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United States Department of Agriculture

Agricultural Research Service

Research Project: Leveraging Remote Sensing, Land Surface Modeling and Ground-based Observations ... Variables within Heterogeneous Agricultural Landscapes

Location: Hydrology and Remote Sensing Laboratory

Title: Integrating landsat with MODIS products for vegetationn monitoring

item Gao, Feng

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 12/31/2012
Publication Date: N/A
Publication URL:
Citation: N/A

Interpretive Summary:

Technical Abstract: Satellite imagery provides a valuable data source for monitoring vegetation from space. In order to monitor vegetation dynamics and changes, high spatial resolution satellite imagery with frequent acquisition is required. However, current satellite systems cannot satisfy these requirements due to either technical or fiscal difficulties. In recent years, studies have been focused on integrating high spatial resolution Landsat and high temporal resolution MODIS data for vegetation monitoring. This chapter describes three types of approaches to integrate these two data sources. The first approach adopts MODIS algorithms for Landsat data processing. The second approach blends Landsat and MODIS data through a data fusion technique. The third approach normalizes Landsat data using standard MODIS data products. This chapter presents examples and recent applications on the integration of Landsat and MODIS data. Their advantages and limitations are discussed.

Last Modified: 06/23/2017
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