期刊
SENSORS
卷 23, 期 8, 页码 -出版社
MDPI
DOI: 10.3390/s23084101
关键词
ecosystem conditions; regional assessment; landscape pattern; remote sensing; spatial big data
Regional ecosystem conditions are important for environmental management, public awareness, and land use decision making. VOR and PSR are commonly used conceptual models for indicator selection and organization. However, there are challenges regarding spatial data, integration of natural and human dimensions, and data quality and analyses.
Ecosystem conditions at the regional level are critical factors for environmental management, public awareness, and land use decision making. Regional ecosystem conditions may be examined from the perspectives of ecosystem health, vulnerability, and security, as well as other conceptual frameworks. Vigor, organization, and resilience (VOR) and pressure-stress-response (PSR) are two commonly adopted conceptual models for indicator selection and organization. The analytical hierarchy process (AHP) is primarily used to determine model weights and indicator combinations. Although there have been many successful efforts in assessing regional ecosystems, they remain affected by a lack of spatially explicit data, weak integration of natural and human dimensions, and uncertain data quality and analyses. In the future, regional ecosystem condition assessments may be advanced by incorporating recent improvements in spatial big data and machine learning to create more operative indicators based on Earth observations and social metrics. The collaboration between ecologists, remote sensing scientists, data analysts, and scientists in other relevant disciplines is critical for the success of future assessments.
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