Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors

Sensors

Guang Zheng¹ 

[1] Remote Sensing and Geospatial Analysis Laboratory and Precision Forestry Cooperative, College of Forest Resources, University of Washington, Box 352100, Seattle, Washington, USA 98195-2100; E-Mail

关键词: Leaf area index (LAI);    remote sensing;    light detection and ranging (LiDAR);    gap fraction;    gap size;    terrestrial LiDAR;   

DOI  :  10.3390/s90402719

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2009 by the authors; licensee MDPI, Basel, Switzerland