Tatygul URMAMBETOVA*1
* Corresponding author
1 Kyrgyz State University of Construction, Transport and Architecture, Bishkek, KYRGYZSTAN
E-mail: tatygul_urmambetova@yahoo.com
Pages: 49-58. DOI: 10.24193/JSSP.2017.1.04
Cite: Urmambetova T. (2017), Characterization of Surface Heat Fluxes over Heterogeneous Areas Using Landsat 8 Data for Urban Planning Studies. Journal of Settlements and Spatial Planning, 8(1), 49-58. DOI: 10.24193/JSSP.2017.1.04
Abstract. Land surface temperature (LST) is a key indicator of the Earth’s surface energy and it is one of the important inputs in hydrological, meteorological and climatological applications. It is also important for global change studies and acts as a controlling variable in climatic models. Estimation of LST from satellite thermal infrared radiometer has proven to be very useful. The present work employs temporal Landsat 8 data over Delhi region to characterize the land surface (urban and non-urban) using thermal intensity and sensible heat flux. A full-scene of the Landsat 8 acquired on April 11 and October 20, 2013 (path/146- row/40) of Delhi area and surroundings was used in this study. In pre-processing atmospheric correction was carried out using image based and model based techniques. The pre-processed data was used for land use land cover (LULC) classification by supervised classification method. In the study area, six classes were considered, as follows: Water body; Forest; Agriculture/Park; Bare soil; High density built-up and Low density built-up. The Landsat 8 near infrared and red bands were used to estimate the vegetation index, surface emissivity whereas the thermal bands were employed to calculate land surface temperature using the generalized split window algorithm. In order to have information on heat fluxes over different land surfaces, sensible heat flux was evaluated and stratified over urban and non-urban features. The study reveals that the methodology proves to be suitable to effectively characterize the heterogeneous land surface.
K e y w o r d s: land surface temperature, land use/land cover, NDVI, sensible heat flux