浏览全部资源
扫码关注微信
纸质出版日期： 2021-01-07 ，
扫 描 看 全 文
余柏蒗，王丛笑，宫文康，陈佐旗，施开放，吴宾，洪宇辰，李乔玄，吴健平.2021.夜间灯光遥感与城市问题研究：数据、方法、应用和展望.遥感学报，25（1）： 342-364
Yu B L，Wang C X，Gong W K，Chen Z Q，Shi K F，Wu B，Hong Y C，Li Q X and Wu J P. 2021. Nighttime light remote sensing and urban studies： Data， methods， applications， and prospects. National Remote Sensing Bulletin， 25（1）：342-364
夜间灯光遥感是能够探测夜间微光的光学遥感技术，可获取白天遥感无法获取的信息。由于城市区域的人造光源是夜间稳定亮光的主要来源，夜间灯光遥感影像已被证明可以更直观地反映夜间人类活动差异，同时具有覆盖范围大、时效快和易获取等优势，可广泛应用于多尺度长时序的城市问题研究。目前，基于夜间灯光遥感数据的应用研究成果较为丰富，不少学者对夜间灯光遥感数据的数据预处理以及应用潜力等方面进行了归纳。但基于夜间灯光遥感与城市问题研究的整理和总结还有待进一步加强。基于此，本文通过对近几十年来有关夜间灯光遥感数据的研究成果进行了详细梳理，从多尺度城市空间结构分析、城市社会经济指标估算以及城市公共安全领域研究3方面入手，系统梳理夜间灯光遥感数据的应用能力。进一步根据数据应用过程中出现的问题，从夜间灯光遥感日数据应用、长时间序列数据集生产以及定量验证等角度探讨了夜间灯光遥感所面临的挑战与前景。
Nighttime light remote sensing is a unique optical remote sensing technology that can record ground object radiation information at night that cannot be obtained by daytime remote sensing. Given that artificial light in urban areas is the main source of stable nighttime light
nighttime light remote sensing images have been proven to reflect the variation in human activities at night. At the same time
they have extensive coverage
are time intensive and readily available
and have widely been a proxy for urban studies on the multi-scale or long-term analysis. The application related to the nighttime light data is growing at present. However
most reviews have focused on the preprocessing and potential application of nighttime light data
and the summary of nighttime light data in urban studies is still limited. In this study
we reviewed nighttime light-related research in three aspects: multi-scale analysis of the urban spatial structure
multi-scale estimation of urban socio-economic indicators
and research in urban public security. Three challenges
namely
the application of nighttime light data with a short time interval
the generation of longer nighttime light time series
and the quantitative validation
are also discussed to explore the potential applications in the future.
夜间灯光遥感城市研究多尺度综述
nighttime lightremote sensingurban studymulti-scalereview
Amaral S, Monteiro A M V, Camara G and Quintanilha J A. 2006. DMSP/OLS night-time light imagery for urban population estimates in the Brazilian Amazon. International Journal of Remote Sensing, 27(5): 855-870 [DOI: 10.1080/01431160500181861http://dx.doi.org/10.1080/01431160500181861]
Anas A, Arnott R and Small K A. 1998. Urban spatial structure. Journal of Economic Literature, 36(3): 1426-1464
Ardila D and Pack D. 2016. The cubesat multispectral observation system (CUMULOS)//Proceedings of Conference on Characterization and Radiometric Calibration for Remote Sensing. [s.l.]: [s.n.]
Bai X M, Shi P J and Liu Y S. 2014. Society: realizing China's urban dream. Nature, 509(7499): 158-160 [DOI: 10.1038/509158ahttp://dx.doi.org/10.1038/509158a]
Bauer S E, Wagner S E, Burch J, Bayakly R and Vena J E. 2013. A case-referent study: light at night and breast cancer risk in Georgia. International Journal of Health Geographics, 12: 23 [DOI: 10.1186/1476-072X-12-23http://dx.doi.org/10.1186/1476-072X-12-23]
Baugh K, Hsu F C, Elvidge C D and Zhizhin M. 2013. Nighttime lights compositing using the VIIRS day-night band: preliminary results. Proceedings of the Asia-Pacific Advanced Network, 35: 70-86 [DOI: 10.7125/apan.35.8http://dx.doi.org/10.7125/apan.35.8]
Cai J X, Huang B and Song Y M. 2017. Using multi-source geospatial big data to identify the structure of polycentric cities. Remote Sensing of Environment, 202: 210-221 [DOI: 10.1016/j.rse.2017.06.039http://dx.doi.org/10.1016/j.rse.2017.06.039]
Cao C Y and Bai Y. 2014. Quantitative analysis of VIIRS DNB nightlight point source for light power estimation and stability monitoring. Remote Sensing, 6(12): 11915-11935 [DOI: 10.3390/rs61211915http://dx.doi.org/10.3390/rs61211915]
Cao C Y, Shao X and Uprety S. 2013. Detecting light outages after severe storms using the S-NPP/VIIRS day/night band radiances. IEEE Geoscience and Remote Sensing Letters, 10(6): 1582-1586 [DOI: 10.1109/LGRS.2013.2262258http://dx.doi.org/10.1109/LGRS.2013.2262258]
Cao L Q, Li P X and Zhang L P. 2009. Urban population estimation based on the DMSP/OLS night-time Satellite Data——A case of Hubei province. Remote Sensing Information, (1): 83-87
曹丽琴, 李平湘, 张良培. 2009. 基于DMSP/OLS夜间灯光数据的城市人口估算——以湖北省各县市为例. 遥感信息, (1): 83-87 [DOI: 10.3969/j.issn.1000-3177.2009.01.016]
Cao X, Chen J, Imura H and Higashi O. 2009. A SVM-based method to extract urban areas from DMSP-OLS and SPOT VGT data. Remote Sensing of Environment, 113(10): 2205-2209 [DOI: 10.1016/j.rse.2009.06.001http://dx.doi.org/10.1016/j.rse.2009.06.001]
Chander G, Markham B L and Helder D L. 2009. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment, 113(5): 893-903 [DOI: 10.1016/j.rse.2009.01.007http://dx.doi.org/10.1016/j.rse.2009.01.007]
Chen J, Zhuo L, Shi P J and Ichinose T. 2003. The study on urbanization process in China based on DMSP/OLS data: development of a light index for urbanization level estimation. Journal of Remote Sensing, 7(3): 168-175
陈晋, 卓莉, 史培军, 一之濑俊明. 2003. 基于DMSP/OLS数据的中国城市化过程研究——反映区域城市化水平的灯光指数的构建. 遥感学报, 7(3): 168-175 [DOI: 10.3321/j.issn:1007-4619.2003.03.002http://dx.doi.org/10.3321/j.issn:1007-4619.2003.03.002]
Chen J Q, Wei H, Li N, Chen S Q, Qu W Q and Zhang Y. 2020. Exploring the spatial-temporal dynamics of the Yangtze River delta urban agglomeration based on night-time light remote sensing technology. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13: 5369-5383 [DOI: 10.1109/JSTARS.2020.3022178http://dx.doi.org/10.1109/JSTARS.2020.3022178]
Chen Q, Ding M J, Yang X C and Hu K J. 2017. Spatially explicit assessment of heat health risks using multi-source data: a case study of the Yangtze River delta region, China. Journal of Geo-Information Science, 19(11): 1475-1484
陈倩, 丁明军, 杨续超, 胡可嘉. 2017. 长江三角洲地区高温热浪人群健康风险评价. 地球信息科学学报, 19(11): 1475-1484 [DOI: 10.3724/SP.J.1047.2017.01475http://dx.doi.org/10.3724/SP.J.1047.2017.01475]
Chen X and Nordhaus W D. 2011. Using luminosity data as a proxy for economic statistics. Proceedings of the National Academy of Sciences of the United States of America, 108(21): 8589-8594 [DOI: 10.1073/pnas.1017031108http://dx.doi.org/10.1073/pnas.1017031108]
Chen X and Nordhaus W D. 2019. VIIRS nighttime lights in the estimation of cross-sectional and time-series GDP. Remote Sensing, 11(9): 1057 [DOI: 10.3390/rs11091057http://dx.doi.org/10.3390/rs11091057]
Chen X X, Wu A S, Xiong X X, Lei N and Chiang K. 2016. Using ground targets to validate S-NPP VIIRS day-night band calibration. Remote Sensing, 8(12): 984 [DOI: 10.3390/rs8120984http://dx.doi.org/10.3390/rs8120984]
Chen Z J, Liu Y M, Liu X and Kong F B. 2018. Research on carbon emission peak in Yangtze River economic zone with steady economic growth: based on data of global night-time light. Journal of Natural Resources, 33(12): 2213-2222
陈志建, 刘月梅, 刘晓, 孔凡斌. 2018. 经济平稳增长下长江经济带碳排放峰值研究——基于全球夜间灯光数据的视角. 自然资源学报, 33(12): 2213-2222 [DOI: 10.31497/zrzyxb.20171145http://dx.doi.org/10.31497/zrzyxb.20171145]
Chen Z Q, Yu B L, Hu Y J, Huang C, Shi K F and Wu J P. 2015. Estimating house vacancy rate in metropolitan areas using NPP-VIIRS nighttime light composite data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(5): 2188-2197 [DOI: 10.1109/JSTARS.2015.2418201http://dx.doi.org/10.1109/JSTARS.2015.2418201]
Chen Z Q, Yu B L, Song W, Liu H X, Wu Q S, Shi K F and Wu J P. 2017. A new approach for detecting urban centers and their spatial structure with nighttime light remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 55(11): 6305-6319 [DOI: 10.1109/TGRS.2017.2725917http://dx.doi.org/10.1109/TGRS.2017.2725917]
Chen Z Q, Yu B L, Zhou Y Y, Liu H X, Yang C S, Shi K F and Wu J P. 2019. Mapping global urban areas from 2000 to 2012 using time-series nighttime light data and MODIS products. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(4): 1143-1153 [DOI: 10.1109/JSTARS.2019.2900457http://dx.doi.org/10.1109/JSTARS.2019.2900457]
