|
|
|
|
|
|
Identification of poverty based on nighttime light remote sensing data: A case study on contiguous special poverty-stricken areas in Liupan Mountains |
Dan SHEN1,2, Liang ZHOU1,2,3( ), Peian WANG1,2 |
1.College of Mapping and Geographic Information, Lanzhou Jiaotong University, Lanzhou 730070, China
2.Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China
3.Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China |
|
|
|
|
Abstract In the process of targeted poverty alleviation, the problems that traditional data statistic aperture is not unified and that nighttime light data for identifying poverty is studied in a short time usually exist. With Liupan Mountain as an example, the average light index and multidimensional poverty index (MPIstatistical) indices were constructed by using the method of invariant target area and gray relational model with the help of night light and socio-economic statistics. Poverty estimation models were constructed through average light index and MPIstatistics. MPIestimation was generated and used to explore long-term sequence of poverty identification. Some conclusions have been reached: the accuracy of poverty results based on nighttime light image was higher, which can reflect the real poverty degree of the region, and the relative error ranges between 3.14% and 3.52%. The MPI estimated averages of the contiguous special poverty areas respectively are 0.346, 0.353, 0.353, 0.357 and 0.358 in many years. The level of poverty has been reduced year by year. Between 2000 and 2012, there were 3946 counties with extremely poor conditions and 2021 counties with highly poor conditions. The Moran’s I index from 2000 to 2015 respectively were 0.49, 0.45, 0.47, 0.49 and 0.43, indicating that the poverty level in 78 counties exhibits obvious agglomeration. The pattern of poverty is presented with the spatial evolution trend of “relatively less poverty in the eastern and western regions and relatively heavier poverty in the northern and southern regions”.
|
| Keywords
DMSP-OLS/NPP-VIIRS
poverty index
targeted poverty alleviation
poverty identification
Liupan Mountains
|
|
|
|
Corresponding Authors:
Liang ZHOU
E-mail: zhougeo@126.com
|
|
Issue Date: 23 May 2019
|
|
|
| [1] |
刘艳华, 徐勇 . 中国农村多维贫困地理识别及类型划分[J]. 地理学报, 2015,70(6):993-1007.
|
| [1] |
Liu Y H, Xu Y . Geographical identification and classification of multi-dimensional poverty in rural China[J]. Acta Geographica Sinica, 2015,70(6):993-1007.
|
| [2] |
Liu Y H, Xu Y . A geographic identification of multidimensional poverty in rural China under the framework of sustainable livelihoods analysis[J]. Applied Geography, 2016,73:62-76.
doi: 10.1016/j.apgeog.2016.06.004
url: https://linkinghub.elsevier.com/retrieve/pii/S0143622816301400
|
| [3] |
何深静, 左姣姣, 朱寿佳 , 等. 中国大城市贫困研究的多种测度与多层模型分析[J]. 人文地理, 2014,29(6):74-80.
|
| [3] |
He S J, Zuo J J, Zhu S J , et al. Understanding urban poverty in large Chinese cities using multiple measurements and hierarahical regression models[J]. Human Geography, 2014,29(6):74-80.
|
| [4] |
Jean N, Burke M, Xie M , et al. Combining satellite imagery and machine learning to predict poverty[J]. Science, 2016,353(6301):790-793.
doi: 10.1126/science.aaf7894
url: http://www.sciencemag.org/cgi/doi/10.1126/science.aaf7894
|
| [5] |
周亮, 徐建刚, 林蔚 , 等. 秦巴山连片特困区地形起伏与人口及经济关系[J]. 山地学报, 2015,33(6):742-750.
|
| [5] |
Zhou L, Xu J G, Lin W , et al. Relationship of terrain relief degree and population economic development and evaluation of development suitability in continuous poor areas:A case study on Qinba of national contiguous special poverty-stricken areas[J]. Mountain Research, 2015,33(6):742-750.
|
| [6] |
陈烨烽, 王艳慧, 王小林 . 中国贫困村测度与空间分布特征分析[J]. 地理研究, 2016,35(12):2298-2308.
|
| [6] |
Chen Y F, Wang Y H, Wang X L . Measurement and spatial analysis of poverty-stricken villages in China[J]. Geographical Research, 2016,35(12):2298-2308.
|
| [7] |
田宇, 许建, 麻学锋 . 武陵山片区多维贫困度量及其空间表征[J]. 经济地理, 2017,37(1):162-169.
|
| [7] |
Tian Y, Xu J, Ma X F . Multidimensional poverty measurement and spatial distribution of contiguous special poverty-stricken areas:A case study on key city in Wuling Mountain area of poverty alleviation[J]. Economic Geography, 2017,37(1):162-169.
|
| [8] |
杨振, 江琪, 刘会敏 , 等. 中国农村居民多维贫困测度与空间格局[J]. 经济地理, 2015,35(12):148-153.
