2016
DOI: 10.1016/j.eiar.2015.10.006
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A method to the impact assessment of the returning grazing land to grassland project on regional eco-environmental vulnerability

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Cited by 71 publications
(42 citation statements)
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“…Due to intra-regional differences, the interactions will appear dissimilar; such differences should be taken into consideration when assessing the impacts of the environmental conservation projects. This is consistent with the findings of Shao et al regarding the Grain for Green Project [31]. In their research, the studied river basin was divided into three regions according to different ecological vulnerability levels.…”
Section: Similar Attitudes But a Higher Acceptance In The Southern Resupporting
confidence: 91%
“…Due to intra-regional differences, the interactions will appear dissimilar; such differences should be taken into consideration when assessing the impacts of the environmental conservation projects. This is consistent with the findings of Shao et al regarding the Grain for Green Project [31]. In their research, the studied river basin was divided into three regions according to different ecological vulnerability levels.…”
Section: Similar Attitudes But a Higher Acceptance In The Southern Resupporting
confidence: 91%
“…After that policy makers started to prioritize ecosystem restoration. Subsequently, this resulted in a range of conservation projects, such as Grain for Green (also known as the Converting Slope Land into Forest), the Natural Forest Protection (NFP) program, the Beijing and Tianjin Sandstorm Source Control (BTSSC) project, the Ecological and Environmental Protection project in Three-river Source (Shao et al, 2016), Karst Rocky Desertification Control project in southwest China (Guo & An, 2013), and the Returning Grazing Land to Grassland (RGLG) project, among others. All of these projects were implemented in large spatial and long temporal scales funded mostly by central government.…”
Section: Pes Schemes Vs Conservation Projectsmentioning
confidence: 99%
“…The latter honors the complex multivariate normality after transformation and allows back-transformation of the simulated variables to the original dataset as well as restoring the multivariate characteristics [24,25]. Applications of PPMT in 3D multivariate geosciences mapping include petroleum reservoirs [23], environmental studies [26], grade control [27], and mineral resource classification [24]. However, PPMT, in some circumstances, does not completely remove the cross-dependency among the variables, and PPMT forward transformation may show some slight dependency [21] in bivariate relationships.…”
Section: Introductionmentioning
confidence: 99%