Cheng B, Chen Z Q, Yu B L, Li Q X, Wang C X, Li B B, Wu B, Li Y and Wu J P. 2020. Automated extraction of street lights from JL1-3B nighttime light data and assessment of their solar energy potential. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13: 675-684 [DOI: 10.1109/JSTARS.2020.2971266http://dx.doi.org/10.1109/JSTARS.2020.2971266]
Cinzano P, Falchi F, Elvidge C D and Baugh K E. 2000. The artificial night sky brightness mapped from DMSP satellite operational Linescan system measurements. Monthly Notices of the Royal Astronomical Society, 318(3): 641-657 [DOI: 10.1046/j.1365-8711.2000.03562.xhttp://dx.doi.org/10.1046/j.1365-8711.2000.03562.x]
Cole T A, Wanik D W, Molthan A L, Román M O and Griffin R E. 2017. Synergistic use of nighttime satellite data, electric utility infrastructure, and ambient population to improve power outage detections in urban areas. Remote Sensing, 9(3): 286 [DOI: 10.3390/rs9030286http://dx.doi.org/10.3390/rs9030286]
Colomb R, Alonso C and Nollmann I. 2003. SAC-C mission and the international am constellation for earth observation. Acta Astronautica, 52(9/12): 995-1005 [DOI: 10.1016/S0094-5765(03)00 082-1http://dx.doi.org/10.1016/S0094-5765(03)00082-1]
Coscieme L, Sutton P C, Anderson S, Liu Q and Elvidge C D. 2017. Dark times: nighttime satellite imagery as a detector of regional disparity and the geography of conflict. GIScience and Remote Sensing, 54(1): 118-139 [DOI: 10.1080/15481603.2016.1260676http://dx.doi.org/10.1080/15481603.2016.1260676]
Doll C N H. 2008. CIESIN thematic guide to night-time light remote sensing and its applications. Center for International Earth Science Information Network, Columbia University
Doll C N H, Muller J P and Elvidge C D. 2000. Night-time imagery as a tool for global mapping of socioeconomic parameters and greenhouse gas emissions. AMBIO: A Journal of the Human Environment, 29(3): 157-162 [DOI: 10.1579/0044-7447-29.3.157http://dx.doi.org/10.1579/0044-7447-29.3.157]
Doll C N H, Muller J P and Morley J G. 2006. Mapping regional economic activity from night-time light satellite imagery. Ecological Economics, 57(1): 75-92 [DOI: 10.1016/j.ecolecon.2005.03.007http://dx.doi.org/10.1016/j.ecolecon.2005.03.007]
Dong Y, Varquez A C G and Kanda M. 2017. Global anthropogenic heat flux database with high spatial resolution. Atmospheric Environment, 150: 276-294 [DOI: 10.1016/j.atmosenv.2016.11.040http://dx.doi.org/10.1016/j.atmosenv.2016.11.040]
Duh J D, Shandas V, Chang H and George L A. 2008. Rates of urbanisation and the resiliency of air and water quality. Science of the Total Environment, 400(1/3): 238-256 [DOI: 10.1016/j.scitotenv.2008.05.002http://dx.doi.org/10.1016/j.scitotenv.2008.05.002]
Elvidge C D, Baugh K E, Kihn E A, Kroehl H W and Davis E R. 1997a. Mapping city lights with nighttime data from the DMSP operational Linescan system. Photogrammetry and Remote Sensing, 63(6): 727-734
Elvidge C D, Baugh K E, Kihn E A, Kroehl H W, Davis E R and Davis C W. 1997b. Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumption. International Journal of Remote Sensing, 18(6): 1373-1379 [DOI: 10.1080/014311697218485http://dx.doi.org/10.1080/014311697218485]
Elvidge C D, Baugh K E, Dietz J B, Bland T, Sutton P C and Kroehl H W. 1999. Radiance calibration of DMSP-OLS low-light imaging data of human settlements. Remote Sensing of Environment, 68(1): 77-88 [DOI: 10.1016/S0034-4257(98)00098-4http://dx.doi.org/10.1016/S0034-4257(98)00098-4]
Elvidge C D, Baugh K E, Anderson S J, Sutton P C and Ghosh T. 2012. The night light development Index (NLDI): a spatially explicit measure of human development from satellite data. Social Geography, 7(1): 23-35 [DOI: 10.5194/sg-7-23-2012http://dx.doi.org/10.5194/sg-7-23-2012]
Elvidge C D, Baugh K E, Zhizhin M and Hsu F C. 2013b. Why VIIRS data are superior to DMSP for mapping nighttime lights. Proceedings of the Asia-Pacific Advanced Network, 35: 62-69 [DOI: 10.7125/apan.35.7http://dx.doi.org/10.7125/apan.35.7]
Elvidge C D, Erwin E H, Baugh K E, Ziskin D, Tuttle B T, Ghosh T and Sutton P C. 2009a. Overview of DMSP nightime lights and future possibilities//Proceedings of 2009 Joint Urban Remote Sensing Event. Shanghai, China: IEEE: 1-5 [DOI: 10.1109/URS.2009.5137749http://dx.doi.org/10.1109/URS.2009.5137749]
Elvidge C D, Ghosh T, Hsu F C, Zhizhin M and Bazilian M. 2020. The dimming of lights in China during the COVID-19 pandemic. Remote Sensing, 12(17): 2851 [DOI: 10.3390/rs12172851http://dx.doi.org/10.3390/rs12172851]
Elvidge C D, Imhoff M L, Baugh K E, Hobson V R, Nelson I, Safran J, Dietz J B and Tuttle B T. 2001. Night-time lights of the world: 1994-1995. ISPRS Journal of Photogrammetry and Remote Sensing, 56(2): 81-99 [DOI: 10.1016/S0924-2716(01)00040-5http://dx.doi.org/10.1016/S0924-2716(01)00040-5]
Elvidge C D, Sutton P C, Ghosh T, Tuttle B T, Baugh K E, Bhaduri B and Bright E. 2009b. A global poverty map derived from satellite data. Computers and Geosciences, 35(8): 1652-1660 [DOI: 10.1016/j.cageo.2009.01.009http://dx.doi.org/10.1016/j.cageo.2009.01.009]
Elvidge C D, Zhizhin M, Hsu F C and Baugh K. 2013a. What is so great about nighttime VIIRS data for the detection and characterization of combustion sources? Proceedings of the Asia-Pacific Advanced Network, 35: 33-48 [DOI: 10.7125/APAN.35.5http://dx.doi.org/10.7125/APAN.35.5]
Elvidge C D, Zhizhin M, Hsu F C and Baugh K E. 2013c. VIIRS nightfire: satellite pyrometry at night. Remote Sensing, 5(9): 4423-4449 [DOI: 10.3390/rs5094423http://dx.doi.org/10.3390/rs5094423]
Elvidge C D, Ziskin D, Baugh K E, Tuttle B T, Ghosh T, Pack D W, Erwin E H and Zhizhin M. 2009c. A fifteen year record of global natural gas flaring derived from satellite data. Energies, 2(3): 595-622 [DOI: 10.3390/en20300595http://dx.doi.org/10.3390/en20300595]
Falchi F, Cinzano P, Duriscoe D, Kyba C C M, Elvidge C D, Baugh K, Portnov B A, Rybnikova N A and Furgoni R. 2016. The new world atlas of artificial night sky brightness. Science Advances, 2(6): e1600377 [DOI: 10.1126/sciadv.1600377http://dx.doi.org/10.1126/sciadv.1600377]
Fang C L. 2009. Research progress and general definition about identification standards of urban agglomeration space. Urban Planning Forum, (4): 1-6
方创琳. 2009. 城市群空间范围识别标准的研究进展与基本判断. 城市规划学刊, (4): 1-6 [DOI: 10.3969/j.issn.1000-3363.2009.04.001]
Fang C L. 2015. Important progress and future direction of studies on China’s urban agglomerations. Journal of Geographical Sciences, 25(8): 1003-1024 [DOI: 10.1007/s11442-015-1216-5http://dx.doi.org/10.1007/s11442-015-1216-5]
Fang C L and Yu D L. 2017. Urban agglomeration: an evolving concept of an emerging phenomenon. Landscape and Urban Planning, 162: 126-136 [DOI: 10.1016/j.landurbplan.2017.02.014http://dx.doi.org/10.1016/j.landurbplan.2017.02.014]
Foley J A, DeFries R, Asner G P, Barford C, Bonan G, Carpenter S R, Chapin F S, Coe M T, Daily G C, Gibbs H K, Helkowski J H, Holloway T, Howard E A, Kucharik C J, Monfreda C, Patz J A, Prentice I C, Ramankutty N and Snyder P K. 2005. Global consequences of land use. Science, 309(5734): 570-574 [DOI: 10.1126/science.1111772http://dx.doi.org/10.1126/science.1111772]
Gao Y, Wang H, Wang P T, Sun X Y and Lv T T. 2013. Population spatial processing for Chinese coastal zones based on census and multiple night light data. Resources Science, 35(12): 2517-2523
高义, 王辉, 王培涛, 孙晓宇, 吕婷婷. 2013. 基于人口普查与多源夜间灯光数据的海岸带人口空间化分析. 资源科学, 35(12): 2517-2523
Ghosh T, Anderson S, Powell R L, Sutton P C and Elvidge C D. 2009. Estimation of Mexico’s informal economy and remittances using nighttime imagery. Remote Sensing, 1(3): 418-444 [DOI: 10.33 90/rs1030418http://dx.doi.org/10.3390/rs1030418]
Gillespie T W, Frankenberg E, Chum K F and Thomas D. 2014. Night-time lights time series of tsunami damage, recovery, and economic metrics in Sumatra, Indonesia. Remote Sensing Letters, 5(3): 286-294 [DOI: 10.1080/2150704X.2014.900205http://dx.doi.org/10.1080/2150704X.2014.900205]
