A method to the impact assessment of the returning grazing land to grassland project on regional eco-environmental vulnerability |
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| Institution: | 1. Key Laboratory of Geoscience Spatial Information Technology, Ministry of Land and Resources of China, Chengdu University of Technology, Chengdu 610059, Sichuan, China;2. School of Earth Sciences, Zhejiang University, Hangzhou 310027, Zhejiang, China;3. College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225, Sichuan, China;4. Center for Global Change and Earth Observations, Michigan State University, East Lansing 48823, MI, USA;1. College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China;2. Department of Bioresource Engineering, Faculty of Agricultural and Environmental Science McGill University, Québec H9X 3V9, Canada;3. School of Agricultural, Computational and Environmental Sciences, International Centre for Applied Climate Sciences, Institute of Agriculture and Environment, University of Southern Queensland, Springfield, QLD 4300, Australia;4. Key Laboratory of Ecohydrology of Inland River Basin, Alashan Desert Eco-Hydrology Experimental Research Station, Cold and Arid Regions Environmental Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 73000, China;1. Center for Space and Remote Sensing Research, National Central University, 300, Jhongda Rd., Jhongli District, Taoyuan City 32001, Taiwan, ROC;2. Taiwan Group on Earth Observations, Hsinchu, Taiwan, ROC;3. Institute of Geography, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet Rd., Cau Giay, Hanoi, Viet Nam |
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| Abstract: | The Chinese government has conducted the Returning Grazing Land to Grassland Project (RGLGP) across large portions of grasslands from western China since 2003. In order to explore and understand the impact in the grassland's eco-environment during the RGLGP, we utilized Projection Pursuit Model (PPM) and Geographic Information System (GIS) to develop a spatial assessment model to examine the ecological vulnerability of the grassland. Our results include five indications: (1) it is practical to apply the spatial PPM on ecological vulnerability assessment for the grassland. This methodology avoids creating an artificial hypothesis, thereby providing objective results that successfully execute a multi-index assessment process and analysis under non-linear systems in eco-environments; (2) the spatial PPM is not only capable of evaluating regional eco-environmental vulnerability in a quantitative way, but also can quantitatively demonstrate the degree of effect in each evaluation index for regional eco-environmental vulnerability; (3) the eco-environment of the Xianshui River Basin falls into the medium range level. The normalized difference vegetation index (NDVI) and land use cover and change (LUCC) crucially influence the Xianshui River Basin's eco-environmental vulnerability. Generally, in the Xianshui River Basin, regional eco-environmental conditions improved during 2000 and 2010. The RGLGP positively affected NDVI and LUCC structure, thereby promoting the enhancement of the regional eco-environment; (4) the Xianshui River Basin divides its ecological vulnerability across different levels; therefore our study investigates three ecological regions and proposes specific suggestions for each in order to assist in eco-environmental protection and rehabilitation; and lastly that (5) the spatial PPM established by this study has the potential to be applied on all types of grassland eco-environmental vulnerability assessments under the RGLGP and under the similar conditions in the Returning Agriculture Land to Forest Project (RALFP). However, when establishing an eco-environmental vulnerability assessment model, it is necessary to choose suitable evaluation indexes in accordance with regional eco-environmental characteristics. |
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