THERMAL REMOTE SENSING FOR LAND SURFACE TEMPERATURE MONITORING: MARAQEH COUNTY, IRAN Bakhtiar Feizizadeh 1, 2 and Thomas Blaschke 2 1. Centre for Remote Sensing and GIS, University of Tabriz, Tabriz 51368, Iran, Bakhtiar.FeiziZadeh@stud.sbg.ac.at 2. Centre for Geoinformatics, University of Salzburg, Salzburg 5020, Austria ABSTRACT Thermal infrared (TIR) remote sensing allows for the collection, analysis, and modelling of enviro- nmental parameters. It allows to calculating land surface temperature (LST) which is an important factor in many environmental processes including global warming or urban heat islands. In this study the Surface Energy Balance Algorithm for Land (SEBAL) method has been applied to Landsat Enhanced Thematic Mapper (ETM+) imagery for Maraqeh County, Iran. A five step model based on the SEBAL method analyses the spatial variation of LST. The modelled LST values were validated with LSTs measured at the Maraqeh County meteorological station. Differences between modelled and measured LST values were only in the range of 0.6%. Index Term- Land surface temperature, SEBAL, ETM+, Maraqeh County 1. INTRODCTION Land surface temperature (LST) is an important factor for the determination of biophysical parameters and processes including surface energy uxes, particularly evaporation, crop production and near surface air temperature [1]. LST is of great important to the characterization of energy exchange between the ground surface and the atmosphere [2]. When using LST to assess environmental impacts it is beneficial to model the spatial and temporal patterns of regional LST. In the absence of a dense network of land-based meteorological stations, the spatio-temporal distribution of LST values from remote sensing imagery can be used as a parameter to support sustainable management, including water resource management and landscape planning, as well in-depth agriculture and agro-environmental studies. Available satellite thermal infrared sensors provide different spatial resolution and temporal coverage data that can be used to estimate LST [3]. TIR remote sensing data are indispensible to quantify and qualify land surface processes [4]. Two main reasons why TIR data contribute to an improved understanding of land surface processes should be mentioned here: (i) the surface temperature values complement measured point data and can be related to specific landscape and bio- physical components; (ii) surface temperatures can be related to energy fluxes of specific landscape phenomena or processes [5-6]. Various satellite and airborne instruments can record thermal infrared spectra including Landsat TM/ETM+, ASTER and MODIS, AVHRR [1]. One of the major advantages of using Landsat satellite images is that this information, when converted into temperatures, can be used to link directly to other processes (e.g. micro-meteorological) [2]. The main objective of this research is to calculate LSTs for an area in north-western Iran from Landsat ETM+ imagery using the Surface Energy Balance Algorithm for Land (SEBAL) method. 2217 978-1-4673-1159-5/12/$31.00 ©2012 IEEE IGARSS 2012