Spatial scaling between leaf area index maps of different resolutions.

Abstract:

:We developed algorithms for spatial scaling of leaf area index (LAI) using sub-pixel information. The study area is located near Liping County, Guizhou Province, in China. Methods for LAI spatial scaling were investigated on LAI images with 960 m resolution derived in two ways. LAI from distributed calculation (LAID) was derived using Landsat ETM+ data (30 m), and LAI from lumped calculation (LAIL) was obtained from the coarse (960 m) resolution data derived through resampling the ETM+ data. We found that lumped calculations can be considerably biased compared to the distributed (ETM+) case, suggesting that global and regional LAI maps can be biased if surface heterogeneity within the mapping resolution is ignored. Based on these results, we developed algorithms for removing the biases in lumped LAI maps using sub-pixel land cover-type information, and applied these to correct one coarse resolution LAI product which greatly improved its accuracy.

journal_name

J Environ Manage

authors

Jin Z,Tian Q,Chen JM,Chen M

doi

10.1016/j.jenvman.2006.08.016

subject

Has Abstract

pub_date

2007-11-01 00:00:00

pages

628-37

issue

3

eissn

0301-4797

issn

1095-8630

pii

S0301-4797(06)00278-7

journal_volume

85

pub_type

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