Comparative Analysis of Split-Window and Single-Channel Algorithms for Land Surface Temperature Retrieval of a Pseudo-Invariant Target

Abstract

Land surface temperature (LST) acquired from remote sensing observations is essential to monitor surface energy and water exchange processes at the land-atmosphere interface. Most LST retrieval methodologies are developed focusing on Northern hemisphere. Consequently, Southern hemisphere has a great need for investigating the performance of LST retrieval algorithms already consolidated in the literature. In this paper, we compared a Splitwindow (SW) and a Single-channel (SC) method to retrieve LST from Landsat 8 OLI/TIRS images in a dune field, Southern Brazil. To validate the results, the Atmospheric Correction Parameter Calculator (ACPC) tool and Radiative Transfer Equation (RTE) were used. Results demonstrated that both methodologies are in accordance with the RTE, despite they overestimated the LST. Analysis of variance (ANOVA) indicated that the means are not statistically significant (0.05 level). The correlations between LST retrieved and RTE were strong, producing R² of 0.984 and 0.973 for the SW and SC, respectively, and RMSE values of 1.18 and 1.6. SW also exhibited the best values of MSD (±0.983) and Bias (0.773), thus reinforcing its superior performance. SW can be applied with an accuracy of 1.18 K in Southern Brazil, without needing complex modeling or specific radiosonde.

Determining the influence of population density on the land surface temperature based on remote sensing data and GIS techniques: application to Prizren, Kosovo

“…have not yet been calibrated into units (Käfer et al, 2020) that make sense (meaningful units). An important step to be taken is the return to radiance of DNs (Isaya Ndossi & Avdan, 2016).…”

“…In Landsat 8 sensor satellite images, thermal data is stored in the form of digital numbers (DN) (Berila & Isufi, 2021a). These numbers represent cells (pixels) that have not yet been calibrated into units (Käfer et al, 2020) that make sense (meaningful units). An important step FIGURE 4.…”

Mapping summer SUHI and its impact on the environment using GIS and Remote Sensing techniques: A case study on Municipality of Prishtina (Kosovo)

“…In Landsat 8 sensor satellite images, thermal data is stored in the form of digital numbers (DN). These numbers represent cells (pixels) that have not yet been calibrated into units (Käfer et al, 2020) that make sense (meaningful units). After taking satellite images, the first process or task is to return the digital numbers to radiance.…”

SSD Analyze for the Assessment of Long Term Thermal Effect of Urbanization on the Izmir City’s Local Climate Change

“…Since LANDSAT 5 which is the only satellite offering freely available archived data since 1984 provides only one channel thermal band and optical spectral data without missing lines (as being experienced in LANDSAT 7 data), single band LST computation algorithm was preferred to extract LST values from LANDSAT data to analyze LST distribution over the city of Izmir for 32 years. Even if use of a single thermal band from old LANDSAT satellite (or sensor) makes retrieving LST more difficult, it is actually easier than those from multiple thermal bands for example from LANDSAT 8 (Kafer et al, 2020). Qin proposed a single TIR band algorithm using Landsat TM data to map LST distribution (Lu et al, 2009;Feyisa et al, 2016;Qin et al, 2001).…”