The Spatial and Temporal Evolution of Ecological Environment Quality in Karst Ecologically Fragile Areas Driven by Poverty Alleviation Resettlement

Abstract

Many scholars are skeptical about the poverty reduction effect and the ecological effect of poverty alleviation resettlement (PAR). This study evaluates the spatial and temporal evolution of the ecological environment quality (EEQ) to analyze the effectiveness of ecological restoration from PAR. Based on cloud computing using the Google Earth Engine platform, remote-sensing data were obtained and reconstructed from 2000 to 2020. The remote-sensing ecological index (RSEI) was used to analyze the spatial and temporal evolution of EEQ. The results show that the RSEI of the study area increased by 13.07% after the implementation of PAR, and the rate of increase was higher than that in the period before PAR; the Pu’an and Qinglong areas improved most obviously, in terms of the fragile ecological environment and the prominent contradiction between peasants and land. The residual trends method indicated that the contribution rate of improvement in RSEI due to PAR was 70.56%, 88.38%, and 82.96% in 2017, 2018, and 2020, respectively. An increase in RSEI was more obvious in the area with a greater relocated population and a higher corresponding coupling coordination level. PAR has a promoting effect on EEQ improvement but does not have ecological restoration benefits in every region. It is not satisfactory in terms of the degeneration of the LST indicator and the ecological impact of human wells.

Temporal and Spatial Changes of Ecological Environment Quality Based on RSEI: A Case Study in Ulan Mulun River Basin, China

“…The system is concerned with future and present states, while past states have less weight. The transfer matrix is a quantitative description of system state and state transition in system analysis, which can effectively analyze the transition of different levels of the RSEI [70]. In this study, remote sensing images were used to calculate the different levels of RSEI transfer process in the Ulan Mulun River Basin from 2000 to 2020.…”

Examining the links between livelihood sustainability and environmental protection in the anti-poverty relocation and settlement program areas: An empirical analysis of Shaanxi, China

“…As a result, past studies have concentrated on population issues, namely households' volition (Wilmsen and Wang, 2015;Lo and Wang, 2018;Gomersall, 2020), the factors influencing the participation of households (Guo et al, 2017;Shi and Zhou, 2018), and the impact on household livelihoods (e.g., livelihood vulnerability, livelihood capital, adaptation strategy, and income levels) Liu et al, 2018;Liu et al, 2020;Leng et al, 2021). Research on the environmental status of ARSP areas is limited (Zhou et al, 2022), and even fewer studies have combined these two aspects by approaching the resettlement as a process with multiple outcomes (Li et al, 2021). Previous studies on the correlations between livelihoods and the environment have explored the livelihoods and the environmental effect of the ARSP on regional (watershed) to global scales (Li et al, 2015), but such scales may be too broad and ambiguous to make policy recommendations.…”

On the Landscape Activity Measure Coupling Ecological Index and Public Vitality Index of UGI: The Case Study of Zhongshan, China

“…The ecological index (EI) integrates a series of basic observation indices of environmental ecology. Based on the theories of environment, geography, and landscape ecology, relevant research has been carried out in various fields of urban landscape greening quality, such as its spatial differentiation [35], change detection [36,37], driving force analysis [38], and so on. EI mainly includes characteristic indices of environmental components based on environmental science, and characteristic indices of ecological pattern and process based on landscape ecology.…”