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Proceedings Paper

Comparison of two datasets from two different satellite sensors at @490 nm in the same space-temporal window over the Gulf of California area
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Paper Abstract

The main technical problem that may arise when trying to monitor hydrological ecosystems is that the number of desired images of a region of interest in a specific space-time window is not always available and some of the available images need to be discarded due to insufficient quality which means a considerable decrease in the size of the sample set. For this reason, the number of image samples can be multiplied by the number of satellite sensors that have detection bands in the same spectral range, available in the same space-time window. Prior to this fusion of samples, a comparison is made of the sensors placed in the available satellite platforms to validate the compatibility of them due to the difference in the characteristics of the satellite vehicle, the characteristics of each sensor, and the difference in time when the pictures were taken. In our case, the area of interest is the Gulf of California because it is an enormous biological rich ecosystem, making it an excellent scenario for climate change monitoring. This work also exposes the effect of anomalous data, such as the negative values and those outside the expected range in the images, the reason why they appear and the strategies used to minimize their effect. Finally, the scope and limitations of performing a combined use of the data coming from different satellites, thus increasing the number of available images and thus making more precise estimates of optical parameters of seas and oceans.

Paper Details

Date Published: 21 October 2019
PDF: 10 pages
Proc. SPIE 11149, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI, 1114910 (21 October 2019);
Show Author Affiliations
José Luis Poom-Medina, Univ. de Sonora (Mexico)
José Carlos Jiménez-Escalona, Instituto Politécnico Nacional (Mexico)
Hector Antonio Villa-Martinez, Univ. de Sonora (Mexico)


Published in SPIE Proceedings Vol. 11149:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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