Gottmann J. 1957. Megalopolis or the urbanization of the northeastern seaboard. Economic Geography, 33(3): 189-200 [DOI: 10.2307/142307http://dx.doi.org/10.2307/142307]
Gu C L. 2011. Study on urban agglomeration: progress and prospects. Geographical Research, 30(5): 771-784
顾朝林. 2011. 城市群研究进展与展望. 地理研究, 30(5): 771-784 [DOI: 10.11821/yj2011050001http://dx.doi.org/10.11821/yj2011050001]
Guo W, Lu D S, Wu Y L and Zhang J X. 2015. Mapping impervious surface distribution with integration of SNNP VIIRS-DNB and MODIS NDVI data. Remote Sensing, 7(9): 12459-12477 [DOI: 10.3390/rs70912459http://dx.doi.org/10.3390/rs70912459]
Guo W, Zhang Y H and Gao L. 2018. Using VIIRS-DNB and Landsat data for impervious surface area mapping in an arid/semiarid region. Remote Sensing Letters, 9(6): 587-596 [DOI: 10.1080/2150704X.2018.1455234http://dx.doi.org/10.1080/2150704X.2018.1455234]
Han P P, Huang J L, Li R D, Wang L H, Hu Y X, Wang J L and Huang W. 2014. Monitoring trends in light pollution in China based on nighttime satellite imagery. Remote Sensing, 6(6): 5541-5558 [DOI: 10.3390/rs6065541http://dx.doi.org/10.3390/rs6065541]
Hattori R, Horie S, Hsu F C, Elvidge C D and Matsuno Y. 2014. Estimation of in-use steel stock for civil engineering and building using nighttime light images. Resources, Conservation and Recycling, 83: 1-5 [DOI: 10.1016/j.resconrec.2013.11.007http://dx.doi.org/10.1016/j.resconrec.2013.11.007]
Hayashi H, Hashitera S, Kohiyama M, Matsuoka M, Maki N, Fujita H and Elvidge C D. 2000. International collaboration for the early damaged area estimation system using DMSP/OLS nighttime images//Proceedings of IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings. Honolulu, HI, USA, USA: IEEE, 6: 2697-2699 [DOI: 10.1109/IGARSS.2000.859685http://dx.doi.org/10.1109/IGARSS.2000.859685]
He C Y, Li J G, Chen J, Shi P J, Pan Y Z, Li J, Zhuo L and Ichinose T. 2005. The urbanization model and process in Bohai Sea surrounding area in the 1990s by using DMSP/OLS data. Acta Geographica Sinica, 60(3): 409-417
何春阳, 李景刚, 陈晋, 史培军, 潘耀忠, 李京, 卓莉, 一之濑俊明. 2005. 基于夜间灯光数据的环渤海地区城市化过程. 地理学报, 60(3): 409-417 [DOI: 10.11821/xb200503007http://dx.doi.org/10.11821/xb200503007]
He C Y, Liu Z F, Gou S Y, Zhang Q F, Zhang J S and Xu L L. 2019. Detecting global urban expansion over the last three decades using a fully convolutional network. Environmental Research Letters, 14(3): 034008 [DOI: 10.1088/1748-9326/aaf936http://dx.doi.org/10.1088/1748-9326/aaf936]
He C Y, Ma Q, Liu Z F and Zhang Q F. 2014. Modeling the spatiotemporal dynamics of electric power consumption in mainland China using saturation-corrected DMSP/OLS nighttime stable light data. International Journal of Digital Earth, 7(12): 993-1014 [DOI: 10.1080/17538947.2013.822026http://dx.doi.org/10.1080/17538947.2013.822026]
He C Y, Shi P J, Li J G, Chen J, Pan Y Z, Li J, Zhuo L and Ichinose T. 2006. Restoring urbanization process in China in the 1990s by using non-radiance-calibrated DMSP/OLS nighttime light imagery and statistical data. Chinese Science Bulletin, 51(7): 1614-1620
何春阳, 史培军, 李景刚, 陈晋, 潘耀忠, 李京, 卓莉, 一之濑俊明. 2006. 基于DMSP/OLS夜间灯光数据和统计数据的中国大陆20世纪90年代城市化空间过程重建研究. 科学通报, 51(7): 856-861 [DOI: 10.3321/j.issn:0023-074X.2006.07.017http://dx.doi.org/10.3321/j.issn:0023-074X.2006.07.017]
Henderson J V, Storeygard A and Weil D N. 2012. Measuring economic growth from outer space. American Economic Review, 102(2): 994-1028 [DOI: 10.1257/aer.102.2.994http://dx.doi.org/10.1257/aer.102.2.994]
Henderson M, Yeh E T, Gong P, Elvidge C and Baugh K. 2003. Validation of urban boundaries derived from global night-time satellite imagery. International Journal of Remote Sensing, 24(3): 595-609 [DOI: 10.1080/01431160304982http://dx.doi.org/10.1080/01431160304982]
Hillger D, Seaman C, Liang C, Miller S, Lindsey D and Kopp T. 2014. Suomi NPP VIIRS imagery evaluation. Journal of Geophysical Research: Atmospheres, 119(11): 6440-6455 [DOI: 10.1002/2013jd021170http://dx.doi.org/10.1002/2013jd021170]
Hsu F C, Baugh K E, Ghosh T, Zhizhin M and Elvidge C D. 2015. DMSP-OLS radiance calibrated nighttime lights time series with intercalibration. Remote Sensing, 7(2): 1855-1876 [DOI: 10.3390/rs70201855http://dx.doi.org/10.3390/rs70201855]
Hsu F C, Elvidge C D and Matsuno Y. 2013. Exploring and estimating in-use steel stocks in civil engineering and buildings from night-time lights. International Journal of Remote Sensing, 34(2): 490-504 [DOI: 10.1080/01431161.2012.712232http://dx.doi.org/10.1080/01431161.2012.712232]
Hu D Y, Chen S S and Duan F Z. 2017a. Estimation of the anthropogenic heat flux distribution in beijing-tianjin-hebei region based on Suomi-NPP/VIIRS nighttime light image//Proceedings of 2017 IEEE International Geoscience and Remote Sensing Symposium. Fort Worth, TX, USA: IEEE: 4012-4015 [DOI: 10.1109/IGARSS.2017.8127880http://dx.doi.org/10.1109/IGARSS.2017.8127880]
Hu K J, Yang X C, Zhong J M, Fei F R and Qi J G. 2017b. Spatially explicit mapping of heat health risk utilizing environmental and socioeconomic data. Environmental Science and Technology, 51(3): 1498-1507 [DOI: 10.1021/acs.est.6b04355http://dx.doi.org/10.1021/acs.est.6b04355]
Hu S S, Ma S, Yan W, Lu W, and Zhao X B. 2018. Feasibility of a specialized ground light source for night-time low-light calibration. International Journal of Remote Sensing, 39(8): 2543-2559 [DOI: 10.1080/01431161.2018.1430915http://dx.doi.org/10.1080/01431161.2018.1430915]
Hu Y N, Peng J, Liu Y X, Du Y Y, Li H L and Wu J S. 2017c. Mapping development pattern in Beijing-Tianjin-Hebei urban agglomeration using DMSP/OLS nighttime light data. Remote Sensing, 9(7): 760 [DOI: 10.3390/rs9070760http://dx.doi.org/10.3390/rs9070760]
Huang R J, Zhang Y L, Bozzetti C, Ho K F, Cao J J, Han Y M, Daellenbach K R, Slowik J G, Platt S M, Canonaco F, Zotter P, Wolf R, Pieber S M, Bruns E A, Crippa M, Ciarelli G, Piazzalunga A, Schwikowski M, Abbaszade G, Schnelle-Kreis J, Zimmermann R, An Z S, Szidat S, Baltensperger U, Haddad I E and Prévôt A S H. 2014. High secondary aerosol contribution to particulate pollution during haze events in China. Nature, 514(7521): 218-222 [DOI: 10.1038/nature13774http://dx.doi.org/10.1038/nature13774]
Huang X, Hu T, Li J Y, Wang Q and Benediktsson J A. 2018. Mapping urban areas in China using multisource data with a novel ensemble SVM method. IEEE Transactions on Geoscience and Remote Sensing, 56(8): 4258-4273 [DOI: 10.1109/TGRS.2018.2805829http://dx.doi.org/10.1109/TGRS.2018.2805829]
Imhoff M L, Lawrence W T, Stutzer D C and Elvidge C D. 1997. A technique for using composite DMSP/OLS “city lights” satellite data to map urban area. Remote Sensing of Environment, 61(3): 361-370 [DOI: 10.1016/S0034-4257(97)00046-1http://dx.doi.org/10.1016/S0034-4257(97)00046-1]
Jean N, Burke M, Xie M, Davis W M, Lobell D B and Ermon S. 2016. Combining satellite imagery and machine learning to predict poverty. Science, 353(6301): 790-794 [DOI: 10.1126/science.aaf7894http://dx.doi.org/10.1126/science.aaf7894]
Jia T, Chen K and Wang J Y. 2017. Characterizing the growth patterns of 45 major metropolitans in mainland China using DMSP/OLS data. Remote Sensing, 9(6): 571 [DOI: 10.3390/rs9060571http://dx.doi.org/10.3390/rs9060571]
Jiang W, He G J, Long T F, Guo H X, Yin R Y, Leng W C, Liu H C and Wang G Z. 2018. Potentiality of using luojia 1-01 nighttime light imagery to investigate artificial light pollution. Sensors, 18(9): 2900 [DOI: 10.3390/s18092900http://dx.doi.org/10.3390/s18092900]
Jiang W, He G J, Long T F and Liu H C. 2017. Ongoing conflict makes Yemen dark: from the perspective of nighttime light. Remote Sensing, 9(8): 798 [DOI: 10.3390/rs9080798http://dx.doi.org/10.3390/rs9080798]
Jin M, Deng S Q, Yang C S, Yu B L and Wu J P. 2017. Multi-scale clustering analysis on Chinese urbans based on nighttime light image. Remote Sensing Technology and Application, 32(5): 973-982
