Retrieving Leaf Area Index LAI Using Remote Sensing: Theories, Methods and SensorsReport as inadecuate




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Remote Sensing and Geospatial Analysis Laboratory and Precision Forestry Cooperative, College of Forest Resources, University of Washington, Box 352100, Seattle, Washington, 98195-2100, USA





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Abstract The ability to accurately and rapidly acquire leaf area index LAI is an indispensable component of process-based ecological research facilitating the understanding of gas-vegetation exchange phenomenon at an array of spatial scales from the leaf to the landscape. However, LAI is difficult to directly acquire for large spatial extents due to its time consuming and work intensive nature. Such efforts have been significantly improved by the emergence of optical and active remote sensing techniques. This paper reviews the definitions and theories of LAI measurement with respect to direct and indirect methods. Then, the methodologies for LAI retrieval with regard to the characteristics of a range of remotely sensed datasets are discussed. Remote sensing indirect methods are subdivided into two categories of passive and active remote sensing, which are further categorized as terrestrial, aerial and satellite-born platforms. Due to a wide variety in spatial resolution of remotely sensed data and the requirements of ecological modeling, the scaling issue of LAI is discussed and special consideration is given to extrapolation of measurement to landscape and regional levels. View Full-Text

Keywords: Leaf area index LAI; remote sensing; light detection and ranging LiDAR; gap fraction; gap size; terrestrial LiDAR Leaf area index LAI; remote sensing; light detection and ranging LiDAR; gap fraction; gap size; terrestrial LiDAR





Author: Guang Zheng and L. Monika Moskal *

Source: http://mdpi.com/



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