Net radiation (Rn) is a critical variable in estimating energy balance and evapotranspiration by remote sensing techniques on a regional scale. The objective of this paper is to evaluate the effect of estimated and measured instantaneous solar radiation (Rg) and the atmospheric correction of surface temperature by Landsat 8 images on the estimated surface Rn in northern Pantanal. Rn and meteorological factors were measured on a floodplain and on two nonflooded areas in northern Pantanal. Rg was estimated by models proposed by Zillman et al. (RgZillman) and Allen et al. (RgAllen). Surface temperature was corrected by atmospheric and emissivity effects. Annual and seasonal averages of solar radiation were not different among the experimental sites. The floodplain area featured higher net radiation than both nonflooded areas. Instantaneous Rninst estimated by measured Rg and with RgAllen were not different from measured Rninst. Rninst estimated by surface temperature was, on average, 5.7% higher, with a 22% error lower than Rninst estimated with brightness temperature. The current study highlights the possibility of estimating Rninst by RgAllen and the need for correcting the effect of the atmosphere and surface emissivity to estimate surface temperature and Rninst.
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.
During the last decades, the Amazon rainforest underwent uncontrolled exploitation that modified its environmental variables. The current paper analyzes the spatiotemporal dynamics of the normalized difference vegetation index (NDVI), leaf area index (LAI), and surface albedo, and temperature in two different vegetation covers, preserved and deforested areas. We calculated the remote-sensing products using Landsat 5 TM images obtained during the dry season 1984, 1991, 2000, and 2011 of the central region of the State of Rondônia, Brazil. The results showed a reduction of vegetation indexes NDVI (∼0.70 in 1984 to ∼0.27 in 2011) and LAI (∼1.8 in 1984 to ∼0.3 in 2011), with an increase of surface albedo (0.12 in 1984 to 0.20 in 2011) and temperature (∼24°C in 1984 to 30°C in 2011) as the effect of the rainforest converted in grassland during the study period. No changes in any variables were observed in the protected area. Forest conversion into grassland resulted in a decrease of 69% in NDVI and 110% in LAI and a rise of 59% and 24% in albedo and surface temperature, respectively.
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