金梦, 邓顺强, 杨成术, 余柏蒗, 吴健平. 2017. 基于夜间灯光遥感数据多尺度城市聚类分析. 遥感技术与应用, 32(5): 973-982 [DOI: 10.11873/j.issn.1004-0323.2017.5.0973http://dx.doi.org/10.11873/j.issn.1004-0323.2017.5.0973]
Jing W L, Yang Y P, Yue X F and Zhao X D. 2015. Mapping urban areas with integration of DMSP/OLS nighttime light and MODIS data using machine learning techniques. Remote Sensing, 7(9): 12419-12439 [DOI: 10.3390/rs70912419http://dx.doi.org/10.3390/rs70912419]
Katz Y and Levin N. 2016. Quantifying urban light pollution — A comparison between field measurements and EROS-B imagery. Remote Sensing of Environment, 177: 65-77 [DOI: 10.1016/j.rse.2016.02.017http://dx.doi.org/10.1016/j.rse.2016.02.017]
Keola S, Andersson M and Hall O. 2015. Monitoring economic development from space: using nighttime light and land cover data to measure economic growth. World Development, 66: 322-334 [DOI: 10.1016/j.worlddev.2014.08.017http://dx.doi.org/10.1016/j.worlddev.2014.08.017]
Kohiyama M, Hayashi H, Maki N, Higashida M, Kroehl H W, Elvidge C D and Hobson V R. 2004. Early damaged area estimation system using DMSP-OLS night-time imagery. International Journal of Remote Sensing, 25(11): 2015-2036 [DOI: 10.1080/01431160 310001595033http://dx.doi.org/10.1080/01431160310001595033]
Kumar P, Sajjad H, Joshi P K, Elvidge C D, Rehman S, Chaudhary, B S, Tripathy B R, Singh J and Pipal G. 2019. Modeling the luminous intensity of beijing, China using DMSP-OLS night-time lights series data for estimating population density. Physics and Chemistry of the Earth, Parts A/B/C, 109: 31-39 [DOI: 10.1016/j.pce.2018.06.002http://dx.doi.org/10.1016/j.pce.2018.06.002]
Kyba C C M, Garz S, Kuechly H, De Miguel A S, Zamorano J, Fischer J and Hölker F. 2015. High-resolution imagery of earth at night: new sources, opportunities and challenges. Remote Sensing, 7(1): 1-23 [DOI: 10.3390/rs70100001http://dx.doi.org/10.3390/rs70100001]
Lee S and Cao C Y. 2016. Soumi NPP VIIRS day/night band stray light characterization and correction using calibration view data. Remote Sensing, 8(2): 138 [DOI: 10.3390/rs8020138http://dx.doi.org/10.3390/rs8020138]
Letu H, Hara M, Yagi H, Naoki K, Tana G, Nishio F and Shuhei O. 2010. Estimating energy consumption from night-time DMPS/OLS imagery after correcting for saturation effects. International Journal of Remote Sensing, 31(16): 4443-4458 [DOI: 10.1080/01431160903277464http://dx.doi.org/10.1080/01431160903277464]
Levin N and Duke Y. 2012. High spatial resolution night-time light images for demographic and socio-economic studies. Remote Sensing of Environment, 119: 1-10 [DOI: 10.1016/j.rse.2011.12.005http://dx.doi.org/10.1016/j.rse.2011.12.005]
Levin N, Johansen K, Hacker J M and Phinn S. 2014. A new source for high spatial resolution night time images — the EROS-B commercial satellite. Remote Sensing of Environment, 149: 1-12 [DOI: 10.1016/j.rse.2014.03.019http://dx.doi.org/10.1016/j.rse.2014.03.019]
Li C S, Yang W N, Tang Q L, Tang X L, Lei J J, Wu M Y and Qiu S Y. 2020a. Detection of multidimensional poverty using luojia 1-01 nighttime light imagery. Journal of the Indian Society of Remote Sensing, 48(7): 963-977 [DOI: 10.1007/s12524-020-01126-3http://dx.doi.org/10.1007/s12524-020-01126-3]
Li D R, Zhang G, Shen X, Zhong X, Jiang Y H, Wang T Y, Tu J G and Li Z J. 2019. Design and processing night light remote sensing of LJ-1 01 satellite. Journal of Remote Sensing, 23(6): 1011-1022
李德仁, 张过, 沈欣, 钟兴, 蒋永华, 汪韬阳, 涂建光, 李治江. 2019. 珞珈一号01星夜光遥感设计与处理. 遥感学报, 23(6): 1011-1022 [DOI: 10.11834/jrs.20199327http://dx.doi.org/10.11834/jrs.20199327]
Li F, Yan Q W, Zou Y J and Liu B L. 2019. Improving the accuracy of built-up area extraction based on nighttime light data and poi: a case study of NPP/VIIRS and luojia 1-01 nighttime light images. Geomatics and Information Science of Wuhan University, 1-14
厉飞, 闫庆武, 邹雅婧, 刘保丽. 2019. 利用POI提高夜间灯光数据提取建成区的精度研究——以珞珈一号01星和NPP/VIIRS数据为例. 武汉大学学报(信息科学版), 1-14 [DOI: 10.13203/j.whugis20190266]
Li J. 2020. Spatial scope identification and characteristics analysis of urban agglomeration in mainland China. Acta Geodaetica et Cartographica Sinica, 49(3): 401
李佳. 2020. 中国大陆城市群空间范围识别及其特征分析. 测绘学报, 49(3): 401 [DOI: 10.11947/j.AGCS.2020.20190121http://dx.doi.org/10.11947/j.AGCS.2020.20190121]
Li Q X, Zheng H, Zhang G, Guo X Y and Liu W L. 2020. Analysis of luojia1-01 index based on nighttime light imagery. Journal of Geomatics, 45(3): 8-15
李黔湘, 郑晗, 张过, 郭雪瑶, 刘伟玲. 2020. 基于夜间灯光影像的珞珈一号指数分析. 测绘地理信息, 45(3): 8-15 [DOI: 10.14188/j.2095-6045.2020022http://dx.doi.org/10.14188/j.2095-6045.2020022]
Li W, Sun B D, Zhao J C and Zhang T L. 2018c. Economic performance of spatial structure in Chinese prefecture regions: evidence from night-time satellite imagery. Habitat International, 76: 29-39 [DOI: 10.1016/j.habitatint.2018.05.006http://dx.doi.org/10.1016/j.habitatint.2018.05.006]
Li X, Chen F R and Chen X L. 2013a. Satellite-observed nighttime light variation as evidence for global armed conflicts. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(5): 2302-2315 [DOI: 10.1109/JSTARS.2013.2241021http://dx.doi.org/10.1109/JSTARS.2013.2241021]
Li X and Li D R. 2014. Can night-time light images play a role in evaluating the Syrian Crisis? International Journal of Remote Sensing, 35(18): 6648-6661 [DOI: 10.1080/01431161.2014.971469http://dx.doi.org/10.1080/01431161.2014.971469]
Li X, Li D R, Xu H M and Wu C Q. 2017a. Intercalibration between DMSP/OLS and VIIRS night-time light images to evaluate city light dynamics of Syria’s major human settlement during Syrian Civil War. International Journal of Remote Sensing, 38(21): 5934-5951 [DOI: 10.1080/01431161.2017.1331476http://dx.doi.org/10.1080/01431161.2017.1331476]
Li X, Li X Y, Li D R, He X J and Jendryke M. 2019a. A preliminary investigation of Luojia-1 night-time light imagery. Remote Sensing Letters, 10(6): 526-535 [DOI: 10.1080/2150704X.2019.1577573http://dx.doi.org/10.1080/2150704X.2019.1577573]
Li X, Ma R Q, Zhang Q L, Li D R, Liu S S, He T and Zhao L X. 2019b. Anisotropic characteristic of artificial light at night – systematic investigation with VIIRS DNB multi-temporal observations. Remote Sensing of Environment, 233: 111357 [DOI: 10.1016/j.rse.2019.111357http://dx.doi.org/10.1016/j.rse.2019.111357]
Li X, Xu H M, Chen X L, and Li C. 2013b. Potential of NPP-VIIRS nighttime light imagery for modeling the regional economy of China. Remote Sensing, 5(6): 3057-3081 [DOI: 10.3390/rs506 3057http://dx.doi.org/10.3390/rs5063057]
Li X, Zhan C, Tao J B and Li L. 2018b. Long-term monitoring of the impacts of disaster on human activity using DMSP/OLS nighttime light data: a case study of the 2008 Wenchuan, China earthquake. Remote Sensing, 10(4): 588 [DOI: 10.3390/rs10040588http://dx.doi.org/10.3390/rs10040588]
Li X, Zhao L X, Li D R and Xu H M. 2018a. Mapping urban extent using luojia 1-01 nighttime light imagery. Sensors, 18(11): 3665 [DOI: 10.3390/s18113665http://dx.doi.org/10.3390/s18113665]
Li X, Zhu J, Yin X D, Yao J C, Huang J L and Li M T. 2019. Mapping construction land of Guangzhou based on luojia No.1 nightlight data. Journal of Geo-information Science, 21(11): 1802-1810
李翔, 朱江, 尹向东, 姚江春, 黄嘉玲, 李密滔. 2019. 基于珞珈一号夜间灯光数据的广州市建设用地识别. 地球信息科学学报, 21(11): 1802-1810 [DOI: 10.12082/dqxxkx.2019.190041http://dx.doi.org/10.12082/dqxxkx.2019.190041]
Li X C, Zhou Y Y, Zhao M and Zhao X. 2020b. A harmonized global nighttime light dataset 1992-2018. Scientific Data, 7(1): 168 [DOI: 10.1038/s41597-020-0510-yhttp://dx.doi.org/10.1038/s41597-020-0510-y]
Li X K, Zhang C R, Li W D and Liu K. 2017b. Evaluating the use of DMSP/OLS nighttime light imagery in predicting PM2.5 concentrations in the northeastern united states. Remote Sensing, 9(6): 620 [DOI: 10.3390/rs9060620http://dx.doi.org/10.3390/rs9060620]
Liang L, Bian J H, Li A N, Feng W L, Lei G B, Zhang Z J and Zuo J Q. 2020. Consistent intercalibration of nighttime light data between DMSP/OLS and NPP/VIIRS in the China-Pakistan economic corridor. Journal of Remote Sensing, 24(2): 149-160
