Mapping LAI using BRDF model in arid and semi-arid Northwestern China

Hongchun Peng; Haiying Li; Xin Li; Wanchang Zhang; Yanhua Chen

doi:10.1117/12.689641

3 October 2006 Mapping LAI using BRDF model in arid and semi-arid Northwestern China

Hongchun Peng, Haiying Li, Xin Li, Wanchang Zhang, Yanhua Chen

Proceedings Volume 6366, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VI; 63661H (2006) https://doi.org/10.1117/12.689641
Event: SPIE Remote Sensing, 2006, Stockholm, Sweden

Abstract

Leaf area index (LAI) is a critical vegetation parameter for the global and regional scale studies of the climatic and environmental change. There are many methods that can be used to get LAI. In this paper, the method, developed by Qi et al. (2000) was selected. The process includes three steps: the first step is model inversion, using BRDF model to produce LAI with pixels chose randomly in one vegetation type region; the second step is quality control, removing the outliers, fitting equations using the LAI from second step and satellite data NDVI; the third step is LAI mapping, selecting the best equation and applying it to the whole region to mapping spatial LAI distribution. The main objective of this paper is to get one method that can be used in Arid and Semi-arid Northwestern China to derive LAI in the case of lack of LAI measurements. The results derived by the above approach were compared with ones derived from the empirical method (Sellers et al. 1996) and the LAI measured in field. The results suggested that the method can get good result and R² was 0.7947, though they were greater than field measurements. The results from empirical method were closer to the measurements than ones from Qi's method, but the higher the values of NDVI were, the greater the values of estimated LAI were than LAI measurements, when the values of NDVI were greater than a certain values (here 0.74). However, the result derived from Qi's method is closer to the LAI measured in field. In general, this method was feasible in arid and semi-arid northwestern China and can get satisfactory results.

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Hongchun Peng, Haiying Li, Xin Li, Wanchang Zhang, and Yanhua Chen "Mapping LAI using BRDF model in arid and semi-arid Northwestern China", Proc. SPIE 6366, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VI, 63661H (3 October 2006); https://doi.org/10.1117/12.689641

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KEYWORDS

Vegetation

Data modeling

Bidirectional reflectance transmission function

Reflectivity

Associative arrays

Lithium

Statistical modeling

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