Spatio-temporal variations of nighttime lights in China’s poverty-stricken counties
- Pages: 1-16(2022)
DOI： 10.11834/jrs.20221856
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摘要
2020年是我国全面打赢脱贫攻坚战的收官之年。评估减贫效果是当前验收工作的重点，并对探索解决相对贫困的长效机制具有重要意义。本文通过生产精准扶贫阶段（2014-2020年NPP-VIIRS）夜间灯光遥感年合成数据，构建县域夜间灯光指数和夜间灯光变化指数，分别探讨了我国831个国家级贫困县和14个集中连片特困区的减贫效果。结果表明，2014年以来我国大部分贫困县的经济水平得到显著提高，减贫效果突出。然而，仍有108个贫困县夜间灯光强度呈现负增长趋势，主要位于西部地区的集中连片特困区交界处，西部地区内部出现南北发展不平衡现象。14个集中连片特困地区的夜间灯光亮度变化呈现出基数小增速快（I型）、基数大增速快（II型）、基数大增速慢（III型）和基数小增速慢（IV型）种类型，且在集中连片特困区交界处和省级行政边界交汇处呈现高高集聚和低低制约的空间分布格局，交界处的贫困县易被边缘化。进一步分析表明，实施基础设施扶贫、特色产业扶贫、资产收益扶贫（光伏扶贫）、易地搬迁扶贫这四类脱贫路径的贫困县夜间灯光变化明显。
Abstract
Objective By the end of 2020, China has scored a victory in its fight against poverty. Evaluate the poverty reduction effect is not only condutive to issue implementation plans for acceptance of poverty exit, but also of great imprtance to build a long-term and effectual mechanism to solve the relative poverty.Method By synthesizing an annual dataset of NPP-VIIRS nighttime light (NTL) data from 2014 to 2020, we developed a county-level NTL index to investigate the poverty reduction effects of 831 national-level poverty-stricken counties and 14 concentrated contiguous poverty-stricken areas in China.Result The results indicated that the economic level of most poverty-stricken counties in China has been improved significantly during the study period, and the poverty reduction effect is prominent. However, there are still 108 poverty-stricken counties with negative growth trend of NTL intensity, which are mainly located at the junction of concentrated and contiguous poverty-stricken areas in the western region. Besides, the NTL intensity development between the north and south parts of western regions is unbalanced. Four NTL development modes, i.e., small NTL base with a rapid growth rate (mode I), large NTL base with a rapid growth rate (mode II)), large NTL base with a slow growth rate (mode III), and small NTL base with a slow growth rate (mode IV) were identified in the 14 concentrated contiguous poverty-stricken areas. It was also interesting to find that the high concentration mode and low restriction mode were distributed at the junction areas among different provincial administrative boundaries. Besides, poor counties along the border are vulnerable to marginalization. Further analysis indicated that significant NTL changes were observed in the poverty-stricken counties with four poverty alleviation paths: infrastructure poverty alleviation, characteristic industry poverty alleviation, asset income poverty alleviation (photovoltaic poverty alleviation) , and relocation poverty alleviation.
关键词
夜间灯光NPP-VIIRS国家级贫困县集中连片特困地区时空变化减贫效果
Keywords
Nighttime lights(NTL)NPP-VIIRSNTL changesPoor countiesPoverty reduction effect
references
Alkire S and Foster J. 2007. Counting and multidimensional poverty measurement. Journal of Public Economics, 95（7-8）:476-487. [DOI:10.1016/j.jpubeco.2010.11.006http://dx.doi.org/10.1016/j.jpubeco.2010.11.006]
Alkire S and Santos M E. 2014. Measuring acute poverty in the developing world: robustness and scope of the multidimensional poverty index. World Development, 59（1）:251-274. [DOI:10.1016/j.worlddev.2014.01.026http://dx.doi.org/10.1016/j.worlddev.2014.01.026]
Anthony F S. 1995. Revisiting the Sen poverty index. Econometrica, 63（5）:1225-1230. [DOI:10.2307/2171728http://dx.doi.org/10.2307/2171728]