梁丽, 边金虎, 李爱农, 冯文兰, 雷光斌, 张正健, 左家旗. 2020. 中巴经济走廊DMSP/OLS与NPP/VIIRS夜光数据辐射一致性校正. 遥感学报, 24(2): 149-160 [DOI: 10.11834/jrs.20208241http://dx.doi.org/10.11834/jrs.20208241]
Liang Z, Huang J, Wei F L, Shen J S and Li S C. 2020. Identifying the spatial range of urban agglomerations in China based on night light remote sensing and POI data. Geographical Research, 39(1): 92-102
梁泽, 黄姣, 韦飞黎, 申嘉澍, 李双成. 2020. 基于夜光遥感影像与百度POI数据的中国城市群空间范围识别方法. 地理研究, 39(1): 92-102 [DOI: 10.11821/dlyj020181002http://dx.doi.org/10.11821/dlyj020181002]
Liao L B, Weiss S, Mills S and Hauss B. 2013. Suomi NPP VIIRS day-night band on-orbit performance. Journal of Geophysical Research: Atmospheres, 118(22): 12705-12718 [DOI: 10.1002/2013jd020475http://dx.doi.org/10.1002/2013jd020475]
Liu C, Yang K, Bennett M M, Guo Z Y, Cheng L and Li M C. 2019a. Automated extraction of built-up areas by fusing VIIRS nighttime lights and landsat-8 data. Remote Sensing, 11(13): 1571 [DOI: 10.3390/rs11131571http://dx.doi.org/10.3390/rs11131571]
Liu Q, Sha D X, Liu W, Houser P, Zhang L Y, Hou R Z, Lan H, Flynn C, Lu M Y, Hu T and Yang C W. 2020. Spatiotemporal patterns of COVID-19 impact on human activities and environment in mainland China using nighttime light and air quality data. Remote Sensing, 12(10): 1576 [DOI: 10.3390/rs12101576http://dx.doi.org/10.3390/rs12101576]
Liu Q Y, Zhan Q M, Li J S, Yang C and Liu W. 2019. Extracting built-up areas using luojia 1-01 nighttime light imageries in Wuhan, China. Geomatics and Information Science of Wuhan University, 1-18
刘权毅, 詹庆明, 李建松, 杨晨, 刘稳. 2019. 珞珈一号夜间灯光影像在建设用地提取中的应用: 以武汉市为例. 武汉大学学报(信息科学版), 1-18 [DOI: 10.13203/j.whugis20190376]
Liu S S, Li X, Levin N and Jendryke M. 2019b. Tracing cultural festival patterns using time-series of VIIRS monthly products. Remote Sensing Letters, 10(12):1172-1181 [DOI: 10.1080/2150704x.2019.1666313http://dx.doi.org/10.1080/2150704x.2019.1666313]
Liu X, De Sherbinin A and Zhan Y N. 2019c. Mapping urban extent at large spatial scales using machine learning methods with VIIRS nighttime light and MODIS daytime NDVI data. Remote Sensing, 11(10): 1247 [DOI: 10.3390/rs11101247http://dx.doi.org/10.3390/rs11101247]
Liu X P, Ou J P, Wang S J, Li X, Yan Y C, Jiao L M and Liu Y L. 2018. Estimating spatiotemporal variations of city-level energy-related CO2 emissions: an improved disaggregating model based on vegetation adjusted nighttime light data. Journal of Cleaner Production, 177: 101-114 [DOI: 10.1016/j.jclepro.2017.12.197http://dx.doi.org/10.1016/j.jclepro.2017.12.197]
Liu Y and Li Y C. 2019. Urban centers extraction and analysis using night time light date: a case study of main urban areas of Chongqing. China Resources Comprehensive Utilization, 37(3): 160-164
刘源, 李月臣. 2019. 基于夜间灯光数据的城市中心区域提取与分析——以重庆市主城区为例. 中国资源综合利用, 37(3): 160-164 [DOI: 10.3969/j.issn.1008-9500.2019.03.050http://dx.doi.org/10.3969/j.issn.1008-9500.2019.03.050]
Liu Z F, He C Y, Zhang Q F, Huang Q X and Yang Y. 2012. Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008. Landscape and Urban Planning, 106(1): 62-72 [DOI: 10.1016/j.landurbplan.2012.02.013http://dx.doi.org/10.1016/j.landurbplan.2012.02.013]
Lo C P. 2002. Urban indicators of China from radiance-calibrated digital DMSP-OLS nighttime images. Annals of the Association of American Geographers, 92(2): 225-240 [DOI: 10.1111/1467-8306.00288http://dx.doi.org/10.1111/1467-8306.00288]
Lu H M, Zhang M L, Sun W W and Li W Y. 2018. Expansion analysis of Yangtze River delta urban agglomeration using DMSP/OLS nighttime light imagery for 1993 to 2012. ISPRS International Journal of Geo-Information, 7(2): 52 [DOI: 10.3390/ijgi7020052http://dx.doi.org/10.3390/ijgi7020052]
Luo Q and Li X J. 2019. The spatial differentiation and influencing factors of urban centers in China based on VIIRS night light. Geographical Research, 38(1): 155-166
罗庆, 李小建. 2019. 基于VIIRS夜间灯光的中国城市中心的分异特征及其影响因素. 地理研究, 38(1): 155-166 [DOI: 10.11821/dlyj020180467http://dx.doi.org/10.11821/dlyj020180467]
Ma J J, Guo J Y, Ahmad S, Li Z Q and Hong J. 2020. Constructing a new inter-calibration method for DMSP-OLS and NPP-VIIRS nighttime light. Remote Sensing, 12(6): 937. [DOI: 10.3390/rs12060937http://dx.doi.org/10.3390/rs12060937]
Ma T, Zhou C H, Pei T, Haynie S and Fan J F. 2012. Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data: a comparative case study from China's cities. Remote Sensing of Environment, 124: 99-107 [DOI: 10.1016/j.rse.2012.04.018http://dx.doi.org/10.1016/j.rse.2012.04.018]
Mao S Y, Jiao L M, Xu G and Li Z H. 2019. Identification of the polycentric spatial structure in Wuhan City based on multisource data. Progress in Geography, 38(11): 1675-1683
毛帅永, 焦利民, 许刚, 李泽慧. 2019. 基于多源数据的武汉市多中心空间结构识别. 地理科学进展, 38(11): 1675-1683 [DOI: 10.18306/dlkxjz.2019.11.003http://dx.doi.org/10.18306/dlkxjz.2019.11.003]
Miller S D, Mills S P, Elvidge C D, Lindsey D T, Lee T F and Hawkins J D. 2012. Suomi satellite brings to light a unique frontier of nighttime environmental sensing capabilities. Proceedings of the National Academy of Sciences of the United States of America, 109(39): 15706-15711 [DOI: 10.1073/pnas.1207034109http://dx.doi.org/10.1073/pnas.1207034109]
Miller S D and Turner R E. 2009. A dynamic lunar spectral irradiance data set for NPOESS/VIIRS Day/Night band nighttime environmental applications. IEEE Transactions on Geoscience and Remote Sensing, 47(7): 2316-2329 [DOI: 10.1109/TGRS.2009.20 12696http://dx.doi.org/10.1109/TGRS.2009.2012696]
Mills S, Weiss S and Liang C. 2013. VIIRS day/night band (DNB) stray light characterization and correction//Proceedings of SPIE Earth Observing Systems XVIII. San Diego, California, United States: SPIE, 8866: 88661P [DOI: 10.1117/12.2023107http://dx.doi.org/10.1117/12.2023107]
Molthan A and Jedlovec G. 2013. Satellite observations monitor outages from superstorm sandy. Eos, Transactions, American Geophysical Union, 94(5): 53-54 [DOI: 10.1002/2013EO050001http://dx.doi.org/10.1002/2013EO050001]
Ou J P, Liu X P, Li X and Shi X. 2016. Mapping global fossil fuel combustion CO2 emissions at high resolution by integrating nightlight, population density, and traffic network data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(4): 1674-1684 [DOI: 10.1109/JSTARS.2015.2476347http://dx.doi.org/10.1109/JSTARS.2015.2476347]
Ou J P, Liu X P, Liu P H and Liu X J. 2019. Evaluation of luojia 1-01 nighttime light imagery for impervious surface detection: a comparison with NPP-VIIRS nighttime light data. International Journal of Applied Earth Observation and Geoinformation, 81: 1-12 [DOI: 10.1016/j.jag.2019.04.017http://dx.doi.org/10.1016/j.jag.2019.04.017]
Pack D W, Hardy B S and Longcore T. 2017. Studying the earth at night from CubeSats//Proceedings of the 31st Annual AIAA/USU Conference on Small Satellites. Logan, Utah, United States: AIAA, USU
Peng J, Lin H X, Chen Y Q, Blaschke T, Luo L W, Xu Z H, Hu Y N, Zhao M Y and Wu J S. 2020. Spatiotemporal evolution of urban agglomerations in China during 2000-2012: a nighttime light approach. Landscape Ecology, 35(2): 421-434 [DOI: 10.1007/s10980-019-00956-yhttp://dx.doi.org/10.1007/s10980-019-00956-y]
Qiang Y, Huang Q X and Xu J W. 2020. Observing community resilience from space: using nighttime lights to model economic disturbance and recovery pattern in natural disaster. Sustainable Cities and Society, 57: 102115 [DOI: 10.1016/j.scs.2020.102115http://dx.doi.org/10.1016/j.scs.2020.102115]
Rashed T and Jürgens C. 2010. Remote Sensing of Urban and Suburban Areas. Dordrecht: Springer [DOI: 10.1007/978-1-4020-43 85-7http://dx.doi.org/10.1007/978-1-4020-4385-7]
Román M O and Stokes E C. 2015. Holidays in lights: tracking cultural patterns in demand for energy services. Earth’s Future, 3(6): 182-205 [DOI: 10.1002/2014ef000285http://dx.doi.org/10.1002/2014ef000285]
