DMSP/OLS夜间灯光数据在城市化发展研究中起着重要作用。基于5年（1992、1997、2002、2007、2012年）的稳定夜间灯光数据，从时空角度分析绿洲区域夜间灯光数据的变化特征，揭示其演变规律，探讨绿洲城市发展趋势。结果表明：（1）时间序列的夜间灯光数据表现出分散向规则分布转变的趋势。尤其是2007年的核心区域灯光达到饱和状态（值为63），外部边缘区域增长明显，反映出绿洲城市中心可利用空间的有限性导致城市边缘区向外扩展的范围增加和速度加快的现象。（2）夜间灯光数据在空间上呈现出单核心点状向以道路为中心的带状发展趋势，这与绿洲城市发展建设过程相一致。（3）借助非确定型决策分析方法预测2027年绿洲地区发展趋势，结果显示2027年乐观估计整个区域夜间灯光数据比2012年增加0.3倍，城镇区域将扩大约0.6倍，悲观估计整个区域夜间灯光数据增加近2倍，城镇区域将扩大约3倍。从而可以推断社会经济发展将对绿洲环境有较大的影响，在未来15年内绿洲发展应注重环境承载力与人类社会经济发展的协调性问题。
Night-time satellite images from the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) are widely used in the research of urban development. The stable night light data in 1992, 1997, 2002, 2007 and 2012 were selected to analyze the spatio-temporal distribution in the Hotan oasis of Xingjiang to reveal the law of changes, and to probe into the developing tendency of urban in desert area. The results are shown as follows: (1) The distribution of stable night light data show the phenomenon from decentralized state to the regular which reflects the process of regional social economy development from low to high. Especially in 2007, the core area of light data reached the saturation state (the value is 63), and significantly region growth on the outer edge. This reflects the center development of oasis city was tending to stability, and limited available space in core resulted to extend outwards continuously and accelerate speed. (2)The spatial distribution of stable nighttime light data showed the trend from point to belt along the road, which is consistent with the development of oasis cities. (3)The development trend of oasis cities in 2027 was forecasted with uncertain decision analysis. By 2027, the optimistic estimate of the entire region of light data increased by 0.3 times than 2012, and the urban area would expand about 0.6 times. The pessimistic estimate of light data nearly increased by 2 times, and the urban area would expand by 3 times. It can be inferred that the social and economic development will have the greater impact on the oasis environment. Therefore, in the next 15 years, we should pay more attention to the coordination of environmental capacity and the development of human society and economy.
[1] Imhoff M L,Lawrence W T,Stutzer D C.A technique for using composite DMSP/OLS “city lights” satellite data to accurately map urban areas[J].Remote Sensing of Environment,1997,61:261-370.
[2] Sutton P C.A scale adjusted measure of urban sprawl using nighttime satellite imagery[J].Remote Sensing of Environment,2003,86(3):353-369.
[3] Henderson M,Yeh E T,Gong P.Validation of urban boundaries derived from global night-time satellite imagery[J].International Journal of Remote Sensing,2003,24(3):595-609.
[4] Small C,Pozzi F,Elvidge C D.Spatial analysis of global urban extent from DMSP-OLS night lights[J].Remote Sensing of Environment,2005,96:277-291.
[5] Amaral S,Camara G,Miguel A.Estimating populationand energy consumption in Brazilian Amazonia using DMSP night-time satellite data[J].Computers,Environment and Urban Systems,2005,29:179-195.
[6] Ma Q,He C Y,Wu J G,et al.Quantifying spatiotemporal patterns of urban impervious surfaces in China:an improved assessment using nighttime light data[J].Landscape and Urban Planning,2014,130:36-49.
[7] Chowdhury P K R,Maithani S.Modelling urban growth in the Indo-Gangetic plain using nighttime OLS data and cellular automata[J].International Journal of Applied Earth Observation and Geoinformation,2014,33(1):155-165.
[8] Zhang Q L,Seto K C.Mapping urbanization dynamics at regional and global scales using multi-temporal DMSP/OLS nighttime light data[J].Remote Sensing of Environment,2011,115:2320-2329.
[9] Ma T,Zhou Y K,Zhou C H,et al.Night-time light derived estimation of spatio-temporal characteristics of urbanization dynamics using DMSP/OLS satellite data[J].Remote Sensing of Environment,2015,158:453-464.
[10] Zhou Y Y,Smith S J,Elvidge C D.A cluster-based method to map urban area from DMSP/OLS nightlights[J].Remote Sensing of Environment,2014,147:173-185.
[11] Huang Q X,He C Y,Gao B,et al.Detecting the 20 year city-size dynamics in China with a rank clock approach and DMSP/OLS nighttime data[J].Landscape and Urban Planning,2015,137:138-148.
[12] 卓莉,史培军,陈晋,等.20世纪90年代中国城市时空变化特征——基于灯光指数CNLI方法的探讨[J].地理学报,2003,58(6):893-902.
[13] Dickinson L C,Boselly S E,Burgmann W W.Defense Meteorological Satellite Program User's Guide,Air Weather Service (MAC)[R].US Air Force,1974.
[14] National Geophysical Data Center.Operational linescan systern-data description[EB/OL].2014.http://ngdc.noaa.gov/eog/dmsp/downloadV4composites.html.
[15] Pandey B,Joshi P K,Seto K C.Monitoring urbanization dynamics in India using DMSP/OLS night time lights and SPOT-VGT data[J].International Journal of Applied Earth Observation and Geoinformation,2013,23:49-61.
[16] Ma T,Zhou C,Pei T,et al.Quantitative estimation of urbanization dynamics using time series of DMSP_OLS nighttime light data-A comparative case study from China's cities[J].Remote Sensing of Environment,2012,124:99-107.
[17] Liu Z,He C,Zhang Q,et al.Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008[J].Landscape and Urban Planning,2012,106:62-67.
[18] Small C,Pozzi F,Elvidge C D.Spatial analysis of global urban extent from DMSP-OLS night lights[J].Remote Sensing of Environment,2005,96(3/4):277-291.
[19] Sutton P,Roberts D,Elvidge C,et al.Census from Heaven: an estimate of the global human population using night-time satellite imagery[J].Remote sensing,2001,16(22):3061-3076.
[20] Zhou L,Shi P J,Chen J,et al.Application of compound night light index derived from DMSP OLS to urbanization analysis in China in the 1990s[J].Acta Geographica Sinica,2003,8(6):893-902.
[21] 王晓慧,肖鹏峰,冯学智,等.基于DMSP/OLS数据的中国大尺度城镇用地信息提取[J].国土资源遥感,2013,25(3):159-164.
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