)
    [52] Liu F, Zhang Z X, Shi L F et al., 2016a. Urban expansion in China and its spatial-temporal differences over the past four decades. Journal of Geographical Sciences, 26(10):1477- 1496. doi: 10.1007/s11442-016-1339-3
    [53] Liu F, Zhang Z X, Wang X, 2016b. Forms of urban expansion of Chinese municipalities and provincial capitals, 1970s-2013. Remote Sensing, 8(11):930. doi: 10.3390/rs8110930
    [54] Liu Haojie, Li Aimin, 2012. Urban Expansion and Remote Sensing Applications. Zhengzhou:The Yellow River Water Conservancy Press. (in Chinese)
    [55] Liu J Y, Kuang W H, Zhang Z X et al., 2014a. Spatiotemporal characteristics, patterns, and causes of land-use changes in China since the late 1980s. Journal of Geographical Scienc-es, 24(2):195-210. doi: 10.1007/s11442-014-1082-6
    [56] Liu Jiyuan, Zhang Qian, Hu Yunfeng, 2012a. Regional differences of China's urban expansion from late 20th to early 21st century based on remote sensing information. Chinese Geographical Science, 22(1):1-14. doi:10.1007/s11769-012- 0510-8
    [57] Liu Jiyuan, Zhang Zengxiang, Zhuang Dafang et al., 2005. Spatial Temporal Information of Land Use Changes of China in 1990s basing on Remote Sensing. Beijing:Science Press. (in Chinese)
    [58] Liu Rui, 2009. The Application Research of Surface Deformation Monitoring and Urban Expansion based on 3S Technology in Tangshan City Hebei Province. Chengdu:Chengdu University of Technology. (in Chinese)
    [59] Liu Yongjian, Shen Jun, 2004. Study of prediction method of urban water consumption on genetic algorithm and neural network. Journal of Water Resource and Water Engineering, 15(4):21-25. (in Chinese)
    [60] Liu Y S, Yang R, Long H L et al., 2014b. Implications of land-use change in rural China:a case study of Yucheng, Shandong province. Land Use Policy, 40:111-118. doi: 10.1016/j.landusepol.2013.03.012
    [61] Liu Yongxue, Li Manchun, 2006. An algorithm of multi-spectral remote sensing image segmentation based on edge information. Journal of Remote Sensing, 10(3):350-356. (in Chinese)
    [62] Liu Z F, He C Y, Zhang Q F et al., 2012b. Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008. Landscape and Urban Plan-ning, 106(1):62-72. doi: 10.1016/j.landurbplan.2012.02.013
    [63] Liu Z F, He C Y, Zhou Y Y et al., 2014c. How much of the world's land has been urbanized, really? A hierarchical framework for avoiding confusion. Landscape Ecology, 29(5):763-771. doi: 10.1007/s10980-014-0034-y
    [64] Luo Xiaobo, 2011. Remote Sensing Image Intelligent Classifica-tion and its Application. Beijing:Publishing House of Elec-tronics Industry. (in Chinese)
    [65] Martinuzzi S, Gould W A, González O M R, 2007. Land devel-opment, land use, and urban sprawl in Puerto Rico integrating remote sensing and population census data. Landscape and Urban Planning, 79(3-4):288-297. doi:10.1016/j.landurbplan. 2006.02.014
    [66] McIntyre N E, Knowles-Yánez K, Hope D, 2000. Urban ecology as an interdisciplinary field:differences in the use of "urban" between the social and natural sciences. Urban Ecosystem, 4(1):5-24. doi: 10.1023/A:1009540018553
    [67] Morris A E J, 2013. History of Urban Form before the Industrial Revolution. London:Routledge.
    [68] Mountrakis G, Im J, Ogole C, 2011. Support vector machines in remote sensing:A review. ISPRS Journal of Photogrammetry and Remote Sensing, 66(3):247-259. doi:10.1016/j.isprsjprs. 2010.11.001
    [69] Muilu T, Rusanen J, 2004. Rural definitions and short-term dy-namics in rural areas of Finland in 1989-1997. Environment and Planning A:Economy and Space, 36(8):1499-1516. doi: 10.1068/a36169
    [70] NBSC (National Bureau of Statistics of the People's Republic of China), 2016. China Statistical Yearbook 2015. Beijing:China Statistics Press. (in Chinese)
    [71] Oke T R, 1973. City size and the urban heat island. Atmospheric Environment (1967), 7(8):769-779. doi:10.1016/0004-6981 (73)90140-6
    [72] Piao Yan, Ma Keming, 2006. Economic driving force of urban built-up area expansion in Beijing. Natural Resource Eco-nomics of China, (7):34-37. (in Chinese)
    [73] Potere D, Schneider A, 2007. A critical look at representations of urban areas in global maps. GeoJournal, 69(1-2):55-80. doi: 10.1007/s10708-007-9102-z
    [74] Prokop G, Jobstmann H, Schönbauer A, 2011. Report on Best Practices for Limiting Soil Sealing and Mitigating its Effects. Technical Report-2011-050, Brussels:European Commission, 231.
