ISPRS-Archives The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Archives Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9034 Copernicus Publications Göttingen, Germany 10.5194/isprs-archives-XLII-4-W4-219-2017 SPATIAL AND TEMPORAL ANALYSIS OF SEA SURFACE SALINITY USING SATELLITE IMAGERY IN GULF OF MEXICO Rajabi S. 1 Hasanlou M. https://orcid.org/0000-0002-7254-4475 1 Safari A. R. 1 School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran 27 09 2017 XLII-4/W4 219 223 Copyright: © 2017 S. Rajabi et al. 2017 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://isprs-archives.copernicus.org/articles/XLII-4-W4/219/2017/isprs-archives-XLII-4-W4-219-2017.html The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLII-4-W4/219/2017/isprs-archives-XLII-4-W4-219-2017.pdf

The recent development of satellite sea surface salinity (SSS) observations has enabled us to analyse SSS variations with high spatiotemporal resolution. In this regards, The Level3-version4 data observed by Aquarius are used to examine the variability of SSS in Gulf of Mexico for the 2012-2014 time periods. The highest SSS value occurred in April 2013 with the value of 36.72 psu while the lowest value (35.91 psu) was observed in July 2014. Based on the monthly distribution maps which will be demonstrated in the literature, it was observed that east part of the region has lower salinity values than the west part for all months mainly because of the currents which originate from low saline waters of the Caribbean Sea and furthermore the eastward currents like loop current. Also the minimum amounts of salinity occur in coastal waters where the river runoffs make fresh the high saline waters. Our next goal here is to study the patterns of sea surface temperature (SST), chlorophyll-a (CHLa) and fresh water flux (FWF) and examine the contributions of them to SSS variations. So by computing correlation coefficients, the values obtained for SST, FWF and CHLa are 0.7, 0.22 and 0.01 respectively which indicated high correlation of SST on SSS variations. Also by considering the spatial distribution based on the annual means, it found that there is a relationship between the SSS, SST, CHLa and the latitude in the study region which can be interpreted by developing a mathematical model.