Remote Sensing Letters Vol. 4, No. 1, January 2013, 76–84 Geographically weighted modelling of surface salinity in Florida Bay using Landsat TM data ZHIXIAO XIE*, CAIYUN ZHANG and LEONARD BERRY Department of Geosciences, Florida Atlantic University, Boca Raton, FL, 33431, USA (Received 4 January 2012; in final form 9 May 2012) An effective remote-sensing approach is needed for surface salinity monitoring in Florida Bay, a typical estuarine and coastal ecosystem (ECE). Yet, the non-sta- tionary nature of surface salinity makes it difficult to model with conventional regression methods. A geographically weighted regression (GWR) approach was proposed to model surface salinity from Landsat Thematic Mapper (TM) imagery in this study. The models were constructed and validated with spatiotemporally matched field-surveyed salinity and TM imagery collected in February 1999. The GWR models reported high coefficient of determination (R 2 ) values and low root mean square errors (RMSEs) in validation. A 1999 model was also used to hindcast the surface salinity with TM imagery collected in December 1998 and validated with surface salinity collected at that time. The validation reported a reasonably low RMSE. It suggests a GWR approach, with field survey and remotely sensed data, may be useful in modelling and predicting the spatial variation pattern of sur- face salinity in Florida Bay, and could potentially serve as a less costly alternative or a supplement to field survey currently undertaken for salinity monitoring in the coastal areas of the Greater Everglades. 1. Introduction Estuarine and coastal ecosystems (ECEs) contain some of the marine world’s most important ecosystems and represent significant resources for human activities. They are also among the most heavily used and threatened natural systems globally and are the frontier of impacts of climate change and sea level rise. In ECE, salinity is a key physical characteristic as it affects water quality, vegetative communities and most animal species (Marshall et al . 2008). Hence, salinity monitoring and modelling are important in the assessment of ecological resources in Florida Bay (CROGEE 2002), a typical and important ECE in the South Florida, USA. Salinity assessment in Florida Bay currently relies on field observation and salinity modelling. The former includes automatic data collection at gauge stations, as well as field survey. Modelling the spatial and temporal patterns makes it possible to extrapo- late to parts or the entire Florida Bay from these sample points and snapshots. Models can be grouped into either statistic based or mechanistic based (Marshall et al . 2008). The accuracy of these models is limited by the data available to describe patterns of salinity and the driving processes, e.g. little or no salinity data can be collected for the *Corresponding author. Email: xie@fau.edu Remote Sensing Letters ISSN 2150-704X print/ISSN 2150-7058 online © 2012 Taylor & Francis http://www.tandfonline.com http://dx.doi.org/10.1080/2150704X.2012.693218 Downloaded by [Florida Atlantic University] at 13:45 04 June 2012