    [75] Pullanikkatil D, Palamuleni L G, Ruhiiga T M, 2016. Land use/land cover change and implications for ecosystems services in the Likangala River Catchment, Malawi. Physics and Chemistry of the Earth, Parts A/B/C, 93:96-103, doi:10. 1016/j.pce.2016.03.002
    [76] Ram B, Kolarkar A S, 1993. Remote sensing application in mon-itoring land-use changes in arid Rajasthan. International Journal of Remote Sensing, 14(17):3191-3200. doi: 10.1080/01431169308904433
    [77] Ren L J, Cui E Q, Sun H Y, 2014. Temporal and spatial variations in the relationship between urbanization and water quality. Environmental Science and Pollution Research, 21(23):13646-13655. doi: 10.1007/s11356-014-3242-8
    [78] Rodríguez Martín J A, De Arana C, Ramos-Miras J J et al., 2015. Impact of 70 years urban growth associated with heavy metal, pollution. Environmental Pollution, 196:156-163. doi:10. 1016/j.envpol.2014.10.014
    [79] Sarvestani M S, Ibrahim A L, Kanaroglou P, 2011. Three decades of urban growth in the city of Shiraz, Iran:a remote sensing and geographic information systems application. Cities, 28(4):320-329. doi: 10.1016/j.cities.2011.03.002
    [80] Schneider A, Friedl M A, Potere D, 2009. A new map of global urban extent from MODIS satellite data. Environmental re-search letters, 4(4):044003. doi: 10.1088/1748-9326/4/4/044003
    [81] Schneider A, Friedl MA, Potere D, 2010. Mapping global urban areas using MODIS 500-m data:new methods and datasets based on ‘urban ecoregions’. Remote Sensing of Environment, 114(8):1733-1746. doi: 10.1016/j.rse.2010.03.003
    [82] Seto K C, Fragkias M, Güneralp B et al., 2011. A meta-analysis of global urban land expansion. PLOS One, 6(8):e23777. doi: 10.1371/journal.pone.0023777
    [83] Seto K C, Güneralp B, Hutyra L R, 2012. Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences of the United States of America, 109(40):16083-16088. doi: 10.1073/pnas.1211658109
    [84] Shang Zhengyong, 2011. Evolution of Urban Spatial Morphology on Multi-scales:A Case Study in Huaian City of Jiangsu Province. Nanjing:Nanjing Normal University. (in Chinese)
    [85] Sharp J S, Clark J K, 2008. Between the country and the concrete:Rediscovering the rural-urban fringe. City and Community, 7(1):61-79. doi: 10.1111/j.1540-6040.2007.00241.x
    [86] Shi Lifeng, Liu Fang, Zhang Zengxiang et al., 2015. Spatial dif-ferences of coastal urban expansion in China from 1970s to 2013. Chinese Geographical Science, 25(4):389-403. doi: 10.1007/s11769-015-0765-y
    [87] Shi Peijun, Chen Jin, Pan Yaozhong, 2000a. Land use change mechanism in Shenzhen City. Acta Geographica Sinica, 55(2):151-160. (in Chinese)
    [88] Shi Peijun, Gong Peng, Li Xiaobing et al., 2000b. Methods and Applications of Land Use/Cover Changes. Beijing:Science Press. (in Chinese)
    [89] Shi Zepeng, Ma Youhua, Wang Yujia et al., 2012. Review on the classification methods of land use/cover based on remote sensing image. Chinese Agricultural Science Bulletin, 28(12):273-278. (in Chinese)
    [90] SMBQTS (The State Bureau of Quality and Technical Supervision, Ministry of Construction of the PRC), 1999. GB/T 50280-1998 Standard for Basic Terminology of Urban Planning. Beijing:Standards Press of China. (in Chinese)
    [91] Streutker D R, 2002. A remote sensing study of the urban heat island of Houston, Texas. International Journal of Remote Sensing, 23(13):2595-2608. doi:10.1080/0143116011011 5023
    [92] Su S L, Jiang Z L, Zhang Q et al., 2011. Transformation of agri-cultural landscapes under rapid urbanization:A threat to sus-tainability in Hang-Jia-Hu region, China. Applied Geogra-phy, 31:439-449. doi: 10.1016/j.apgeog.2010.10.008
    [93] Suriya S, Mudgal B V, 2012. Impact of urbanization on flooding:The Thirusoolam sub watershed:a case study. Journal of Hy-drology, 412-413:210-219. doi:10.1016/j.jhydrol.2011. 05.008
    [94] Tan Jianguo, Gu Wen, 2015. Research progress on urban-induced rainfall effect. Advances in Meteorological Science and Tech-nology, 5(6):17-22. (in Chinese)
