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Sensors 2015, 15(2), 3070-3089;

Some Insights on Grassland Health Assessment Based on Remote Sensing

Department of Geography and Planning, University of Saskatchewan, Saskatoon, SK S7N 5C8, Canada
Author to whom correspondence should be addressed.
Received: 25 November 2014 / Revised: 16 January 2015 / Accepted: 21 January 2015 / Published: 29 January 2015
(This article belongs to the Section Remote Sensors)
Full-Text   |   PDF [831 KB, uploaded 29 January 2015]


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. View Full-Text
Keywords: ecosystem; grassland health assessment; grassland monitoring; remote sensing ecosystem; grassland health assessment; grassland monitoring; remote sensing
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Xu, D.; Guo, X. Some Insights on Grassland Health Assessment Based on Remote Sensing. Sensors 2015, 15, 3070-3089.

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