Abstract
Near real time (NRT) remote sensing derived land surface temperature (Ts) data has an utmost importance in various applications of natural hazards and disasters. Space-based instrument MODIS (moderate resolution imaging spectroradiometer) acquired NRT data products of Ts are made available for the users by LANCE (Land, Atmosphere Near real-time Capability) for Earth Observing System (EOS) of NASA (National Aeronautics and Space Administration) free of cost. Such Ts products are swath data with 5 min temporal increments of satellite acquisition, and the average latency is 60-125 min to be available in public domain. The swath data of Ts requires a specialized tool, i.e., HEG (HDF-EOS to GeoTIFF conversion tool) to process and make the data useful for further analysis. However, the file naming convention of the available swath data files in LANCE is not appropriate to download for an area of interest (AOI) to be processed by HEG. In this study, we developed a method/algorithm to overcome such issues in identifying the appropriate swath data files for an AOI that would be able to further processes supported by the HEG. In this case, we used Terra MODIS acquired NRT swath data of Ts, and further applied it to an existing framework of forecasting forest fires (as a case study) for the performance evaluation of our processed Ts. We were successful in selecting appropriate swath data files of Ts for our study area that was further processed by HEG, and finally were able to generate fire danger map in the existing forecasting model. Our proposed method/algorithm could be applied on any swath data product available in LANCE for any location in the world.
Highlights
Remote sensing data acquired by space-based instruments has an utmost importance in monitoring a wide variety of natural and man-made phenomena on the Earth
Ts image was generated for each area of interest (AOI) of our study area from multiple daily MOD11_L2 swath data using our proposed algorithm
moderate resolution imaging spectroradiometer (MODIS) near real time (NRT) swath data files required for an AOI by minimizing the number of files supported by the HEG tool to process it
Summary
Remote sensing data acquired by space-based instruments (i.e., satellite) has an utmost importance in monitoring a wide variety of natural and man-made phenomena on the Earth. Land related imagery products focus primarily on geophysical parameters and processes of the Earth’s surfaces including land and sea surface temperatures, soil moisture, vegetation, and other land covers [2]. These remotely sensed data would be able to analyze the processes involved in Sensors 2020, 20, 984; doi:10.3390/s20040984 www.mdpi.com/journal/sensors. Near real time (NRT) satellite data have been used to monitor and forecast air quality by estimating air pollutants such as aerosols, carbon monoxide (CO), ozone, nitrogen oxides, and sulfur dioxide in the atmospheric composition [3,4,5,6]. Biophysical parameters like stress conditions in vegetation and soil moisture have a relation with surface temperature (Ts) [7], and further involve in causing various natural hazards and disasters including agricultural drought and wildland/forest fires
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