    [95] Tan Minghong, Li Xiubin, Lü Changhe, 2003. An analysis of driving forces of urban land expansion in China. Economic Geography, 23(5):635-639. (in Chinese)
    [96] Tan M H, Li X B, Xie H et al., 2005. Urban land expansion and arable land loss in China-a case study of Beijing-Tianjin-Hebei region. Land Use Policy, 22(3):187-196. doi: 10.1016/j.landusepol.2004.03.003
    [97] Tao W, Liu J, Ban-Weiss G A et al., 2015. Effects of urban land expansion on the regional meteorology and air quality of East-ern China. Atmospheric Chemistry and Physics, 15(15):8597-8614. doi: 10.5194/acp-15-8597-2015
    [98] Taubenböck H, Esch T, Felbier A et al., 2012. Monitoring urbani-zation in mega cities from space. Remote sensing of environ-ment, 117:162-176. doi: 10.1016/j.rse.2011.09.015
    [99] Taubenböck H, Wiesner M, Felbier A et al., 2014. New dimensions of urban landscapes:The spatio-temporal evolution from a polynuclei area to a mega-region based on remote sensing data. Applied Geography, 47:137-153. doi:10.1016/j.apgeog. 2013.12.002
    [100] Tian G J, Ma B R, Xu X L et al., 2016. Simulation of urban ex-pansion and encroachment using cellular automata and mul-ti-agent system model-A case study of Tianjin metropolitan region, China. Ecological Indicators, 70:439-450. doi: 10.1016/j.ecolind.2016.06.021
    [101] Turner B L, Lambin E F, Reenberg A, 2007.The emergence of land change science for global environmental change and sus-tainability. Proceedings of the National Academy of Sciences of the United States of America, 104(52):20666-20671. doi: 10.1073/pnas.0704119104
    [102] Verburg P H, Neumann K, Nol L, 2011. Challenges in using land use and land cover data for global change studies. Global change biology, 17(2):974-989. doi:10.1111/j.1365-2486. 2010.02307.x
    [103] Vitousek P M, Mooney H A, Lubchenco J et al., 1997. Human domination of earth's ecosystems. Science, 277(5325):494-499. doi: 10.1126/science.277.5325.494
    [104] Wang Liping, Zhou Yankang, Xue Junfei, 2005. Study on urban land expansion and its driving mechanism in Jiangsu Province. China Land Science, 19(6):26-29. (in Chinese)
    [105] Wang H L, Qiu F, 2017. Investigating the impact of agricultural land losses on deforestation:Evidence from a peri-urban area in Canada. Ecological economics, 139:9-18. doi:10.1016/j. ecolecon.2017.04.002
    [106] Wang J, Feng J M, Yan Z W, 2015. Potential sensitivity of warm season precipitation to urbanization extents:modeling study in Beijing-Tianjin-Hebei Urban Agglomeration in China. Journal of Geophysical Research, 120(18):9408-9425. doi: 10.1002/2015JD023572
    [107] White R, Engelen G, 1993. Cellular automata and fractal urban form:a cellular modeling approach to the evolution of urban land-use patterns. Environment and Planning A:Economy and Space, 25(8):1175-1199. doi: 10.1068/a251175
    [108] White R, Engelen G, 1997. Cellular automata as the basis of inte-grated dynamic regional modelling. Environment and Planning B:Urban Analytics and City Science, 24(2):235-246. doi: 10.1068/b240235
    [109] Wilkinson G G, 2005. Results and implications of a study of fif-teen years of satellite image classification experiments. IEEE Transactions on Geoscience and Remote Sensing, 43(3):433-440. doi: 10.1109/TGRS.2004.837325
    [110] Wu F L, 1998. SimLand:a prototype to simulate land conversion through the integrated GIS and CA with AHP-derived transition rules. International Journal of Geographical information Science, 12(1):63-82. doi: 10.1080/136588198242012
    [111] Wu F, Webster C J, 1998. Simulation of land development through the integration of cellular automata and multicriteria evaluation. Environment and Planning B:Urban Analytics and City Science, 25(1):103-126. doi: 10.1068/b250103
    [112] Wu Zhiqiang, Li Dehua, 2010. Principles of Urban Planning. 4th ed. Beijing:China Architecture &Building Press. (in Chinese)
    [113] Wulder M A, White J C, Masek J G et al., 2011. Continuity of Landsat observations:short term considerations. Remote Sensing of Environment, 115(2):747-751. doi:10.1016/j.rse. 2010.11.002