doi: 10.15957/j.cnki.jjdl.2015.12.021
url: http://d.wanfangdata.com.cn/Periodical/jjdl201512021
|
| [8] |
Yang Z, Jiang Q, Liu H M , et al. Multi-dimensional poverty measure and spatial pattern of China’s rural residents[J]. Economic Geography, 2015,35(12):148-153.
|
| [9] |
Noor A M, Alegana V A, Gething P W , et al. Using remotely sensed night-time light as a proxy for poverty in Africa[J]. Population Health Metrics, 2008,6(1):1-13.
doi: 10.1186/1478-7954-6-1
|
| [10] |
Elvidge C D, Sutton P C, Ghosh T , et al. A global poverty map derived from satellite data[J]. Computers and Geosciences, 2009,35(8):1652-1660.
doi: 10.1016/j.cageo.2009.01.009
url: https://linkinghub.elsevier.com/retrieve/pii/S0098300409001253
|
| [11] |
Wang W, Cheng H, Zhang L . Poverty assessment using DMSP/OLS night-time light satellite imagery at a provincial scale in China[J]. Advances in Space Research, 2012,49(8):1253-1264.
doi: 10.1016/j.asr.2012.01.025
url: https://linkinghub.elsevier.com/retrieve/pii/S0273117712000828
|
| [12] |
Yu B L, Shi K F, Hu Y J , et al. Poverty evaluation using NPP-VIIRS nighttime light composite data at the county level in China[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015,8(3):1217-1229.
|
| [13] |
潘竟虎, 胡艳兴 . 基于夜间灯光数据的中国多维贫困空间识别[J]. 经济地理, 2016,36(11):125-131.
|
| [13] |
Pan J H, Hu Y X . Spatial identification of multidimensional poverty in China based on nighttime light remote sensing data[J]. Economic Geography, 2016,36(11):125-131.
|
| [14] |
曹子阳, 吴志峰, 匡耀求 , 等. DMSP-OLS夜间灯光影像中国区域的校正及应用[J]. 地球信息科学学报, 2015,17(9):1093-1102.
|
| [14] |
Cao Z Y, Wu Z F, Kuang Y Q , et al. Correction of DMSP/OLS night-time light images and its application in China[J]. Journal of Geo-Information Science, 2015,17(9):1093-1102.
|
| [15] |
李峰, 米晓楠, 刘军 , 等. 基于NPP-VIIRS夜间灯光数据的北京市GDP空间化方法[J]. 国土资源遥感, 2016,28(3):19-24.doi: 10.6046/gtzyyg.2016.03.04.
doi: 10.6046/gtzyyg.2016.03.04
|
| [15] |
Li F, Mi X N, Liu J , et al. Spatialization of GDP in Beijing using NPP-VIIRS data[J]. Remote Sensing for Land and Resources, 2016,28(3):19-24.doi: 10.6046/gtzyyg.2016.03.04.
|
| [16] |
袁媛, 王仰麟, 马晶 , 等. 河北省县域贫困度多维评估[J]. 地理科学进展, 2014,33(1):124-133.
doi: 10.11820/dlkxjz.2014.01.014
url: http://d.wanfangdata.com.cn/Periodical/dlkxjz201401014
|
| [16] |
Yuan Y, Wang Y L, Ma J , et al. Multidimensional evaluation of county poverty degree in Hebei Province[J]. Progress in Geography, 2014,33(1):124-133.
|
| [17] |
袁涛 . DMSP/OLS数据支持的贫困地区测度方法研究[D].北京:中国地质大学( 北京), 2013.
|
| [17] |
Yuan T . Monitoring Methods for Poor Areas Supported by DMSP/OLS Night Time Light Imgery[D].Beijing:China University of Geosciences(Beijing), 2013.
|
| [18] |
丁建军 . 中国11个集中连片特困区贫困程度比较研究——基于综合发展指数计算的视角[J]. 地理科学, 2014,34(12):1418-1427.
url: http://d.wanfangdata.com.cn/Periodical_dlkx201412002.aspx
|
| [18] |
Ding J J . Comparative analysis on poverty degree of China’s 11 contiguous destitute areas:With view of comprehensive development index[J]. Scientia Geographica Sinica, 2014,34(12):1418-1427.
|
| [19] |
李宗光, 胡德勇, 李吉贺 , 等. 基于夜间灯光数据的连片特困区GDP估算及其空间化[J]. 国土资源遥感, 2016,28(2):168-174.doi: 10.6046/gtzyyg.2016.02.26.
doi: 10.6046/gtzyyg.2016.02.26
|
| [19] |
Li Z G, Hu D Y, Li J H , et al. Simulation and spatialization of GDP in poverty areas based on night light imagery[J]. Remote Sensing for Land and Resources, 2016,28(2):168-174.doi: 10.6046/gtzyyg.2016.02.26.
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
2019,
Vol. 31
