Assessing Habitat Quality on Synergetic Land-Cover Dataset Across the Greater Mekong Subregion over the Last Four Decades
In the face of rapid infrastructure expansion and escalating anthropogenic activities, it becomes imperative to prioritize the examination of long-term transformations in land cover and ecological quality within the Greater Mekong Subregion (GMS). We developed an ecological evaluation system integrating the land cover data assimilation framework (LCDAF) with the InVEST model to accomplish this goal. The LCDAF compensates for the disadvantages of weather interference, difficulty in recognizing complex scenes, and poor generalization in remote sensing image classification, and also adds temporal continuity that other fusion methods do not have. The synthesized land cover dataset demonstrates superior overall accuracy compared to five existing global products. This enhanced dataset provides a robust foundation for comprehensive analysis and decision making within the ecological evaluation system. We implemented a rigorous and quantitative assessment of changes in land cover and habitat quality spanning 1980 to 2020. The land cover analysis unveiled a noteworthy trend that surfaced in the dynamic interplay between forested areas and croplands, highlighting simultaneous processes of forest restoration and agricultural expansion, albeit at varying rates. Further analysis of habitat quality showed that the GMS generally sustained a moderate level with a slight downward trend observed over the period. Significantly, Laos attained the highest ranking in habitat quality, succeeded by Myanmar, China, Cambodia, Vietnam, and Thailand. In human factors, land use intensity and landscape fragmentation emerge as contributors with detrimental effects on habitat quality. Substantial progress was achieved in implementing forestland conservation measures, exemplified in regions such as Cambodia and Guangxi Province of China, where these endeavors proved effective in mitigating habitat degradation. Despite these positive endeavors, the GMS’s overall habitat quality did not significantly improve. It emphasizes the enduring challenges confronted by the region in terms of ecological management and habitat conservation.
Authors
- Tian-Le Sun (ORCID: https://orcid.org/0000-0001-8928-6073)
- Junjun Fang (ORCID: https://orcid.org/0000-0001-8226-7611)
- Baozhang Chen (ORCID: https://orcid.org/0000-0001-8972-706X)
- Shu’an Liu (ORCID: https://orcid.org/0000-0002-5618-5169)
- Tewekel Melese Gemechu (ORCID: https://orcid.org/0000-0001-5178-5352)
- Philippe Ciais (ORCID: https://orcid.org/0000-0001-8560-4943)
- Jingchun Fang (ORCID: https://orcid.org/0000-0003-0690-0627)
- Huifang Zhang (ORCID: https://orcid.org/0000-0002-4011-8623)
Institutions
- Centre National de la Recherche Scientifique (FR)
- Université de Versailles Saint-Quentin-en-Yvelines (FR)
- Chinese Academy of Sciences (CN)
- Nanjing University of Information Science and Technology (CN)
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- Université Paris-Saclay (FR)
- Ambo University (ET)
- China National Administration of Coal Geology (CN)
- Laboratoire des Sciences du Climat et de l'Environnement (FR)
- CEA Paris-Saclay (FR)
- Guangdong Province Environmental Monitoring Center (CN)
- Institute of Geographic Sciences and Natural Resources Research (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- Remote Sensing
- Published
- 2025-04-20
- DOI
- https://doi.org/10.3390/rs17081467
- Citations
- 3
- Primary Topic
- Land Use and Ecosystem Services
- Type
- article
- Field-Weighted Citation Impact
- 3.32
Funders
- National Natural Science Foundation of China