    [114] Xie W X, Huang Q X, He C Y et al., 2018. Projecting the impacts of urban expansion on simultaneous losses of ecosystem ser-vices:a case study in Beijing, China. Ecological Indicators, 84:183-193. doi: 10.1016/j.ecolind.2017.08.055
    [115] Xie Y H, Weng Q H, 2017. Spatiotemporally enhancing time-series DMSP/OLS nighttime light imagery for assessing large-scale urban dynamics. ISPRS Journal of Photogrammetry and Remote Sensing, 128:1-15. doi:10.1016/j.isprsjprs. 2017.03.003
    [116] Xu Hanqiu, 2011. Urban expansion process in the center of the Fuzhou Basin, Southeast China in 1976-2006. Scientia Geo-graphica Sinica, 31(3):351-357. (in Chinese)
    [117] Xue Yanming, Liu Hui, 2017. SIMO-MIMO model urban build-ings downward-looking array SAR 3D simulation. Bulletin of Surveying and Mapping, (8):19-24. (in Chinese)
    [118] Yang Qingsheng, Li Xia, 2007. Calibrating urban cellular automata using genetic algorithms. Geographical Research, 26(2):229-237. (in Chinese)
    [119] Yang Shangguang, Wang Mark Yaolin, Wang Chunlan, 2012. Revisiting and rethinking regional urbanization in Changjiang River Delta, China. Chinese Geographical Science, 22(5):617-625. doi: 10.1007/s11769-012-0565-6
    [120] Yao Shimou, Chen Shuang, Wu Jiannan et al., 2009. Spatial ex-pansion patterns of Chinese big cities-the case of Suzhou. Scientia Geographica Sinica, 29(1):15-21. (in Chinese)
    [121] Yu Sisi, Sun Zhongchang, Guo Huadong et al., 2017. Monitoring and analyzing the spatial dynamics and patterns of megacities along the Maritime Silk Road. Journal of Remote Sensing, 21(2):169-181. (in Chinese)
    [122] Yue Wenze, 2009. Improvement of Urban Impervious Surface Estimation in Shanghai Using Landsat7 ETM+ Data. Chinese Geographical Science, 19(3):283-290. doi: 10.1007/s11769-009-0283-x
    [123] Zhang Bo, Pu Lijie, Huang Xianjin et al., 2005. Land use change and driving mechanism research in city region-the Yangtze River Delta as an example. Resources and Environment in the Yangtze Basin, 14(1):28-33. (in Chinese)
    [124] Zhang Dong, 2005. 3-D Reconstruction of Buildings based on LIDAR Data and Aerial Image. Wuhan:Wuhan University. (in Chinese)
    [125] Zhang H, Ma W C, Wang X R, 2008. Rapid urbanization and implications for flood risk management in hinterland of the Pearl River Delta, China:the Foshan study. Sensors, 8(4):2223-2239. doi: 10.3390/s8042223
    [126] Zhang L, Weng Q H, Shao Z F, 2017. An evaluation of monthly impervious surface dynamics by fusing Landsat and MODIS time series in the Pearl River Delta, China, from 2000 to 2015. Remote sensing of environment, 201:99-114. doi: 10.1016/j.rse.2017.08.036
    [127] Zhang Q W, Su S L, 2016. Determinants of urban expansion and their relative importance:a comparative analysis of 30 major metropolitans in China. Habitat International, 58:89-107. doi: 10.1016/j.habitatint.2016.10.003
    [128] Zhang Zengxiang, 2006. Remote Sensing Monitoring of Urban Expansion in China. Beijing:Star Map Publishing House, 1-20. (in Chinese)
    [129] Zhang Zengxiang, Wang Xiao, Wen Qingke et al., 2016a. Research progress of remote sensing application in land resources. Journal of Remote Sensing, 20(5):1243-1258. (in Chinese)
    [130] Zhang Z X, Wang X, Zhao X L et al., 2014. A 2010 update of Na-tional Land Use/Cover Database of China at 1:100000 scale using medium spatial resolution satellite images. Remote sensing of environment, 149:142-154. doi: 10.1016/j.rse.2014.04.004
    [131] Zhang Z X, Wen Q K, Liu F et al., 2016b. Urban expansion in China and its effect on cultivated land before and after initiating "Reform and Open Policy". Science China Earth Sciences, 59(10):1930-1944. doi: 10.1007/s11430-015-0160-2
    [132] Zhang Y Y, Xia J, Yu J J et al., 2018. Simulation and assessment of urbanization impacts on runoff metrics:insights from landuse changes. Journal of Hydrology, 560:247-258. doi: 10.1016/j.jhydrol.2018.03.031
    [133] Zhao D X, Sing T F, 2017. Air pollution, economic spillovers, and urban growth in China. The Annals of Regional Science, 58(2):32-34. doi: 10.1007/s00168-016-0783-4
