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Habitat Quality Assessment in the Yellow River Delta Based on Remote Sensing and Scenario Analysis for Land Use/Land Cover

Author

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  • Yubin Liu

    (School of Geography and Tourism, Qilu Normal University, Jinan 250020, China)

  • Mei Han

    (School of Geography and Environment, Shandong Normal University, Jinan 250014, China)

  • Min Wang

    (School of Geography and Tourism, Qilu Normal University, Jinan 250020, China)

  • Chao Fan

    (Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China)

  • Hang Zhao

    (Shandong Provincial Institute of Land Surveying and Mapping, Jinan 250102, China)

Abstract

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.

Suggested Citation

  • Yubin Liu & Mei Han & Min Wang & Chao Fan & Hang Zhao, 2022. "Habitat Quality Assessment in the Yellow River Delta Based on Remote Sensing and Scenario Analysis for Land Use/Land Cover," Sustainability, MDPI, vol. 14(23), pages 1-16, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15904-:d:987788
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    References listed on IDEAS

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    1. Qinglong Ding & Yang Chen & Lingtong Bu & Yanmei Ye, 2021. "Multi-Scenario Analysis of Habitat Quality in the Yellow River Delta by Coupling FLUS with InVEST Model," IJERPH, MDPI, vol. 18(5), pages 1-19, March.
    2. Aretano, Roberta & Semeraro, Teodoro & Petrosillo, Irene & De Marco, Antonella & Pasimeni, Maria Rita & Zurlini, Giovanni, 2015. "Mapping ecological vulnerability to fire for effective conservation management of natural protected areas," Ecological Modelling, Elsevier, vol. 295(C), pages 163-175.
    3. Konarska, Keri M. & Sutton, Paul C. & Castellon, Michael, 2002. "Evaluating scale dependence of ecosystem service valuation: a comparison of NOAA-AVHRR and Landsat TM datasets," Ecological Economics, Elsevier, vol. 41(3), pages 491-507, June.
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    Cited by:

    1. Jiehua Lv & Wen Zhou, 2023. "Ecological Environmental Quality in China: Spatial and Temporal Characteristics, Regional Differences, and Internal Transmission Mechanisms," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    2. Shuanglong Du & Zhongfa Zhou & Denghong Huang & Fei Dong & Xiandan Du & Yining Luo & Qingqing Dai & Yue Yang, 2025. "Evaluation of Habitat Quality in Karst Mountainous Areas of Guanling County Based on InVEST and MGWR Models," Land, MDPI, vol. 14(7), pages 1-22, July.

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