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Proceedings Paper

The effect of land cover type on radar altimeter response and its influence on retracker algorithms
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Paper Abstract

Satellite altimeters on-board Envisat and SARAL (Altika) are routinely used to create virtual monitoring stations from the satellite path crossing with any river of significant width. These virtual stations have the advantage of having a low operational cost and providing near real-time absolute measurement of water level. However, many shortcomings still remain open questions and the precision of measurements can vary widely depending on a number of factors such as the river width and environmental conditions surrounding the water course. In this article we have concentrated our efforts on the relation between land cover classes, the shape of waveforms produced by the backscatter response and the separability among different land cover classes and water. Seven land cover classes often encountered nearby large river banks were analyzed: agriculture, native forest, planted forest, savanna, pasture, urban and open water. Waveforms of these classes were sampled to build a waveform library. They were compared among themselves using cross-correlation, cumulative difference and Kolmogorov-Smirnov distance. Average waveforms for each class were calculated and compared. The results show that only the open water" and forest" classes could be characterized as having a typical behavior, probably caused by the limitations of the measurements used. Furthermore, these two classes have very similar responses and could easily be confused. The other classes generally showed chaotic behavior which can mostly be attributed to variations in their cover characteristics. We expect that a better understanding of the influence of land cover on waveform shapes will increase accuracy of water level measurements.

Paper Details

Date Published: 11 October 2014
PDF: 13 pages
Proc. SPIE 9239, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI, 923905 (11 October 2014); doi: 10.1117/12.2066889
Show Author Affiliations
Eric Oliveira Pereira, Univ. Federal de Minas Gerais (Brazil)
Philippe Maillard, Univ. Federal de Minas Gerais (Brazil)

Published in SPIE Proceedings Vol. 9239:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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