Abstract
Land surface temperature (LST) is a key parameter for land cover analysis and for many fields of study, for example, in agriculture, due to its relationship with the state of the crop in the evaluation of natural phenomena such as volcanic eruptions and geothermal areas, in desertification studies, or in the estimation of several variables of environmental interest such as evapotranspiration. The computation of LST from satellite imagery is possible due to the advances in thermal infrared technology and its implementation in artificial satellites. For example, Landsat 8 incorporates Operational Land Imager(OLI) and Thermal InfraRed Sensor(TIRS)sensors the images from which, in combination with data from other satellite platforms (such as Terra and Aqua) provide all the information needed for the computation of LST. Different methodologies have been developed for the computation of LST from satellite images, such as single-channel and split-window methodologies. In this paper, two existing single-channel methodologies are evaluated through their application to images from Landsat 8, with the aim at determining the optimal atmospheric conditions for their application, instead of searching for the best methodology for all cases. This evaluation results in the development of a new adaptive strategy for the computation of LST consisting of a conditional process that uses the environmental conditions to determine the most suitable computation method.
Highlights
In recent decades, climate change and global warming have become two of the main social, economic, and political concerns, so it is common to see news and scientific articles that show the consequences of these phenomena
The number of methodologies available for the task is constantly increasing, the single-channel methods being the ones most widely used. The reason for the latter is that single-channel methods allow the computation of Land surface temperature (LST) from one image in the thermal infrared band only, provided that a set of additional parameters is previously known or calculated, in such a way that the method can be applied to any satellite with at least one thermal infrared band and is not limited to those sensors including several acquisitions within the band
Existing single-channel methods differ from each other by the procedures applied to obtain the required additional parameters, which can be different for each method, and there is no clear determination of the most precise and accurate method for each situation
Summary
Climate change and global warming have become two of the main social, economic, and political concerns, so it is common to see news and scientific articles that show the consequences of these phenomena. Recent studies have shown that the average surface temperature between 2000 and 2016 was 1 ◦C higher than that obtained between 1975 and 2000 [1] This rise in the average temperature of the earth is one of the main consequences of climate change, which has caused, for example, the increase in the melting rate of the poles and glaciers with a consequent rise in sea and ocean levels [2]. Given the problems caused by global warming, it is logical to look for solutions. In this regard, it is key to identify, geolocate, quantify, and monitor this phenomenon
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