Monitoring The Effect Poverty Alleviation In National Poverty-stricken Counties From The Perspective Of Night Light Remote Sensing

In the long-term monitoring of the development of poverty-stricken areas,most studies are based on traditional statistical data.However,traditional data has certain limitations in terms of acquisition and use,such as time lag,high acquisition cost,and strong objectivity.Therefore,based on the NPP-VIIRS night light remote sensing image data,this paper conducts monitoring research and analysis on the development of 592 national-level poverty-stricken counties in my country over a long time series.In this study,the monthly composite data of NPP-VIIRS is selected as the original data to synthesize the annual composite data of the long-term series,Use the officially released 2015 and 2016 annual denoising images to perform noise processing on the 2012-2019 synthetic image;Select Hebei Province as the sample area,draw lessons from the sustainable livelihood framework model in poverty research,select the socio-economic parameter indicators corresponding to the five major livelihood capitals,use the entropy method to obtain the index weights,and build a multi-dimensional poverty index model;Construct a night light intensity model,and compare and fit the obtained light index with the multidimensional poverty index;From the perspective of long time series,this paper makes a comparative study on the evolution trend of spatio-temporal pattern of state-level poverty counties in China,the results show:(1)Comparing the NPP-VIIRS images and standard values after synthetic denoising in2015 and 2016,the relative errors are-8.22% and-5.13%,respectively,and the effect of fitting economic parameters is better than the original data.(2)In 2017,the index weights were much greater in terms of human capital and natural capital than in 2013.The night light index has a high linear correlation with the multidimensional poverty index,and the goodness of fit is above 0.7,which can reflect the overall development of poverty-stricken counties in my country.(3)The counties with the highest TDNI value of poor counties are located at the junction of the two provinces,while the lower counties have a higher elevation and are severely affected by natural disasters and their development is restricted.Anhui Province has the fastest growth rate,and Guizhou Province has the slowest growth rate.Hainan Province,Hebei Province,Henan Province,Inner Mongolia Autonomous Region,Ningxia Autonomous Region,Shanxi Province and Yunnan Province have an obvious trend of first decline and then rise,and the rate of change has obvious aggregation in the spatial distribution.The proportion of TDNI in the long-term time series of various regions has not changed much,with the increase of 3% in North China and a decrease of 3% in East China.(4)The overall TDNI of poverty-stricken counties has shown a rapid growth trend.In 2019,it was 1.59 times the value of TDNI in 2012.Among them,the light value base with higher growth rate is relatively low.The growth rate of 20 poor counties is less than 0,and Shanxi has5 at most.There are 47 impoverished counties showing a negative growth trend in the longterm time series,380 impoverished counties show a low-speed growth trend,143 impoverished counties show a medium-speed growth trend,and 21 impoverished counties show a rapid growth trend.(5)The night light intensity of the national-level poverty-stricken counties in my country migrates to the southeast in a long time sequence,and the spatial distribution area increases.Based on the development of impoverished counties and the rural revitalization strategy as a background,some countermeasures and suggestions are put forward from the perspective of five livelihood capitals.