Changing Salinity as an Indicator of Restoration and Climate Change Impacts on the Greater Everglades
Florida Bay. Image Credit: SFWMD
FAU researchers, Dr. Caiyun Zhang, Dr. Zhixiao Xie and Dr. Leonard Berry, have been assessing salinity changes in the Greater Everglades using remote sensing techniques. The ongoing project explores the potential of the Landsat Thematic Mapper (TM) sensor to monitor salinity in Florida Bay, supporting the Comprehensive Everglades Restoration Plan (CERP) efforts. Remote sensing models have been built for Northeast Florida Bay area first, but eventually for the entire Florida Bay. The results of the initial pilot study indicate that remote sensing has the capability to monitor salinity in the selected study areas and can serve as a supplementary tool to reduce the cost of salinity monitoring programs in CERP.
Previous research (including citations from two resulting journal articles):During the 2011 – 2012 pilot study, researchers investigated the applicability of Landsat remote sensing data for surface salinity monitoring and modeling in Florida Bay. First, the team collected field salinity data surveyed by USGS from the South Florida Information Access (SOFIA, http://sofia.usgs.gov/) and Landsat TM data at the USGS’s Earth Explorer website. Then, they spatially and temporally matched these two datasets with an attempt to find the empirical relationships between surface salinity and TM data. Two study areas were selected: the northeastern Florida Bay, and then the entire Florida Bay. The northeastern bay area is the discharge location of the wide C-111 canal and Taylor Slough carrying a large volume of fresh water into the bay, which makes its water mass different from its surroundings. Florida Bay is a key feature in the Everglades. Salinity monitoring within these two regions is important in CERP. The team tested several models including remote sensing classification methods, multivariate regression analysis models, and geographically weighted regression (GWR) models. Some conclusions are indicated from this project in terms of the applicability of Landsat TM data to salinity monitoring and modeling over the northeastern Florida Bay:
Further experiments for the entirety of Florida Bay demonstrate that location-specific correlations are evident between surface salinity and spectral response in TM data. GWR is proven to be suitable and utilized in modeling and predicting such spatially variable relations. To build an effective GWR model, it seems necessary to perform a principal component analysis (PCA) of the TM data to remove the collinearity between explanatory variables while incorporating as much information from multiple spectral bands. In summary, initial experiments suggest that remote sensing could potentially serve as a less costly alternative or a supplement to field salinity survey currently undertaken in the coastal areas of the Everglades. The research findings were presented in two conferences (SEDAAG 2011, INTECOL 2012) and two peer-reviewed journal articles were published.
Zhang, C., Xie, Z., Roberts, C., Berry, L., & Chen, G. 2012. Salinity Assessment in Northeast Florida Bay Using Landsat TM Data. southeastern geographer, 52(3), 267-281.
Xie, Z., Zhang, C., & Berry, L. 2012. Geographically weighted modelling of surface salinity in Florida Bay using Landsat TM data. Remote Sensing Letters, 4(1), 76-84.