Moderate resolution remote sensing alternatives: a review of Landsat-like sensors and their applications

Scott L. Powell; Dirk Pflugmacher; Alan A. Kirschbaum; Yunsuk Kim; Warren B. Cohen

doi:10.1117/1.2819342

1 November 2007 Moderate resolution remote sensing alternatives: a review of Landsat-like sensors and their applications

Scott L. Powell, Dirk Pflugmacher, Alan A. Kirschbaum, Yunsuk Kim, Warren B. Cohen

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 1, Issue 1, 012506 (November 2007). https://doi.org/10.1117/1.2819342

Abstract

Earth observation with Landsat and other moderate resolution sensors is a vital component of a wide variety of applications across disciplines. Despite the widespread success of the Landsat program, recent problems with Landsat 5 and Landsat 7 create uncertainty about the future of moderate resolution remote sensing. Several other Landsat-like sensors have demonstrated applicability in key fields of earth observation research and could potentially complement or replace Landsat. The objective of this paper is to review the range of applications of 5 satellite suites and their Landsat-like sensors: SPOT, IRS, CBERS, ASTER, and ALI. We give a brief overview of each sensor, and review the documented applications in several earth observation domains, including land cover classification, forests and woodlands, agriculture and rangelands, and urban. We conclude with suggestions for further research into the fields of cross-sensor comparison and multi-sensor fusion. This paper is significant because it provides the remote sensing community a concise synthesis of Landsat-like sensors and research demonstrating their capabilities. It is also timely because it provides a framework for evaluating the range of Landsat alternatives, and strategies for minimizing the impact of a possible Landsat data gap.

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Scott L. Powell, Dirk Pflugmacher, Alan A. Kirschbaum, Yunsuk Kim, and Warren B. Cohen "Moderate resolution remote sensing alternatives: a review of Landsat-like sensors and their applications," Journal of Applied Remote Sensing 1(1), 012506 (1 November 2007). https://doi.org/10.1117/1.2819342

Published: 1 November 2007

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