The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-3/W12-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 471–476, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-471-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 471–476, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-471-2020

  06 Nov 2020

06 Nov 2020

SEASONAL ASSESSMENT OF SURFACE TEMPERATURE WITH NORMALIZED VEGETATION INDEX AND SURFACE ALBEDO OVER PAMPA BIOME

P. S. Käfer1, N. S. Rocha1, L. R. Diaz1, E. A. Kaiser1, S. T. L. Costa1, G. Hallal1, G. Veeck2, D. Roberti2, and S. B. A. Rolim1 P. S. Käfer et al.
  • 1State Research Center for Remote Sensing and Meteorology, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
  • 2Dept. of Physics, Universidade Federal de Santa Maria (UFSM), Santa Maria, Brazil

Keywords: Grasslands, NDVI, LST retrieval, Thermal infrared remote sensing, Landsat data

Abstract. Land surface temperature (LST) governs many biophysical processes at the land-atmosphere interface and the relationship vegetation-LST has been the premise of many studies. This paper purposed to correlate LST with normalized difference vegetation index (NDVI) and surface albedo in the grasslands of Pampa biome during winter and summer seasons. Four Landsat 8 scenes with clear-sky conditions were acquired from the US Geological Survey website and NDVI and surface albedo were calculated. Afterwards, LST was obtained using Split-window (SW) algorithm. Results showed that LST in winter season exhibited less variations between pixels in comparison to summer, where the heterogeneity of the environment is significantly more detectable. LST retrieved from Landsat 8 data was consistent with the actual temperature measured in the field, with differences varying between 1–1.6 K. The LST-Vegetation relationship in the Pampa grasslands varies with the season so that caution must be taken in assuming a regular behaviour between LST and remote sensing vegetation variables, such as empirical relationships that are widely used in many scientific fields.