Split-windows algorithm (swa) methods using fractional vegetation cover (fvc) on landsat 8 oli/tirs

Abstract

Abstract Landsat 8 OLI/TIRS has the ability to generate Land Surface Temperature (LST) with band 10 (10,60 - 11,19 µm) and 11 (11,50 - 12,51 µm). That condition has led to the development of methods for Landsat 8 in LST processing. The SWA has various methods of extracting LST, one using FVC. This research aims to establish the level of accuracy of using FVC methods on SWA methods to ground temperature. LST method is a combination of NDVI and water vapor derived from MODIS Terra. SWA-FVC processing shows a difference between data processing with field conditions. A difference indicated is 2°K (two-degree Kelvin) for urban areas with checks is the road and rooftop. Furthermore, 1°K (one degree Kelvin) for vegetation with middle covered until the high cover of the canopy. SWA-FVC methods have a focus on vegetation index with a similar value of emissivity and can’t to reflect the actual condition of various land-use in the field. LST extraction with SWA-FVC methods proved vegetation index can’t optimum to using for emissivity values for detection LST in the field.