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Deconstructing the drivers of large-scale vegetation change is critical to predicting and managing projected climate and land use changes that will affect regional vegetation cover in degraded or threated ecosystems. We investigate the shared dynamics of spatially variable vegetation across three large watersheds in the southern Africa savanna. Dynamic Factor Analysis (DFA), a multivariate time-series dimension reduction technique, was used to identify the most important physical drivers of regional vegetation change. We first evaluated the Advanced Very High Resolution Radiometer (AVHRR)- vs. the Moderate Resolution Imaging Spectroradiometer (MODIS)-based Normalized Difference Vegetation Index (NDVI) datasets across their overlapping period (2001–2010). NDVI follows a general pattern of cyclic seasonal variation, with distinct spatio-temporal patterns across physio-geographic regions. Both NDVI products produced similar DFA models, although MODIS was simulated better. Soil moisture and precipitation controlled NDVI for mean annual precipitation (MAP) < 750 mm, and above this, evaporation and mean temperature dominated. A second DFA with the full AVHRR (1982–2010) data found that for MAP < 750 mm, soil moisture and actual evapotranspiration control NDVI dynamics, followed by mean and maximum temperatures. Above 950 mm, actual evapotranspiration and precipitation dominate. The quantification of the combined spatio-temporal environmental drivers of NDVI expands our ability to understand landscape level changes in vegetation evaluated through remote sensing and improves the basis for the management of vulnerable regions, like the southern Africa savannas.

Evapotranspiration (ET) is a variable of the climatic system and hydrological cycle that plays an important role in biosphere–atmosphere–hydrosphere interactions. In this paper, remote sensing-based ET estimates with the simplified surface energy balance index (S-SEBI) model using Landsat 8 data were compared with in situ lysimeter measurements for different land covers (Grass, Wheat, Barley, and Vineyard) at the Barrax site, Spain, for the period 2014–2018. Daily estimates produced superior performance than hourly estimates in all the land covers, with an average difference of 12% and 15% for daily and hourly ET estimates, respectively. Grass and Vineyard showed the best performance, with an RMSE of 0.10 mm/h and 0.09 mm/h and 1.11 mm/day and 0.63 mm/day, respectively. Thus, the S-SEBI model is able to retrieve ET from Landsat 8 data with an average RMSE for daily ET of 0.86 mm/day. Some model uncertainties were also analyzed, and we concluded that the overpass of the Landsat missions represents neither the maximum daily ET nor the average daily ET, which contributes to an increase in errors in the estimated ET. However, the S-SEBI model can be used to operationally retrieve ET from agriculture sites with good accuracy and sufficient variation between pixels, thus being a suitable option to be adopted into operational ET remote sensing programs for irrigation scheduling or other purposes.

The transition to renewable energies is an unavoidable step to guarantee a peaceful and sustainable future for humankind. Although solar radiation is one of the main sources of renewable energy, there are broad regions of the planet where it has not been characterized appropriately to provide the necessary information for regional and local planning and design of the different solar powered systems. The Caribbean, and Cuba in particular, lacked until very recently at least one long-term series of surface solar radiation measurements. Here we present the first long-term records of solar radiation for this region. Solar radiation measurements manually conducted and recorded on paper were rescued, reprocessed and quality controlled to develop the solar radiation climatology at the Actinometrical Station of Camagüey, in Cuba (21.422°N; 77.850°W; 122 m a.s.l.) for the period 1981–2016. The diurnal cycle based on the average hourly values of the global, direct and diffuse horizontal variables for the entire period have been determined and analyzed showing the dependence on solar zenith angle (SZA) and clouds. The annual cycle of global solar component given by the mean monthly daily values presents two maxima, one in April and another one in July with values of 5.06 and 4.91 kWh m−2, respectively (18.23 and 17.67 MJ m−2 per day for insolation), and the minimum in December (3.15 kWh m−2 or 11.33 MJ m−2). The maxima are governed by the direct solar components and are modulated by cloudiness. Both, diurnal and annual cycles of the diffuse solar component show a smoothed bell shaped behavior. In general solar radiation at this station presents a strong influence of clouds, with little seasonal variation but with higher values during the rainy season. Daily global radiation annual averages showed its maximum value in the year 1983, with 17.45 MJ m−2 explained by very low cloudiness this year, and the minimum value was reported in 2009 with a value of 12.43 MJ m−2 that could not explained by the cloud coverage or the aerosols optical depths registered that year. The effects of the 1982 El Chichón and 1991 Mount Pinatubo volcanic eruptions on the solar radiation variables at Camagüey are also shown and discussed. The results achieved in this study shown the characteristics of solar radiation in this area and their potential for solar power applications.