Sen A, Kim Y J, Caruso D, Lagerloef G, Colomb R, Yueh S and Le Vine D. 2006. Aquarius/SAC-D mission overview//Proceedings of SPIE Sensors, Systems, and Next-Generation Satellites X. Stockholm, Sweden: SPIE, 6361: 63610I [DOI: 10.1117/12.691981http://dx.doi.org/10.1117/12.691981]
Shao X, Cao C Y, Zhang B, Qiu S, Elvidge C and Von Hendy M. 2014. Radiometric calibration of DMSP-OLS sensor using VIIRS day/night band//Proceedings of SPIE Earth Observing Missions and Sensors: Development, Implementation, and Characterization III. Beijing, China: SPIE: 92640A [DOI: 10.1117/12.2068999http://dx.doi.org/10.1117/12.2068999]
Sharma R C, Tateishi R, Hara K, Gharechelou S and Iizuka K. 2016. Global mapping of urban built-up areas of year 2014 by combining MODIS multispectral data with VIIRS nighttime light data. International Journal of Digital Earth, 9(10): 1004-1020 [DOI: 10.1080/17538947.2016.1168879http://dx.doi.org/10.1080/17538947.2016.1168879]
Shi K F, Chang Z J, Chen Z Q, Wu J P and Yu B L. 2020. Identifying and evaluating poverty using multisource remote sensing and point of interest (POI) data: a case study of Chongqing, China. Journal of Cleaner Production, 255: 120245 [DOI: 10.1016/j.jclepro.2020.120245http://dx.doi.org/10.1016/j.jclepro.2020.120245]
Shi K F, Chen Y, Yu B L, Xu T B, Chen Z Q, Liu R, Li L Y and Wu J P. 2016a. Modeling spatiotemporal CO2 (carbon dioxide) emission dynamics in China from DMSP-OLS nighttime stable light data using panel data analysis. Applied Energy, 168: 523-533 [DOI: 10.1016/j.apenergy.2015.11.055http://dx.doi.org/10.1016/j.apenergy.2015.11.055]
Shi K F, Chen Y, Yu B L, Xu T B, Yang C S, Li L Y, Huang C, Chen Z Q, Liu R and Wu J P. 2016b. Detecting spatiotemporal dynamics of global electric power consumption using DMSP-OLS nighttime stable light data. Applied Energy, 184: 450-463 [DOI: 10.1016/j.apenergy.2016.10.032http://dx.doi.org/10.1016/j.apenergy.2016.10.032]
Shi K F, Huang C, Yu B L, Yin B, Huang Y X and Wu J P. 2014a. Evaluation of NPP-VIIRS night-time light composite data for extracting built-up urban areas. Remote Sensing Letters, 5(4): 358-366 [DOI: 10.1080/2150704X.2014.905728http://dx.doi.org/10.1080/2150704X.2014.905728]
Shi K F, Yu B L, Hu Y J, Huang C, Chen Y, Huang Y X, Chen Z Q and Wu J P. 2015. Modeling and mapping total freight traffic in China using NPP-VIIRS nighttime light composite data. GIScience and Remote Sensing, 52(3): 274-289 [DOI: 10.1080/15481603.2015.1022420http://dx.doi.org/10.1080/15481603.2015.1022420]
Shi K F, Yu B L, Huang C, Wu J P and Sun X F. 2018. Exploring spatiotemporal patterns of electric power consumption in countries along the belt and road. Energy, 150: 847-859 [DOI: 10.1016/j.energy.2018.03.020http://dx.doi.org/10.1016/j.energy.2018.03.020]
Shi K F, Yu B L, Huang Y X, Hu Y J, Yin B, Chen Z Q, Chen L J and Wu J P. 2014b. Evaluating the ability of NPP-VIIRS nighttime light data to estimate the gross domestic product and the electric power consumption of China at multiple scales: a comparison with DMSP-OLS data. Remote Sensing, 6(2): 1705-1724 [DOI: 10.3390/rs6021705http://dx.doi.org/10.3390/rs6021705]
Shu S, Yu B L, Wu J P and Liu H X. 2011. Methods for deriving urban built-up area using night-light data: assessment and application. Remote Sensing Technology and Application, 26(2): 169-176
舒松, 余柏蒗, 吴健平, 刘红星. 2011. 基于夜间灯光数据的城市建成区提取方法评价与应用. 遥感技术与应用, 26(2): 169-176 [DOI: 10.11873/j.issn.1004-0323.2011.2.169http://dx.doi.org/10.11873/j.issn.1004-0323.2011.2.169]
Small C. 2019. Multisensor characterization of urban morphology and network structure. Remote Sensing, 11(18): 2162 [DOI: 10.3390/rs11182162http://dx.doi.org/10.3390/rs11182162]
Small C and Elvidge C D. 2013. Night on earth: mapping decadal changes of anthropogenic night light in Asia. International Journal of Applied Earth Observation and Geoinformation, 22: 40-52 [DOI: 10.1016/j.jag.2012.02.009http://dx.doi.org/10.1016/j.jag.2012.02.009]
Small C, Pozzi F and Elvidge C D. 2005. Spatial analysis of global urban extent from DMSP-OLS night lights. Remote Sensing of Environment, 96(3/4): 277-291 [DOI: 10.1016/j.rse.2005.02.002http://dx.doi.org/10.1016/j.rse.2005.02.002]
Su Y X, Chen X Z, Ye Y Y, Wu Q T, Zhang H O, Huang N S and Kuang Y Q. 2013. The characteristics and mechanisms of carbon emissions from energy consumption in China using DMSP/OLS night light imageries. Acta Geographica Sinica, 68(11): 1513-1526
苏泳娴, 陈修治, 叶玉瑶, 吴旗韬, 张虹鸥, 黄宁生, 匡耀求. 2013. 基于夜间灯光数据的中国能源消费碳排放特征及机理. 地理学报, 68(11): 1513-1526 [DOI: 10.11821/dlxb20131 1007http://dx.doi.org/10.11821/dlxb201311007]
Sutton P, Roberts D, Elvidge C and Melj H. 1997. A comparison of nighttime satellite imagery and population density for the continental United States. Photogrammetric Engineering and Remote Sensing, 63(11): 1303-1313
Sutton P C and Costanza R. 2002. Global estimates of market and non-market values derived from nighttime satellite imagery, land cover, and ecosystem service valuation. Ecological Economics, 41(3): 509-527 [DOI: 10.1016/S0921-8009(02)00097-6http://dx.doi.org/10.1016/S0921-8009(02)00097-6]
Tan Z R, Wei D L and Yin Z X. 2020. Housing vacancy rate in major cities in China: perspectives from nighttime light data. Complexity, 2020: 1-12 [DOI: 10.1155/2020/5104578http://dx.doi.org/10.1155/2020/5104578]
Tripathy B R, Tiwari V, Pandey V, Elvidge C D, Rawat J S, Sharma M P, Prawasi R and Kumar P. 2017. Estimation of urban population dynamics using DMSP-OLS night-time lights time series sensors data. IEEE Sensors Journal, 17(4): 1013-1020 [DOI: 10.1109/JSEN.2016.2640181http://dx.doi.org/10.1109/JSEN.2016.2640181]
UN-DESA (United Nations, Department of Economic and Social Affairs, Population Division). 2019. World Urbanization Prospects: The 2018 Revision. New York: United Nations
Wang C X, Chen Z Q, Yang C S, Li Q X, Wu Q S, Wu J P, Zhang G and Yu B L. 2020a. Analyzing parcel-level relationships between luojia 1-01 nighttime light intensity and artificial surface features across Shanghai, China: a comparison with NPP-VIIRS data. International Journal of Applied Earth Observation and Geoinformation, 85: 101989 [DOI: 10.1016/j.jag.2019.101989http://dx.doi.org/10.1016/j.jag.2019.101989]
Wang J, Aegerter C, Xu X G and Szykman J J. 2016. Potential application of VIIRS day/night band for monitoring nighttime surface PM2.5 air quality from space. Atmospheric Environment, 124: 55-63 [DOI: 10.1016/j.atmosenv.2015.11.013http://dx.doi.org/10.1016/j.atmosenv.2015.11.013]
Wang L W and Feng C C. 2016. Spatial expansion pattern and its driving dynamics of Beijing-Tianjin-Hebei metropolitan region: based on nighttime light data. Acta Geographica Sinica, 71(12): 2155-2169
王利伟, 冯长春. 2016. 转型期京津冀城市群空间扩展格局及其动力机制——基于夜间灯光数据方法. 地理学报, 71(12): 2155-2169 [DOI: 10.11821/dlxb201612007http://dx.doi.org/10.11821/dlxb201612007]
Wang L Y, Fan H and Wang Y K. 2020b. Improving population mapping using luojia 1-01 nighttime light image and location-based social media data. Science of the Total Environment, 730: 139148 [DOI: 10.1016/j.scitotenv.2020.139148http://dx.doi.org/10.1016/j.scitotenv.2020.139148]
Wang W, Cheng H and Zhang L. 2012. Poverty assessment using DMSP/OLS night-time light satellite imagery at a provincial scale in China. Advances in Space Research, 49(8): 1253-1264 [DOI: 10.1016/j.asr.2012.01.025http://dx.doi.org/10.1016/j.asr.2012.01.025]
Wang X J, Mu X H and Yan G J. 2020c. Quantitative analysis of aerosol influence on Suomi-NPP VIIRS nighttime light in China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13: 3557-3568 [DOI: 10.1109/jstars.2020.3003480http://dx.doi.org/10.1109/jstars.2020.3003480]
Wang Z, Román M O, Sun Q, Molthan A L, Schultz L A and Kalb V L. 2018. Monitoring disaster-related power outages using NASA black marble nighttime light product//Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, ISPRS TC III Mid-term Symposium “Developments, Technologies and Applications in Remote Sensing. Beijing: [s.
