14 December 2017 Estimated net radiation in an Amazon–Cerrado transition forest by Landsat 5 TM
Author Affiliations +
The Amazon–Cerrado transition forest is an extensive region with unique characteristics of radiation exchanges. The measurements of the net radiation (Rn) in this ecosystem are limited to the local scale, and their spatial distribution can be carried out by remote sensing techniques, of which accuracy needs to be evaluated. Thus, the objective of this study was to analyze the accuracy of the model of surface Rn derived from measured solar radiation and estimates of normalized difference vegetation index (NDVI), surface albedo ( α ), and land surface temperature (LST) estimated by images of Landsat 5 TM in an Amazon–Cerrado transition forest. The Rn, NDVI, α , and LST were estimated by Landsat 5 TM images and related to micrometeorological measurements in a tower of the study area. There was seasonality of micrometeorological variables with higher values of incident solar radiation, air temperature, and vapor pressure deficit during the dry season. However, there was no seasonality of Rn. NDVI decreased and α increased during the dry season, while LST was nearly constant. The Rn had negative correlation with α and positive with NDVI. Both instantaneous and daily Rn estimated with Landsat 5 TM images showed high correlation and low error values when compared with Rn measured in the study area.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Heloisa Oliveira Marques, Heloisa Oliveira Marques, Marcelo Sacardi Biudes, Marcelo Sacardi Biudes, Vagner Marques Pavão, Vagner Marques Pavão, Nadja Gomes Machado, Nadja Gomes Machado, Carlos Alexandre Santos Querino, Carlos Alexandre Santos Querino, Victor Hugo de Morais Danelichen, Victor Hugo de Morais Danelichen, } "Estimated net radiation in an Amazon–Cerrado transition forest by Landsat 5 TM," Journal of Applied Remote Sensing 11(4), 046020 (14 December 2017). https://doi.org/10.1117/1.JRS.11.046020 . Submission: Received: 2 August 2017; Accepted: 22 November 2017
Received: 2 August 2017; Accepted: 22 November 2017; Published: 14 December 2017

Back to Top