Bennett M M and Smith L C. 2017. Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeconomic dynamics. Remote Sensing of Environment: An Interdisciplinary Journal, 192,176-197. [DOI: 10.1016/j.rse.2017.01.005http://dx.doi.org/10.1016/j.rse.2017.01.005]
Chen Z Q, Yu B L, Na T and Wu J P. 2019. Delineating seasonal relationships between Suomi NPP-VIIRS nighttime light and human activity across Shanghai, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, PP（99）:1-9. [DOI:10.1109/JSTARS.2019.2916323http://dx.doi.org/10.1109/JSTARS.2019.2916323]
Chen Z Q, Yu B L, Yang C S, Zhou Y Y and Wu J P. 2021. An extended time series （2000-2018） of global NPP-VIIRS-like nighttime light data from a cross-sensor calibration. Earth System Science Data, 13（3）:889-906. [DOI:10.5194/essd-2020-201http://dx.doi.org/10.5194/essd-2020-201]
Elvidge C D, Sutton P C and Ghosh T. 2009. A global poverty map derived from satellite data. Computers & Geosciences, 35（8）:1652-1660. [DOI 10.1016/j.cageo.2009.01.009http://dx.doi.org/10.1016/j.cageo.2009.01.009]
Foster J E, Greer J and Thorbecke E. 1984. A class of decomposable poverty measures. Econometrica, 52（3）:761-765. [ DOI:10.2307/1913475]
Ghosh T, Anderson S J, Elvidge C D and Sutton P C. 2013. Using nighttime satellite imagery as a proxy measure of human well-being. Sustainability, 5（12）:4988-5019. [ DOI：10.3390/su5124988]
He R W, Li G Q and Liu Y W. 2017. Theoretical analysis and case study on targeted poverty alleviation based on sustainable livelihoods framework: a case study of Liangshan Yi autonomous prefecture, Sichuan province. Progress in Geography, 36（2）:182-192
何仁伟, 李光勤, 刘运伟. 2017. 基于可持续生计的精准扶贫分析方法及应用研究--以四川凉山彝族自治州为例.地理科学进展, 36（2）:182-192 [DOI: 10.18306/dlkxjz.2017.02.005http://dx.doi.org/10.18306/dlkxjz.2017.02.005]
Jean N, Burke M, Xie M, Davis WM and Ermon S. 2016. Combining satellite imagery and machine learning to predict poverty. Science, 353（1）:790-794. [DOI:10.1126/science.aaf7894http://dx.doi.org/10.1126/science.aaf7894]
Jia L R, Liu Y S, Liu J L, Li J T. 2018. Study on the poverty causes and aid demands of poor rural households in the concentrated poverty-stricken areas in china. Human Geography, 33（01）:85-93+151
贾林瑞, 刘彦随, 刘继来, 李进涛. 2018. 中国集中连片特困地区贫困户致贫原因诊断及其帮扶需求分析.人文地理, 33（1）:85-93+151 [DOI:10.13959/j.issn.1003-2398.2018.01.011http://dx.doi.org/10.13959/j.issn.1003-2398.2018.01.011.]
Jin G, Deng X Z, Dong Y and Wu F. 2020. China's multidimensional poverty measurement and its spatiotemporal interaction characteristics in the perspective of development geography. Acta Geographica Sinica, 75（08）:1633-46
金贵, 邓祥征, 董寅, 吴锋. 2020. 发展地理学视角下中国多维贫困测度及时空交互特征. 地理学报, 75（8）:1633-46 [DOI:10.11821/dlxb202008006http://dx.doi.org/10.11821/dlxb202008006]
Levin N. 2017. The impact of seasonal changes on observed nighttime brightness from 2014 to 2015 monthly VIIRS DNB composites. Remote Sensing of Environment, 193:150-164. [DOI:10.1016/j.rse.2017.03.003http://dx.doi.org/10.1016/j.rse.2017.03.003]
Li C S, Yang W N, Tang Q L, Tang X L and Qiu S Y. 2020. Detection of multidimensional poverty using luojia 1-01 nighttime light imagery. Journal of the Indian Society of Remote Sensing, 48（7–8）. [DOI: 10.1007/s12524-020-01126-3http://dx.doi.org/10.1007/s12524-020-01126-3]
Li D R and Li X. 2015. An overview on data mining of nighttime light remote sensing. Acta Geodaetica et Cartographica Sinica, 000（6）, 591-601.