n.]: 1853-1856 [DOI: 10.5194/isprs-archives-XLII-3-1853-2018http://dx.doi.org/10.5194/isprs-archives-XLII-3-1853-2018]
Wei Y, Liu H X, Song W, Yu B L and Xiu C L. 2014. Normalization of time series DMSP-OLS nighttime light images for urban growth analysis with pseudo invariant features. Landscape and Urban Planning, 128: 1-13 [DOI: 10.1016/j.landurbplan.2014.04.015http://dx.doi.org/10.1016/j.landurbplan.2014.04.015]
Welch R. 1980. Monitoring urban population and energy utilization patterns from satellite data. Remote Sensing of Environment, 9(1): 1-9 [DOI: 10.1016/0034-4257(80)90043-7http://dx.doi.org/10.1016/0034-4257(80)90043-7]
Wigginton N S, Fahrenkamp-Uppenbrink J, Wible B and Malakoff D. 2016. Cities are the future. Science, 352(6288): 904-905 [DOI: 10.1126/science.352.6288.904http://dx.doi.org/10.1126/science.352.6288.904]
Witmer F D W and O'Loughlin J. 2011. Detecting the effects of wars in the caucasus regions of russia and georgia using radiometrically normalized DMSP-OLS nighttime lights imagery. GIScience and Remote Sensing, 48(4): 478-500 [DOI: 10.2747/1548-1603.48.4.478http://dx.doi.org/10.2747/1548-1603.48.4.478]
Wu B, Yu B L, Yao S J, Wu Q S, Chen Z Q and Wu J P. 2019. A surface network based method for studying urban hierarchies by night time light remote sensing data. International Journal of Geographical Information Science, 33(7): 1377-1398 [DOI: 10.1080/13658816.2019.1585540http://dx.doi.org/10.1080/13658816.2019.1585540]
Wu J D, Li Y, Li N and Shi P J. 2018. Development of an asset value map for disaster risk assessment in China by spatial disaggregation using ancillary remote sensing data. Risk Analysis, 38(1): 17-30 [DOI: 10.1111/risa.12806http://dx.doi.org/10.1111/risa.12806]
Wu J S, Liu H, Peng J and Ma L. 2014. Hierarchical structure and spatial pattern of China's urban system: evidence from DMSP/OLS nightlight data. Acta Geographica Sinica, 69(6): 759-770
吴健生, 刘浩, 彭建, 马琳. 2014. 中国城市体系等级结构及其空间格局——基于DMSP/OLS夜间灯光数据的实证. 地理学报, 69(6): 759-770 [DOI: 10.11821/dlxb201406004http://dx.doi.org/10.11821/dlxb201406004]
Wu J S, Xu D, Xie W D and Peng J. 2015. Spatialization of demographic data at medium scale based on remote sensing images: regarding Beijing-Tianjin-Hebei as an example. Acta Scientiarum Naturalium Universitatis Pekinensis, 51(4): 707-717
吴健生, 许多, 谢舞丹, 彭建. 2015. 基于遥感影像的中尺度人口统计数据空间化——以京津冀地区为例. 北京大学学报(自然科学版), 51(4): 707-717 [DOI: 10.13209/j.0479-8023.2015.100http://dx.doi.org/10.13209/j.0479-8023.2015.100]
Xie Y H and Weng Q H. 2016. Updating urban extents with nighttime light imagery by using an object-based thresholding method. Remote Sensing of Environment, 187: 1-13 [DOI: 10.1016/j.rse.20 16.10.002http://dx.doi.org/10.1016/j.rse.2016.10.002]
Yang X C, Yue W Z and Gao D W. 2013. Spatial improvement of human population distribution based on multi-sensor remote-sensing data: an input for exposure assessment. International Journal of Remote Sensing, 34(15): 5569-5583 [DOI: 10.1080/01431161.2013.792970http://dx.doi.org/10.1080/01431161.2013.792970]
Yao Y L and Li Y. 2011. House vacancy at urban areas in China with nocturnal light data of DMSP-OLS//Proceedings of 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services. Fuzhou, China: IEEE: 457-462 [DOI: 10.1109/ICSDM.2011.5969087http://dx.doi.org/10.1109/ICSDM.2011.5969087]
Yin Z M, Li X, Tong F, Li Z B and Jendryke M. 2019. Mapping urban expansion using night-time light images from luojia1-01 and international space station. International Journal of Remote Sensing, 41(7): 2603-2623 [DOI: 10.1080/01431161.2019.1693661http://dx.doi.org/10.1080/01431161.2019.1693661]
Yu B L, Deng S Q, Liu G, Yang C S, Chen Z Q, Hill C J and Wu J P. 2018c. Nighttime light images reveal spatial-temporal dynamics of global anthropogenic resources accumulation above ground. Environmental Science and Technology, 52(20):11520-11527 [DOI: 10.1021/acs.est.8b02838http://dx.doi.org/10.1021/acs.est.8b02838]
Yu B L, Lian T, Huang Y X, Yao S J, Ye X Y, Chen Z Q, Yang C S and Wu J P. 2018b. Integration of nighttime light remote sensing images and taxi GPS tracking data for population surface enhancement. International Journal of Geographical Information Science, 33(4): 687-706 [DOI: 10.1080/13658816.2018.1555642http://dx.doi.org/10.1080/13658816.2018.1555642]
Yu B L, Shi K F, Hu Y J, Huang C, Chen Z Q and Wu J P. 2015. Poverty evaluation using NPP-VIIRS nighttime light composite data at the county level in China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(3): 1217-1229 [DOI: 10.1109/JSTARS.2015.2399416http://dx.doi.org/10.1109/JSTARS.2015.2399416]
Yu B L, Shu S, Liu H X, Song W, Wu J P, Wang L and Chen Z Q. 2014. Object-based spatial cluster analysis of urban landscape pattern using nighttime light satellite images: a case study of China. International Journal of Geographical Information Science, 28(11): 2328-2355 [DOI: 10.1080/13658816.2014.922186http://dx.doi.org/10.1080/13658816.2014.922186]
Yu B L, Tang M, Wu Q S, Yang C S, Deng S Q, Shi K F, Peng C, Wu J P and Chen Z Q, 2018a. Urban built-up area extraction from log-transformed NPP-VIIRS nighttime light composite data. IEEE Geoscience and Remote Sensing Letters, 15(8): 1279-1283 [DOI: 10.1109/lgrs.2018.2830797http://dx.doi.org/10.1109/lgrs.2018.2830797]
Yue W Z, Qiu S S, Xu H, Xu L H and Zhang L L. 2019. Polycentric urban development and urban thermal environment: a case of Hangzhou, China. Landscape and Urban Planning, 189: 58-70 [DOI: 10.1016/j.landurbplan.2019.04.008http://dx.doi.org/10.1016/j.landurbplan.2019.04.008]
Zeng C Q, Zhou Y, Wang S X, Yan F L and Zhao Q. 2011. Population spatialization in China based on night-time imagery and land use data. International Journal of Remote Sensing, 32(24): 9599-9620 [DOI: 10.1080/01431161.2011.569581http://dx.doi.org/10.1080/01431161.2011.569581]
Zhang B J. 2018. Analysis of the inter-annual variation of nighttime lights in the most affected area of wenchuan earthquake from 2003 to 2013. Journal of Catastrophology, 33(1): 12-18, 22 (张宝军. 2018. 2003-2013年汶川地震极重灾区夜间灯光年际变化分析. 灾害学. 33(1): 12-18, 22) [DOI: 10.3969/j.issn.1000-811X.2018.01.003http://dx.doi.org/10.3969/j.issn.1000-811X.2018.01.003]
Zhang G, Li L T, Jiang Y H, Shen X and Li D R. 2018. On-orbit relative radiometric calibration of the night-time sensor of the luoJia1-01 satellite. Sensors, 18(12): 4225 [DOI: 10.3390/s18124225http://dx.doi.org/10.3390/s18124225]
Zhang G, Shi Y R and Xu M Z. 2020. Evaluation of LJ1-01 nighttime light imagery for estimating monthly PM2.5 concentration: a comparison with NPP-VIIRS nighttime light data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13: 3618-3632 [DOI: 10.1109/JSTARS.2020.3002671http://dx.doi.org/10.1109/JSTARS.2020.3002671]
