Pacific Northwest Research Station

Title: High spatial resolution satellite observations for validation of MODIS land products: IKONOS observations acquired under the NASA scientific data purchase.

Author: Morisette, Jeffrey T.; Nickeson, Jaime E.; Davis, Paul; Wang, Yujie; Tian, Yuhong; Woodcock, Curtis E.; Shabanov, Nikolay; Hansen, Matthew; Cohen, Warren B.; Oetter, Doug R.; Kennedy, Robert E.

Date: 2003

Source: Remote Sensing of Environment. 88: 100-110

Description: Phase 1I of the Scientific Data Purchase (SDP) has provided NASA investigators access to data from four different satellite and airborne data sources. The Moderate Resolution Imaging Spectrometer (MODIS) land discipline team (MODLAND) sought to utilize these data in support of land product validation activities with a lbcus on tile EOS Land Validation Core Sites. These sites provide a globally distributed network of sites where field, aircraft, and satellite data are being collected. As much as possible, uniform data sets useful for validation are being made available for the core sites. The globally consistent, high-resolution imagery available from IKONOS are being used for their geolocation accuracy and ability to characterize the landscape at the 1- to 4-m spatial resolution. This paper provides an overview of the MODIS Land Team's validation strategy to incorporate high-resolution imagery and presents three case studies as examples of the use of IKONOS data lbr MODIS land validation activities. We conclude that the globally consistent data from IKONOS, available through NASA's SDE have supplied critical validation data sets at a reasonable cost.

Keywords: MODIS, IKONOS, NASA

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Citation

Morisette, Jeffrey T.; Nickeson, Jaime E.; Davis, Paul; Wang, Yujie; Tian, Yuhong; Woodcock, Curtis E.; Shabanov, Nikolay; Hansen, Matthew; Cohen, Warren B.; Oetter, Doug R.; Kennedy, Robert E.   2003.  High spatial resolution satellite observations for validation of MODIS land products: IKONOS observations acquired under the NASA scientific data purchase..   Remote Sensing of Environment. 88: 100-110