TY - JOUR
T1 - Spatial–Temporal Analysis of Greenness and Its Relationship with Poverty in China
AU - Xie, Wentong
AU - Ge, Yong
AU - Hamm, Nicholas A. S.
AU - Foody, Giles M.
AU - Ren, Zhoupeng
PY - 2024/10/23
Y1 - 2024/10/23
N2 - Ecological environmental protection and poverty alleviation are of great significance for the study of human–land relationship coordination and sustainable development, and they have also been a focus of attention in China in the past few decades. In this study, we chose 13 contiguous poverty-stricken areas in China as the study area. Using MODIS Leaf Area Index (LAI) data from 2000 to 2020, the spatial–temporal changes in greenness were obtained using the Bayesian spatial–temporal model (BYM). Spatial autocorrelation was used to identify the spatial distribution of poverty using socio-economic statistical data. Driving factors, including natural factors, poverty factors, and the Grain for Green Policy (GTGP), and their influence on greenness were analyzed by using the Geodetector model for detecting spatial differentiation and factors’ interactions. The results showed the following: (1) In 13 contiguous poverty-stricken areas (CPSAs) in China, 59% of the area presented an increasing trend of greenness. (2) In 2000, the high poverty levels with larger MPI values were widely distributed. After 20 years, the overall MPI value was lower, except in some northwest regions with increased MPI values. The spatial autocorrelation of poverty, which relates to the mutual influence of poverty in adjacent areas, also decreased. (3) In the study area, 65.24% of the regions showed strong synergistic effect between greening progress and poverty reduction in the interaction between poverty status and green development. With the improvement of greenness level, the positive correlation between poverty alleviation and ecological environment improvement has become increasingly close. (4) The impacts of interaction factors with the highest q values changed from temperature interacting with precision to regional division interacting with the Grain for Green Policy. The conclusions are that from 2000 to 2020, the impact of natural factors, geographical division, and poverty status on greenness has shown a decreasing trend; The effect of the Grain for Green Policy is gradually increasing; At the same time, the interaction and overlapping effects between the Grain for Green Policy and poverty were increasing. Taking into account the needs of ecological environment, poverty alleviation, and rural revitalization, this research provides valuable reference for formulating and implementing relevant policies based on the actual situation in different regions to promote harmonious coexistence between human-land relationship.
AB - Ecological environmental protection and poverty alleviation are of great significance for the study of human–land relationship coordination and sustainable development, and they have also been a focus of attention in China in the past few decades. In this study, we chose 13 contiguous poverty-stricken areas in China as the study area. Using MODIS Leaf Area Index (LAI) data from 2000 to 2020, the spatial–temporal changes in greenness were obtained using the Bayesian spatial–temporal model (BYM). Spatial autocorrelation was used to identify the spatial distribution of poverty using socio-economic statistical data. Driving factors, including natural factors, poverty factors, and the Grain for Green Policy (GTGP), and their influence on greenness were analyzed by using the Geodetector model for detecting spatial differentiation and factors’ interactions. The results showed the following: (1) In 13 contiguous poverty-stricken areas (CPSAs) in China, 59% of the area presented an increasing trend of greenness. (2) In 2000, the high poverty levels with larger MPI values were widely distributed. After 20 years, the overall MPI value was lower, except in some northwest regions with increased MPI values. The spatial autocorrelation of poverty, which relates to the mutual influence of poverty in adjacent areas, also decreased. (3) In the study area, 65.24% of the regions showed strong synergistic effect between greening progress and poverty reduction in the interaction between poverty status and green development. With the improvement of greenness level, the positive correlation between poverty alleviation and ecological environment improvement has become increasingly close. (4) The impacts of interaction factors with the highest q values changed from temperature interacting with precision to regional division interacting with the Grain for Green Policy. The conclusions are that from 2000 to 2020, the impact of natural factors, geographical division, and poverty status on greenness has shown a decreasing trend; The effect of the Grain for Green Policy is gradually increasing; At the same time, the interaction and overlapping effects between the Grain for Green Policy and poverty were increasing. Taking into account the needs of ecological environment, poverty alleviation, and rural revitalization, this research provides valuable reference for formulating and implementing relevant policies based on the actual situation in different regions to promote harmonious coexistence between human-land relationship.
KW - greenness
KW - geostatistics
KW - poverty-stricken areas
KW - driving factors
UR - https://doi.org/10.3390/rs16213938
U2 - 10.3390/rs16213938
DO - 10.3390/rs16213938
M3 - Article
SN - 2072-4292
VL - 16
JO - Remote Sensing
JF - Remote Sensing
IS - 21
M1 - 3938
ER -