Monitoring boreal forest leaf area index across a Siberian burn chronosequence: A MODIS validation study

International Journal of Remote Sensing
By: , and 



Landscapes containing differing amounts of ecological disturbance provide an excellent opportunity to validate and better understand the emerging Moderate Resolution Imaging Spectrometer (MODIS) vegetation products. Four sites, including 1‐year post‐fire coniferous, 13‐year post‐fire deciduous, 24‐year post‐fire deciduous, and >100 year old post‐fire coniferous forests, were selected to serve as a post‐fire chronosequence in the central Siberian region of Krasnoyarsk (57.3°N, 91.6°E) with which to study the MODIS leaf area index (LAI) and vegetation index (VI) products. The collection 4 MODIS LAI product correctly represented the summer site phenologies, but significantly underestimated the LAI value of the >100 year old coniferous forest during the November to April time period. Landsat 7‐derived enhanced vegetation index (EVI) performed better than normalized difference vegetation index (NDVI) to separate the deciduous and conifer forests, and both indices contained significant correlation with field‐derived LAI values at coniferous forest sites (r 2 = 0.61 and r 2 = 0.69, respectively). The reduced simple ratio (RSR) markedly improved LAI prediction from satellite measurements (r 2 = 0.89) relative to NDVI and EVI. LAI estimates derived from ETM+ images were scaled up to evaluate the 1 km resolution MODIS LAI product; from this analysis MODIS LAI overestimated values in the low LAI deciduous forests (where LAI<5) and underestimated values in the high LAI conifer forests (where LAI>6). Our results indicate that further research on the MODIS LAI product is warranted to better understand and improve remote LAI quantification in disturbed forest landscapes over the course of the year.

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Publication type Article
Publication Subtype Journal Article
Title Monitoring boreal forest leaf area index across a Siberian burn chronosequence: A MODIS validation study
Series title International Journal of Remote Sensing
DOI 10.1080/01431160500285142
Volume 26
Issue 24
Year Published 2005
Language English
Publisher Taylor & Francis
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Description 19 p.
First page 5433
Last page 5451
Country Russia
Other Geospatial Krasnoyarsk Kray
Online Only (Y/N) N
Additional Online Files (Y/N) N
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