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Assessing Regional Ecosystem Conditions Using Geospatial Techniques—A Review
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....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10143971/ https://www.ncbi.nlm.nih.gov/pubmed/37112442 http://dx.doi.org/10.3390/s23084101 |
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author | Zhang, Chunhua Wang, Kelin Yue, Yuemin Qi, Xiangkun Zhang, Mingyang |
author_facet | Zhang, Chunhua Wang, Kelin Yue, Yuemin Qi, Xiangkun Zhang, Mingyang |
author_sort | Zhang, Chunhua |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10143971 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101439712023-04-29 Assessing Regional Ecosystem Conditions Using Geospatial Techniques—A Review Zhang, Chunhua Wang, Kelin Yue, Yuemin Qi, Xiangkun Zhang, Mingyang Sensors (Basel) Review 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. MDPI 2023-04-19 /pmc/articles/PMC10143971/ /pubmed/37112442 http://dx.doi.org/10.3390/s23084101 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Zhang, Chunhua Wang, Kelin Yue, Yuemin Qi, Xiangkun Zhang, Mingyang Assessing Regional Ecosystem Conditions Using Geospatial Techniques—A Review |
title | Assessing Regional Ecosystem Conditions Using Geospatial Techniques—A Review |
title_full | Assessing Regional Ecosystem Conditions Using Geospatial Techniques—A Review |
title_fullStr | Assessing Regional Ecosystem Conditions Using Geospatial Techniques—A Review |
title_full_unstemmed | Assessing Regional Ecosystem Conditions Using Geospatial Techniques—A Review |
title_short | Assessing Regional Ecosystem Conditions Using Geospatial Techniques—A Review |
title_sort | assessing regional ecosystem conditions using geospatial techniques—a review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10143971/ https://www.ncbi.nlm.nih.gov/pubmed/37112442 http://dx.doi.org/10.3390/s23084101 |
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