Validation of Physical Radiative Transfer Equation-Based Land Surface Temperature Using Landsat 8 Satellite Imagery and SURFRAD in-situ Measurements


ŞEKERTEKİN A.

JOURNAL OF ATMOSPHERIC AND SOLAR-TERRESTRIAL PHYSICS, cilt.196, 2019 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 196
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1016/j.jastp.2019.105161
  • Dergi Adı: JOURNAL OF ATMOSPHERIC AND SOLAR-TERRESTRIAL PHYSICS

Özet

Land Surface Temperature (LST) is a key criterion in the physics of the Earth surface that controls the interactions between the land and atmosphere. The objective of this study is to evaluate the performance of physics-based Radiative Transfer Equation (RTE) method on LST retrieval using Landsat 8 satellite imagery and simultaneous in-situ LST data. In order to validate the satellite-based LST, in-situ LST measurements were obtained from Surface Radiation Budget Network (SURFRAD) stations simultaneous with satellite data acquisitions. In the study, four SURFRAD stations (BND, FPK, TBL and GWN) and five images for each SURFRAD station, totally twenty cloud-free images, were used for RTE-based LST validation. RTE method uses the atmospheric parameters acquired from radiosounding data simultaneous with satellite pass; however, these parameters were retrieved from NASA's atmospheric correction parameter calculator since radiosounding data are not available every time. Thus, this situation is another contribution of this study. As a result of the validation process of all data, the statistical measures, namely, coefficient of determination (R-2), Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and RMSE-observations standard deviation ratio (RSR) were calculated as 0.96, 3.12 K, 2.30 K and 0.33, respectively. However, the accuracy of RTE method on LST retrieval increased (R-2 = 0.97, RMSE = 2.17 K, MAE = 1.44 K and RSR = 0.25) after removing TBL station from the analysis, since LST differences in this station were high for all scenes. RSR (ranging from 0 to high positive vlues) is an important measure for model evaluation, and the lower RSR value means high performance of the model. The obtained results revealed that physics-based RTE method is an effective and practical way for LST retrieval from Landsat 8 data despite using interpolated atmospheric parameters instead of radiosounding data.