    [134] Zhao L, Lee X, Smith R B et al., 2014. Strong contributions of local background climate to urban heat islands. Nature, 511(7508):216-219. doi: 10.1038/nature13462
    [135] Zheng Yiqun, Gui Zhicheng, Qiang Xuemin et al., 2013. Simula-tion of the impacts of urbanization in different areas of china on East Asia summer monsoon climate. Progress in Geophysics, 28(2):554-569. (in Chinese)
    [136] Zhou Chenghu, Sun Zhanli, Xie Yichun, 1999. Geo-cellular Au-tomata. Beijing:Science Press. (in Chinese)
    [137] Zhou Hongmei, Gao Yang, Ge Weiqiang et al., 2008. The research on the relationship between the urban expansion and the change of the urban heat island distribution in Shanghai Area. Ecology and Environment, 17(1):163-168. (in Chinese)
    [138] Zhu Huiyi, He Shujin, Zhang Ming, 2001. Driving forces analysis of land use change in Bohai Rim. Geographical Research, 20(6):669-678. (in Chinese)
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Article Metrics

Article views(306) PDF downloads(648) Cited by()

Proportional views
Related

Urban Expansion in China Based on Remote Sensing Technology: A Review

doi: 10.1007/s11769-018-0988-9
Funds:  Under the auspices of National Major Science and Technology Program for Water Pollution Contro and Treatment (No. 2017ZX07101001), International Partnership Program of Chinese Academy of Sciences (No. 131C11KYSB20160061)
    Corresponding author: LIU Fang. E-mail:liufang@radi.ac.cn

Abstract: Urban areas and its evolution are important anthropogenic indicators and human ecological footprints, and play decisive roles in environmental change analysis, global geo-conditional monitoring, and sustainable development. China has the highest rate of urban expansion and has emerged as an urban expansion hotspot worldwide. In this paper, the progress of studies on Chinese urban expansion based on remote sensing technology are summarized and analyzed from the aspects of urban area definition, remotely sensed imagery applied in urban expansion, monitoring methods of urban expansion, and urban expansion applications. Existing issues and future direc-tions of Chinese urban expansion are discussed and proposed. Results indicate that:1) The fusion of multi-source remotely sensed imagery is imperative to meet the needs of urban expansion with various monitoring terms and frequencies on different scales and dimensions. 2) To guarantee the classification accuracy and efficiency and describe urban expansion and its influences on local land use simultaneously, the combination of visual interpretation and automatic classification is the tendency of future monitoring methods of urban areas. 3) Urban expansion data have become the prerequisite for recognizing the urban development process, excavating its driving forces, simulating and predicting the future development directions, and also is conducive to revealing and explaining urban ecological and environmental issues. 4) In the past decades, Chinese scholars have promoted the application of remote sensing technology in the urban expansion field, with data construction, methods and models developing from the quotation stage to improvement and innovation stage; however, an independent and consistent urban expansion data on the national scale with long-term and high-frequency (such as annual monitoring) monitoring is still lacking.

ZHANG Zengxiang, LIU Fang, ZHAO Xiaoli, WANG Xiao, SHI Lifeng, XU Jinyong, YU Sisi, WEN Qingke, ZUO Lijun, YI Ling, HU Shunguang, LIU Bin. Urban Expansion in China Based on Remote Sensing Technology: A Review[J]. Chinese Geographical Science, 2018, 28(5): 727-743. doi: 10.1007/s11769-018-0988-9
Citation: ZHANG Zengxiang, LIU Fang, ZHAO Xiaoli, WANG Xiao, SHI Lifeng, XU Jinyong, YU Sisi, WEN Qingke, ZUO Lijun, YI Ling, HU Shunguang, LIU Bin. Urban Expansion in China Based on Remote Sensing Technology: A Review[J]. Chinese Geographical Science, 2018, 28(5): 727-743. doi: 10.1007/s11769-018-0988-9
Reference (138)

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return