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Feasibility of an open-source algorithm for predicting sea surface temperature based on three multi-resolution data sources

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Field Value
 
Title Feasibility of an open-source algorithm for predicting sea surface temperature based on three multi-resolution data sources
 
Creator Rodríguez-Sobreyra, R
Álvarez-Sánchez, L F
Flores-de-Santiago, F
 
Subject Downscaling
Gulf of California
Sub-pixel mapping
Super-resolution mapping
 
Description 284-291
The utilization of space borne platforms for the quantification of Sea Surface Temperature (SST) has brought about a major
shift in the collection of global information. However, the acquisition of SST through satellite images is limited by its coarse
spatial resolution. To address this issue, downscaling algorithms can be implemented to generate matrices with higher spatial
resolution. Current research used the SST data source from the MODIS-Aqua sensor at three distinct spatial resolutions of 9 km,
4.5 km, and 1 km in the Gulf of California, Mexico. The original SST images were then downscaled to 4.5 km, 1 km, 500 m,
250 m, and 125 m per pixel scales using an open-source algorithm. Results indicate a robust linear correlation between the
original SST-MODIS data and the modelled data for all spatial resolutions. This study demonstrates the feasibility of utilizing
an open-source downscaling algorithm to enhance the spatial resolution of SST images in a marginal sea.
 
Date 2024-02-27T07:02:00Z
2024-02-27T07:02:00Z
2024-02
 
Type Article
 
Identifier 2582-6727 (Online); 2582-6506 (Print)
http://nopr.niscpr.res.in/handle/123456789/63467
https://doi.org/10.56042/ijms.v52i06.8349
 
Language en
 
Publisher NIScPR-CSIR,India
 
Source IJMS Vol.52(06) [June 2023]