Remote estimation of crop gross primary productivity using Landsat and MODIS data

Anatoly A. Gitelson, UNL, agitelson2@unl.edu (Presenter)
Yi Peng, UNL, ypeng2@unlnotes.unl.edu
Toshihiro Sakamoto, Japan, Env. Institute, sakamt@affrc.go.jp
Jeffrey Masek, NASA GSFC, jeffrey.g.masek@nasa.gov
Shashi Verma, UNL, sverma@unlnotes.unl.edu
Andrew E Suyker, UNL, asuyker@unlnotes.unl.edu
John M Baker, UMN, jbaker@umn.edu
Jerry L Hatfield, ARS/USDA, jerry.hatfield@ars.usda.gov
Tilden Meyers, NOAA, tilden.meyers@noaa.gov

The accurate quantification of gross primary production (GPP) in croplands is important for regional and global studies of carbon budgets. The close and consistent relationship between GPP and crop canopy chlorophyll content was established and, thus, vegetation indices related to chlorophyll can be used as a proxy of GPP. In this study, we justified the approach, tested the performance of several widely used chlorophyll-related vegetation indices in estimating total chlorophyll content and GPP in maize and soybeans based on Landsat and MODIS 250 m resolution data collected over AmeriFlux sites in Nebraska, Iowa, Minnesota and Illinois in a period of eight years (2001 to 2008). The results show that GPP can be accurately estimated with chlorophyll-related indices. These indices provide the best approximation of the widely variable GPP in maize and soybean under both irrigated and rainfed conditions.

Presentation Type:  Poster

Session:  Coupled Processes at Land-Atmosphere-Ocean Interfaces   (Mon 4:00 PM)

Associated Project(s): 

• Gitelson, Anatoly: A Satellite-Based Quantification of Carbon Exchange of the Dominant Ecosystems (Maize-Soybean) in the NACP Mid-Continent Intensive (MCI) Region ...details

Poster Location ID: 27