Geothermal energy is becoming essential to deal with the catastrophic effect of climate change. Although the totality of the Earth’s crust allows the exploitation of shallow geothermal resources, it is important to identify those areas with higher thermal possibilities. In this sense, geophysical prospecting plays a vital role in the recognition and estimation of potential geothermal resources. This research evaluates the geothermal conditions of a certain area located in the center of Spain. The evaluation is mainly based on geological and geophysical studies and, in particular, the Time Domain Electromagnetic Method and the Electrical Resistivity Tomography. Once we analyzed the geology and the historical thermal evidence near the study area, our geophysical results were used to define the geothermal possibilities from a double perspective. In relation to anomalous heat gradient, the identification of a fault and the contact with impermeable granitic materials at the depth of 180 m denotes a potential location for the extraction of groundwater. Regarding the common ground-source heat-pump uses, the analysis has allowed the determination of the most appropriate area for the location of the geothermal well field. Finally, the importance of accurately defining the position of the drillings was confirmed by using software GES-CAL.

Forest managers rely on accurate burn severity estimates to evaluate post-fire damage and to establish revegetation policies. Burn severity estimates based on reflective data acquired from sensors onboard satellites are increasingly complementing field-based ones. However, fire not only induces changes in reflected and emitted radiation measured by the sensor, but also on energy balance. Evapotranspiration (ET), land surface temperature (LST) and land surface albedo (LSA) are greatly affected by wildfires. In this study, we examine the usefulness of these elements of energy balance as indicators of burn severity and compare the accuracy of burn severity estimates based on them to the accuracy of widely used approaches based on spectral indexes. We studied a mega-fire (more than 450 km2 burned) in Central Portugal, which occurred from 17 to 24 June 2017. The official burn severity map acted as a ground reference. Variations induced by fire during the first year following the fire event were evaluated through changes in ET, LST and LSA derived from Landsat data and related to burn severity. Fisher’s least significant difference test (ANOVA) revealed that ET and LST images could discriminate three burn severity levels with statistical significance (uni-temporal and multi-temporal approaches). Burn severity was estimated from ET, LST and LSA using thresholding. Accuracy of ET and LST based on burn severity estimates was adequate (κ = 0.63 and 0.57, respectively), similar to the accuracy of the estimate based on dNBR (κ = 0.66). We conclude that Landsat-derived surface energy balance variables, in particular ET and LST, in addition to acting as useful indicators of burn severity for mega-fires in Mediterranean ecosystems, may provide critical information about how energy balance changes due to fire.

An enhanced filter for floating Doppler wind lidar motion correction is presented. The filter relies on an unscented Kalman filter prototype for floating-lidar motion correction without access to the internal line-of-sight measurements of the lidar. In the present work, we implement a new architecture based on two cooperative estimation filters and study the impact of different wind and initial scan phase models on the filter performance in the coastal environment of Barcelona. Two model combinations are considered: (i) a basic random walk model for both the wind turbulence and the initial scan phase and (ii) an auto-regressive model for wind turbulence along with a uniform circular motion model for the scan phase. The filter motion-correction performance using each of the above models was evaluated with reference to a fixed lidar in different wind and motion scenarios (low- and high-frequency turbulence cases) recorded during a 25-day campaign at “Pont del Petroli”, Barcelona, by clustered statistical analysis. The auto-regressive wind model and the uniform circular motion phase model permitted the filter to overcome divergence in all wind and motion scenarios. The statistical indicators comparing both instruments showed overall improvement. The mean deviation increased from 1.62% (without motion correction) to −0.07% (with motion correction), while the root-mean-square error decreased from 1.87% to 0.58%, and the determination coefficient (R2) improved from 0.90 to 0.96.