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Some Insights on Grassland Health Assessment Based on Remote Sensing
Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynami...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367348/ https://www.ncbi.nlm.nih.gov/pubmed/25643060 http://dx.doi.org/10.3390/s150203070 |
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author | Xu, Dandan Guo, Xulin |
author_facet | Xu, Dandan Guo, Xulin |
author_sort | Xu, Dandan |
collection | PubMed |
description | Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment. |
format | Online Article Text |
id | pubmed-4367348 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-43673482015-04-30 Some Insights on Grassland Health Assessment Based on Remote Sensing Xu, Dandan Guo, Xulin Sensors (Basel) Review Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment. MDPI 2015-01-29 /pmc/articles/PMC4367348/ /pubmed/25643060 http://dx.doi.org/10.3390/s150203070 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Xu, Dandan Guo, Xulin Some Insights on Grassland Health Assessment Based on Remote Sensing |
title | Some Insights on Grassland Health Assessment Based on Remote Sensing |
title_full | Some Insights on Grassland Health Assessment Based on Remote Sensing |
title_fullStr | Some Insights on Grassland Health Assessment Based on Remote Sensing |
title_full_unstemmed | Some Insights on Grassland Health Assessment Based on Remote Sensing |
title_short | Some Insights on Grassland Health Assessment Based on Remote Sensing |
title_sort | some insights on grassland health assessment based on remote sensing |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367348/ https://www.ncbi.nlm.nih.gov/pubmed/25643060 http://dx.doi.org/10.3390/s150203070 |
work_keys_str_mv | AT xudandan someinsightsongrasslandhealthassessmentbasedonremotesensing AT guoxulin someinsightsongrasslandhealthassessmentbasedonremotesensing |