李德仁, 李熙. 2015.论夜光遥感数据挖掘. 测绘学报, 000（006）, 591-601[DOI:10.11947/j.AGCS.2015.20150149http://dx.doi.org/10.11947/j.AGCS.2015.20150149]
Liu Y H and Xu Y. 2015. Geographical identification and classification of multi-dimensional poverty in rural China. Acta Geographica Sinica, （6）:993-1007
刘艳华, 徐勇. 2015. 中国农村多维贫困地理识别及类型划分. 地理学报, 6:993-1007 [ DOI:10.11821/dlxb201506012]
Liu Y S and Li J T. 2017. Geographic detection and optimizing decision of the differentiation mechanism of rural poverty in China. Acta Geographica Sinica, 72（1）:161-173
刘彦随, 李进涛. 2017. 中国县域农村贫困化分异机制的地理探测与优化决策. 地理学报, 72（1）:161-173 [ DOI: 10.11821/dlxb201701013]
Ma T, Zhou C H, Pei T, Haynie S, 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]
Noor A M, Alegana V A, Gething P W, Tatem A J and Snow R W. 2008. Using remotely sensed night-time light as a proxy for poverty in Africa. Population Health Metrics, 6（1）:5. [DOI:10.1186/1478-7954-6-5http://dx.doi.org/10.1186/1478-7954-6-5]
Sen A K. 1976. Poverty: An ordinary approach to measurement. Econometrica, 44（2）:219-231. [DOI:10.2307/1912718http://dx.doi.org/10.2307/1912718]
Shen Y Y, Alkire S and Zhan P. 2018. China′s multidimensional poverty 2010—2014: calculation and decomposition. Nankai Economic Studies, 000（5）:3-18
沈扬扬, Sabina Alkire, 詹鹏. 2018. 中国多维贫困的测度与分解. 南开经济研究, 000（5）:3-18 [DOI:10.14116/j.nkes.2018.05.001http://dx.doi.org/10.14116/j.nkes.2018.05.001]
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. [DOI:10.1016/j.jclepro.2020.120245http://dx.doi.org/10.1016/j.jclepro.2020.120245]
Shi K F, Huang C, Yu B L, Yin B, Huang Y X and Wu J P. 2014. Evaluation of NPP-VIIRS night-time light composite data for extracting built-up urban areas. Remote Sensing Letters, 5（4-6）:358-366. [DOI:10.1080/2150704X.2014.905728http://dx.doi.org/10.1080/2150704X.2014.905728]
Shi K F, Yu B L, Huang Y, Hu Y J, Yin B, Chen Z Q, Chen L J and Wu J P. 2014. 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]
Si L J and Wang C Q. 2020. The measurement of reginal poverty alleviation quality and its spatio-temporal evolution: a study based on nighttime light data in poor counties. Journal of Macro-quality Research, 8（6）:28-38
斯丽娟, 王超群. 2020. 区域扶贫质量测度及其时空演变--基于贫困县夜间灯光数据的研究. 宏观质量研究, 8（6）:28-38 [DOI:10.13948/j.cnki.hgzlyj.2020.06.03.003http://dx.doi.org/10.13948/j.cnki.hgzlyj.2020.06.03.003]
Wang C L, Zhou W and Yuan T. 2018. Development in poor counties of China based on nighttime lighting data. Remote Sensing Information, 33（6）:97-102
王成力, 周伟, 袁涛. 2018. 夜间灯光数据下的中国贫困县发展状况. 遥感信息, 33（6）:97-102 [DOI:CNKI:SUN:YGXX.0.2018-06-014http://dx.doi.org/CNKI:SUN:YGXX.0.2018-06-014]
Wang C X, Yu B L, Chen Z Q, Liu Y, Song W, Li X, Yang C S, Small C, Shu S and Wu J P. 2021. Evolution of urban spatial clusters in China: a graph-based method using nighttime light data. Annals of the American Association of Geographers, 1-22. [DOI:10.1080/24694452.2021.1914538http://dx.doi.org/10.1080/24694452.2021.1914538]
Wang S J, Tian J F, Wang B Y, Cheng L S and Du G M. 2017. Regional characteristics and causes of rural poverty in northeast China from the perspective of targeted poverty alleviation. Scientia Geographica Sinica, 37（10）:1449-1458
王士君, 田俊峰, 王彬燕, 程利莎, 杜国明. 2017. 精准扶贫视角下中国东北农村贫困地域性特征及成因. 地理科学, 37（10）:1449-1458 [DOI:10.13249/j.cnki.sgs.2017.10.001http://dx.doi.org/10.13249/j.cnki.sgs.2017.10.001]
Yu B L, Shi K F, Hu Y J, Huang C, Chen Z Q and Wu J P. 2017. Poverty evaluation using NPP-VIIRS nighttime light composite data at the county level in China. IEEE Journal of Selected Topics in Applied Earth Observations & 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（11-12）:2328-2355. [DOI:10.1080/13658816.2014.922186http://dx.doi.org/10.1080/13658816.2014.922186]
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 sesing and urban studies: data, methods, applications, and prospects. National Remote Sensing Bulletin, 25（1）:342-364
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 [DOI:10.11834/jrs.20211018http://dx.doi.org/10.11834/jrs.20211018]
Zhao X Z, Yu B L, Yan L, Chen Z Q and Wu J P. 2019. 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]
Zhou Y, Guo Y Z and Liu Y S. 2018. Comprehensive measurement of county poverty and anti-poverty targeting after 2020 in China. Acta Geographica Sinica, 73（8）:86-101
周扬, 郭远智, 刘彦随. 2018. 中国县域贫困综合测度及2020年后减贫瞄准. 地理学报, 73（8）:86-101[DOI: 10.11821/dlxb201808007http://dx.doi.org/10.11821/dlxb201808007]
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School of Resource and Environmental Sciences, Wuhan University
School of Remote Sensing and Information Engineering, Wuhan University
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University
Academy of Digital China (Fujian), Fuzhou University
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University
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