ArcOLITIRS: A Toolbox for Radiometric Calibration and Surface Temperature Estimation from Landsat 8 Products in ArcGIS Environment

• Published in: Journal of the Indian Society of Remote Sensing Vol. 51; no. 3; pp. 453 - 468
• Main Authors: Arunachalam, M., Joshua, R. Melwyn, Kochuparampil, Ajith Joseph, Saravanavel, J.
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01.03.2023; Springer Nature B.V
• Subjects: absorption; Albedo; Algorithms; Atmosphere; Batch processing; Calibration; Cameras; case studies; Climate change; computer software; digital images; Earth; Earth and Environmental Science; Earth Sciences; Geographic information systems; Graphical user interface; Handbooks; heat; Image processing; India; Land surface temperature; Land use; Landsat; metadata; Metropolitan areas; Population growth; Python; radiometry; reflectance; Remote sensing; Remote Sensing/Photogrammetry; Research Article; Satellites; Sensors; Software; Source code; surface temperature; Temperature; Urban areas; Urbanization; user interface; India; Land surface temperature (LST); ArcPy; Geographic information system (GIS); Radiometric calibration; Semi-automation; Remote sensing
• ISSN: 0255-660X; 0974-3006
• DOI: 10.1007/s12524-022-01636-2

ArcGIS, a leading geospatial software, provides a set of geoprocessing (GP) tools for image processing and raster analysis but lacks advanced image processing and analysis tools specifically for different sensors or camera models offered by other Digital Image Processing (DIP) software like ENVI or ERDAS IMAGINE. To address this gap ArcGIS platform provides an open structure for developers to add their algorithms for advanced image processing by creating custom extensions, tools, or add-ins. Therefore, in the present study, we developed an ArcOLITIRS Toolbox with python script tools for calibrating radiometric measurements and extracting Land Surface Temperature (LST) from Landsat 8 OLI/TIRS Collection-1 (C1) and Collection-2 (C2) products. Tools are demonstrated based on a case study for the Landsat 8 scene (path: 142; row: 51) encompassing Chennai Metropolitan Area (CMA) and its surrounding environments. The reason for selecting this region for the present study is that this area falls in the land-sea interface zone with many natural and anthropogenic processes which cover large LULC types. This region has experienced rapid urbanization and population growth in the last three decades, which led to major changes in land use patterns from natural vegetated surfaces to man-made artificial materials with increased heat absorption that reduces the surface albedo in the urban areas resulting in high LST values. Results of the tools are validated with the Landsat 8 metadata file, C2 Level-2 Surface Reflectance (SR) and Temperature (ST) products from USGS Earth Explorer, NDVI, and different LULC types, and observed the results provide similar results, patterns, and correlation. The tools are implemented as ArcPy script tools, offering complete access to geoprocessing in ArcGIS, an easy-to-use graphical user interface, and support batch processing. The source code is open to the community and extensible for future needs.