The study of energy, water, and carbon exchanges between ecosystems and the atmosphere is important in understanding the role of vegetation in regional microclimates. However, they are still relatively scarce when it comes to Caatinga vegetation. This study aims to identify differences in the dynamics of critical environmental variables such as net radiation (Rn), evapotranspiration (ET), and carbon fluxes (gross primary production, GPP) in contrasting recovered Caatinga (dense Caatinga, DC) and degraded Caatinga (sparse Caatinga, SC) in the state of Paraíba, northeastern Brazil. Estimates were performed using the Surface Energy Balance Algorithm for Land (SEBAL), and comparisons between estimated and measured data were conducted based on the coefficient of determination (R²). The fluxes were measured using the Eddy Covariance (EC) method for comparison with the same variables derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the Terra satellite. The estimates showed higher Rn values for the DC, indicating that this area should have greater energy availability for physical, biological, and chemical processes. The R² between daily Rn estimates and observations was 0.93. The ET estimated using the SEBAL showed higher differences in relation to the observed values; however, it presented better spatial discrimination of the surface features. The MOD16A2 algorithm, however, presented ET values closer to the observed data and agreed with the seasonality of the Enhanced Vegetation Index (EVI). The DC generally showed higher ET values than the SC, while the MODIS data (GPP MOD17A2H) presented a temporal behavior closer to the observations. The difference between the two areas was more evident in the rainy season. The R² values between GPP and GPP MOD17A2H were 0.76 and 0.65 for DC and SC, respectively. In addition, the R² values for GPP Observed and GPP modeled were lower, i.e., 0.28 and 0.12 for the DC and SC, respectively. The capture of CO₂ is more evident for the DC considering the whole year, with the SC showing a notable increase in CO₂ absorption only in the rainy season. The GPP estimated from the MOD17A2H showed a predominant underestimation but evidenced the effects of land use and land cover changes over the two areas for all seasons.

Cities keep growing, and in most of the cases this expansion process is hard to model and describe for planning actions. Quantitative methods are increasingly used to help planning, monitoring, and regulating urban land-use processes. Remote sensing images series are making possible different types of spatial-temporal analysis of the Earth surface. Surface albedo is a remote sensing product acquired in a long series of satellite images such as Landsat (more than 40 years of observation). Those analyses allow measuring waterproofed areas for urban drainage studies, as well as monitoring urban spreading patterns, growth vectors, and issues related to comfort and environmental quality, as well as about land use and land-use planning (directives for master plans) among others. This article shows the direct applicability of surface albedo changes as an indicator of urban land-cover changes. The current study analyzed the urban area of Petrolina County (PE) in the following periods: 2001 and 2006, 2006 and 2011, and 2011 and 2017. Such analysis uses the surface albedo variation along the time and results showed a strong correlation between increased surface albedo and urban expansion. Besides, it enabled to observe the relation between the high urban growth in the 2011-2017 period and the urban spot expansion by 14% (approximately 590 thousand square meters of territorial extension). The Urban development stood out in the Northern and Southwestern regions of Petrolina County.