Generation of 250m MODIS LAI time series by temporal regression

Author

Colditz, René R. ; Llamas, Ricardo M.

Author_Institution

Nat. Comm. for the Knowledge & Use of the Biodiversity (CONABIO), Mexico City, Mexico

fYear

2011

fDate

12-14 July 2011

Firstpage

105

Lastpage

108

Abstract

Vegetation productivity models and many others for hydrology and biogeochemistry studies require biophysical variables such as the leaf area index (LAI). LAI is part of the 13 essential terrestrial variables to monitor climate change. The index can be retrieved by various methods from optical satellite data and is a standard product in the MODIS processing chain at 1km spatial resolution. This study explores the temporal relations between LAI and vegetation indices and applies regression functions to obtain a 250m LAI product.

Keywords

geophysical image processing; radiometry; regression analysis; remote sensing; time series; vegetation; MODIS LAI time series generation; MODIS processing chain; Mexico; biogeochemistry; climate change monitorig; hydrology; leaf area index; optical satellite data; temporal regression; terrestrial variables; vegetation productivity models; Biological system modeling; Correlation; Indexes; MODIS; Spatial resolution; Time series analysis; Vegetation; Leaf area index; MODIS; Mexico; Regression; Time series; Vegetation index;

fLanguage

English

Publisher

ieee

Conference_Titel

Analysis of Multi-temporal Remote Sensing Images (Multi-Temp), 2011 6th International Workshop on the

Conference_Location

Trento

Print_ISBN

978-1-4577-1202-9

Type

conf

DOI

10.1109/Multi-Temp.2011.6005059

Filename

6005059