®®®® SIIA Público

Título del libro: 2011 6th International Workshop On The Analysis Of Multi-Temporal Remote Sensing Images, Multi-Temp 2011 - Proceedings
Título del capítulo: Generation of 250m MODIS LAI time series by temporal regression

Autores UNAM:
RENE ROLAND COLDITZ;
Autores externos:

Idioma:
Inglés
Año de publicación:
2011
Palabras clave:

Leaf Area Index; Me-xico; MODIS; Regression; Vegetation index; Analytical geochemistry; Climate change; Image reconstruction; Radiometers; Regression analysis; Remote sensing; Time series; Vegetation; Time series analysis


Resumen:

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. © 2011 IEEE.


Entidades citadas de la UNAM: