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Habitat Quality Assessment in the Yellow River Delta Based on Remote Sensing and Scenario Analysis for Land Use/Land Cover
Land Use/Land Cover (LULC) change is one of the core features of global change. Habitat quality is an essential representation of ecosystem service functioning and ecosystem health. It is of great significance to assess the habitat quality spatiotemporal heterogeneity caused by land-use change in the regional ecological environment for security and sustainable regional management. Based on the interpreted LULC data of the Yellow River Delta (YRD) in 2000, 2010, and 2020, the PLUS model was used to forecast different LULC 2030 scenarios. Specifically, this study aimed to analyze the LULC change in the YRD and use the InVEST model to evaluate the overall habitat quality in the historical period of the region and future scenarios. From 2000 to 2020, the most critical land-use changes within a 20 km radius from the coastline in the study area are mainly the sharp increase in construction land, mariculture and salt pan, and the sharp decline of coastal wetlands, which is mainly due to the high intensity of human development activities and the process of erosion and deposition in coastal zones and estuarine deltas. During the period, the average habitat quality in the YRD decreased yearly, with the overall regional habitat quality classified as intermediate. The habitat quality was the most significant in the 0–20 km range from the coastline because of the high intensity of human development activities in this area. The habitat quality in the YRD varied under different scenarios in 2030. In the baseline scenario (BS) and socio-economic development (SD) scenario, the habitat quality decreased continuously, but the habitat quality increased under the ecological protection (EP) scenario. This research can provide relevant scientific references for optimizing landscape patterns and improving habitat quality in the YRD region.
Habitat Quality Assessment in the Yellow River Delta Based on Remote Sensing and Scenario Analysis for Land Use/Land Cover
Land Use/Land Cover (LULC) change is one of the core features of global change. Habitat quality is an essential representation of ecosystem service functioning and ecosystem health. It is of great significance to assess the habitat quality spatiotemporal heterogeneity caused by land-use change in the regional ecological environment for security and sustainable regional management. Based on the interpreted LULC data of the Yellow River Delta (YRD) in 2000, 2010, and 2020, the PLUS model was used to forecast different LULC 2030 scenarios. Specifically, this study aimed to analyze the LULC change in the YRD and use the InVEST model to evaluate the overall habitat quality in the historical period of the region and future scenarios. From 2000 to 2020, the most critical land-use changes within a 20 km radius from the coastline in the study area are mainly the sharp increase in construction land, mariculture and salt pan, and the sharp decline of coastal wetlands, which is mainly due to the high intensity of human development activities and the process of erosion and deposition in coastal zones and estuarine deltas. During the period, the average habitat quality in the YRD decreased yearly, with the overall regional habitat quality classified as intermediate. The habitat quality was the most significant in the 0–20 km range from the coastline because of the high intensity of human development activities in this area. The habitat quality in the YRD varied under different scenarios in 2030. In the baseline scenario (BS) and socio-economic development (SD) scenario, the habitat quality decreased continuously, but the habitat quality increased under the ecological protection (EP) scenario. This research can provide relevant scientific references for optimizing landscape patterns and improving habitat quality in the YRD region.
Habitat Quality Assessment in the Yellow River Delta Based on Remote Sensing and Scenario Analysis for Land Use/Land Cover
2022
Article (Journal)
Electronic Resource
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