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Satellite remote sensing of grasslands:from observation to management

草地的卫星遥感: 从观察到管理

作     者:Iftikhar Ali Fiona Cawkwell Edward Dwyer Brian Barrett Stuart Green 

作者机构:Department of GeographyUniversity College CorkCorkIreland Spatial Analysis UnitTeagascDublinIreland EurOcean-European Centre for Information on Marine Science and TechnologyLisbonPortugal School of Geographical and Earth SciencesUniversity of GlasgowGlasgowUK 

出 版 物:《Journal of Plant Ecology》 (植物生态学报(英文版))

年 卷 期:2016年第9卷第6期

页      面:649-671页

核心收录:

学科分类:0905[农学-畜牧学] 09[农学] 

基  金:Teagasc Walsh Fellowship Program for funding this research 

主  题:remote sensing agricultural grassland grassland biomass pasture management grazing intensity 

摘      要:Aims Grasslands are the world’s most extensive terrestrial ecosystem,and are a major feed source for *** increasing demand for meat and other dairy products in a sustainable manner is a big *** a field scale,Global Positioning System and ground-based sensor technologies provide promising tools for grassland and herd management with high *** the growth in availability of spaceborne remote sensing data,it is therefore important to revisit the relevant methods and applications that can exploit this *** this article,we have reviewed the(i)current status of grassland monitoring/observation methods and applications based on satellite remote sensing data,(ii)the technological and methodological developments to retrieve different grassland biophysical parameters and management characteristics(***,grazing intensity)and(iii)identified the key remaining challenges and some new upcoming trends for future *** Findings The retrieval of grassland biophysical parameters have evolved in recent years from classical regression analysis to more complex,efficient and robust modeling approaches,driven by satellite data,and are likely to continue to be the most robust method for deriving grassland information,however these require more high quality calibration and validation *** found that the hypertemporal satellite data are widely used for time series generation,and particularly to overcome cloud contamination issues,but the current low spatial resolution of these instruments precludes their use for field-scale application in many *** trend may change with the current rise in launch of satellite constellations,such as RapidEye,Sentinel-2 and even the microsatellites such as those operated by Skybox *** imagery has not been widely used for grassland applications,and a better understanding of the backscatter behaviour from different phenological stages is needed for more reliable products i

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