Zhang Q W and 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.2016.10.003http://dx.doi.org/10.1016/j.habitatint.2016.10.003]
Zhang Y X, Li X, Song Y and Li C H. 2020. Urban spatial form analysis of GBA based on "LJ1-01" nighttime light remote sensing images. Journal of Applied Sciences, 38(3): 466-477
张雨欣, 李熙, 宋杨, 李长辉. 2020. 基于“珞珈一号”夜光遥感影像的粤港澳大湾区城市空间形态分析. 应用科学学报, 38(3): 466-477 [DOI: 10.3969/j.issn.0255-8297.2020.03.012http://dx.doi.org/10.3969/j.issn.0255-8297.2020.03.012]
Zhao J C, Zhong Z Q, Lu H L, Wu L Y and Chen Y L. 2017. Urban residential CO2 emissions and its determinants: a case study of central plains economic region. Journal of Natural Resources, 32(12): 2100-2114
赵金彩, 钟章奇, 卢鹤立, 吴乐英, 陈玉龙. 2017. 基于夜间灯光的城市居民直接碳排放及影响因素——以中原经济区为例. 自然资源学报, 32(12): 2100-2114 [DOI: 10.11849/zrzyxb.20161068http://dx.doi.org/10.11849/zrzyxb.20161068]
Zhao M, Zhou Y Y, Li X C, Cao W T, He C Y, Yu B L, Li X, Elvidge C D, Cheng W M and Zhou C H. 2019a. Applications of satellite remote sensing of nighttime light observations: advances, challenges, and perspectives. Remote Sensing, 11(17): 1971 [DOI: 10.3390/rs11171971http://dx.doi.org/10.3390/rs11171971]
Zhao M, Zhou Y Y, Li X C, Cheng W M, Zhou C H, Ma T, Li M C and Huang K. 2020b. Mapping urban dynamics (1992-2018) in southeast Asia using consistent nighttime light data from DMSP and VIIRS. Remote Sensing of Environment, 248: 111980 [DOI: 10.1016/j.rse.2020.111980http://dx.doi.org/10.1016/j.rse.2020.111980]
Zhao M, Zhou Y Y, Li X C, Zhou C H, Cheng W M, Li M C and Huang K. 2020a. Building a series of consistent night-time light data (1992-2018) in southeast Asia by integrating DMSP-OLS and NPP-VIIRS. IEEE Transactions on Geoscience and Remote Sensing, 58(3): 1843-1856 [DOI: 10.1109/TGRS.2019.2949797http://dx.doi.org/10.1109/TGRS.2019.2949797]
Zhao N Z, Hsu F C, Cao G F and Samson E L. 2017. Improving accuracy of economic estimations with VIIRS DNB image products. International Journal of Remote Sensing, 38(21): 5899-5918 [DOI: 10.1080/01431161.2017.1331060http://dx.doi.org/10.1080/01431161.2017.1331060]
Zhao X Z, Yu B L, Liu Y, Chen Z Q, Li Q X, Wang C X and Wu J P. 2019b. Estimation of poverty using random forest regression with multi-source data: a case study in Bangladesh. Remote Sensing, 11(4): 375 [DOI: 10.3390/rs11040375http://dx.doi.org/10.3390/rs11040375]
Zhao X Z, Yu B L, Liu Y, Yao S J, Lian T, Chen L J, Yang C S, Chen Z Q and Wu J P. 2018. NPP-VIIRS DNB daily data in natural disaster assessment: evidence from selected case studies. Remote Sensing, 10(10): 1526 [DOI: 10.3390/rs10101526http://dx.doi.org/10.3390/rs10101526]
Zhao Z Z, Cheng G, Wang C, Wang S T and Wang H T. 2020c. City grade classification based on connectivity analysis by luojia I night-time light images in Henan Province, China. Remote Sensing, 12(11): 1705 [DOI: 10.3390/rs12111705http://dx.doi.org/10.3390/rs12111705]
Zheng Q M, Weng Q H, Huang L Y, Wang K, Deng J S, Jiang R W, Ye Z R and Gan M Y. 2018. A new source of multi-spectral high spatial resolution night-time light imagery—JL1-3B. Remote Sensing of Environment, 215: 300-312 [DOI: 10.1016/j.rse.2018.06.016http://dx.doi.org/10.1016/j.rse.2018.06.016]
Zheng Q M, Weng Q H and Wang K. 2019a. Developing a new cross-sensor calibration model for DMSP-OLS and Suomi-NPP VIIRS night-light imageries. ISPRS Journal of Photogrammetry and Remote Sensing, 153: 36-47 [DOI: 10.1016/j.isprsjprs.2019.04.019http://dx.doi.org/10.1016/j.isprsjprs.2019.04.019]
Zheng Y M, Shao G F, Tang L N, He Y R, Wang X R, Wang Y N and Wang H W. 2019b. Rapid assessment of a typhoon disaster based on NPP-VIIRS DNB daily data: the case of an urban agglomeration along Western Taiwan Straits, China. Remote Sensing, 11(14): 1709 [DOI: 10.3390/rs11141709http://dx.doi.org/10.3390/rs11141709]
Zheng Z H, Chen Y B, Wu Z F and Zhang Q F. 2018. Method to reduce saturation of DMSP/OLS nighttime light data based on UNL. Journal of Remote Sensing, 22(1): 161-173
郑子豪, 陈颖彪, 吴志峰, 张棋斐. 2018. 单元路网长度的DMSP/OLS夜间灯光数据去饱和方法. 遥感学报, 22(1): 161-173 [DOI: 10.11834/jrs.20186478http://dx.doi.org/10.11834/jrs.20186478]
Zhong L and Liu X S. 2019. Application potential analysis of LJ1-01 new nighttime light data. Bulletin of Surveying and Mapping, (7): 132-137 (钟亮, 刘小生. 2019. 珞珈一号新型夜间灯光数据应用潜力分析. 测绘通报, (7): 132-137) [DOI: 10.13474/j.cnki.11-2246.2019.0235]
Zhou C S and Ye C D. 2013. Progress on studies of urban spatial structure in China. Progress in Geography, 32(7): 1030-1038
周春山, 叶昌东. 2013. 中国城市空间结构研究评述. 地理科学进展, 32(7): 1030-1038 [DOI: 10.11820/dlkxjz.2013.07.006http://dx.doi.org/10.11820/dlkxjz.2013.07.006]
Zhou L, Zhao Q and Yang F. 2019. Identification of urban agglomeration boundary based on POI and NPP/VIIRS night light data. Progress in Geography, 38(6): 840-850
周亮, 赵琪, 杨帆. 2019. 基于POI与NPP/VIIRS灯光数据的城市群边界定量识别. 地理科学进展, 38(6): 840-850 [DOI: 10.18306/dlkxjz.2019.06.005http://dx.doi.org/10.18306/dlkxjz.2019.06.005]
Zhou Y Y, Smith S J, Elvidge C D, Zhao K G, Thomson A and Imhoff M. 2014. A cluster-based method to map urban area from DMSP/OLS nightlights. Remote Sensing of Environment, 147: 173-185 [DOI: 10.1016/j.rse.2014.03.004http://dx.doi.org/10.1016/j.rse.2014.03.004]
Zhou Y Y, Smith S J, Zhao K G, Imhoff M, Thomson A, Bond-Lamberty B, Asrar G R, Zhang X S, He C Y and Elvidge C D. 2015. A global map of urban extent from nightlights. Environmental Research Letters, 10(5): 054011 [DOI: 10.1088/1748-9326/10/5/054011http://dx.doi.org/10.1088/1748-9326/10/5/054011]
Zhu X B, Ma M G, Yang H and Ge W. 2017. Modeling the spatiotemporal dynamics of gross domestic product in China using extended temporal coverage nighttime light data. Remote Sensing, 9(6): 626 [DOI: 10.3390/rs9060626http://dx.doi.org/10.3390/rs9060626]
Zhuo L, Chen J, Shi P J, Gu Z H, Fan Y D and Ichinose T. 2005. Modeling population density of China in 1998 based on DMSP/OLS nighttime light image. Acta Geographica Sinica, 60(2): 266-276
卓莉, 陈晋, 史培军, 辜智慧, 范一大, 一之濑俊明. 2005. 基于夜间灯光数据的中国人口密度模拟. 地理学报, 60(2): 266-276 [DOI: 10.11821/xb200502010http://dx.doi.org/10.11821/xb200502010]
Zhuo L, Ichinose T, Zheng J, Chen J, Shi P J and Li X. 2009. Modelling the population density of China at the pixel level based on DMSP/OLS non‐radiance‐calibrated night‐time light images. International Journal of Remote Sensing, 30(4): 1003-1018 [DOI: 10.1080/01431160802430693http://dx.doi.org/10.1080/01431160802430693]
Zou Y H, Peng H Q, Liu G, Yang K D, Xie Y H and Weng Q H. 2017. Monitoring urban clusters expansion in the middle reaches of the Yangtze River, China, using time-series nighttime light images. Remote Sensing, 9(10): 1007 [DOI: 10.3390/rs9101007http://dx.doi.org/10.3390/rs9101007]
相关作者
相关机构
京公网安备11010802024621