ALBERT

Description: Understanding forest cover changes is especially important in highly threatened and understudied tropical dry forest landscapes. This research uses Landsat images and a Random Forest classifier (RF) to map old-growth, secondary, and plantation forests and to evaluate changes in their coverage in Ecuador. We used 46 Landsat-derived predictors from the dry and wet seasons to map these forest types and to evaluate the importance of having seasonal variables in classifications. Initial RF models grouped old-growth and secondary forest as a single class because of a lack of secondary forest training data. The model accuracy was improved slightly from 92.8% for the wet season and 94.6% for the dry season to 95% overall by including variables from both seasons. Derived land cover maps indicate that the remaining forest in the landscape occurs mostly along the coastline in a matrix of pastureland, with less than 10% of the landscape covered by plantation forests. To obtain secondary forest training data and evaluate changes in forest cover, we conducted a change analysis between the 1990 and 2015 images. The results indicated that half of the forests present in 1990 were cleared during the 25-year study period and highlighted areas of forest regrowth. We used these areas to extract secondary forest training data and then re-classified the landscape with secondary forest as a class. Classification accuracies decreased with more forest classes, but having data from both seasons resulted in higher accuracy (87.9%) compared to having data from only the wet (85.8%) or dry (82.9%) seasons. The produced cover maps classified the majority of previously identified forest areas as secondary, but these areas likely correspond to forest regrowth and to degraded forests that structurally resemble secondary forests. Among the few areas classified as old-growth forests are known reserves. This research provides evidence of the importance of using bi-seasonal Landsat data to classify forest types and contributes to understanding changes in forest cover of tropical dry forests.

Description: This paper provides the first wide-area Interferometric Synthetic Aperture Radar (InSAR) survey of the whole eastern Trans-Mexican Volcanic Belt (42,200 km2). The aims are to identify ground deformation hotspots within major urbanized areas and rural valleys, establish baselines in geothermal exploration sites, and analyze deformation at geothermal exploitation sites and its relationship with energy production. The whole 2003–2010 ENVISAT C-band SAR archive available over the region was processed with the Small BAseline Subset (SBAS) InSAR method to retrieve over 840,000 coherent targets and estimate their ground displacement rates and time series. Land subsidence hotspots due to aquifer drawdown are found within the city of Puebla (up to −53 mm/year vertical rates, groundwater pumping for industrial use), Tlaxcala and Apizaco (−17 mm/year, industrial and public), the valley of Tecamachalco (−22 mm/year, agricultural), Tulancingo (−55 mm/year, public, industrial and agricultural), and in the eastern Mexico City metropolitan area (−44 mm/year, agricultural). The baseline for the Acoculco caldera complex shows widespread ground stability. Conversely, localized subsidence patterns of −5 to −10 mm/year exist around Las Derrumbadas and Cerro Pinto in the Serdán-Oriental basin, due to intense groundwater pumping for agriculture. A well-defined land subsidence area with −11 mm/year maximum rates is found at Los Humeros volcanic complex within Los Potreros collapse, correlating well with energy production infrastructure location and historical steam production rates. Field surveys carried out in Acoculco and Los Humeros in 2018 provide supporting evidence for the identification of hydrothermal manifestations, and understanding of the landscape and surface deformation patterns within the geothermal fields.

Description: Considering the social and ecological obsolescence of the conventional agricultural model and the crisis faced by rural areas, innovative models based on collective initiatives and agroecological practices are emerging. Here, we present the use of a participatory farming lab as a space to reactivate the agrarian sector in rural and periurban areas of Madrid. The specific objectives of this study are: (1) to describe the project; (2) to identify participants’ profiles and motivations and (3) to identify the most socially valued ecosystem services and the actions collectively taken to enhance them. To do so, we have used the living lab conceptual approach and the ecosystem service lens. Data gathering included a combination of qualitative and quantitative techniques, including participant observation, informal and formal meetings, interviews, workshops and surveys. We found a diversity of motivations for enrolling in the program and 20 ecosystem services were selected as socially important. We also describe how the project has contributed to adopting agroecological practices to sustain those ecosystem services. Finally, we discuss the contribution of the project towards new and integrated rural development strategies, including its potential to promote cooperative solutions that enhance farming activity by also providing ecosystem services.

Description: In this paper, we review the potential of high resolution optical satellite data to reduce the significant investment in resources required for a national field survey for producing estimates of above ground biomass (AGB). We use 5 m resolution RapidEye optical data to support a country wide biomass inventory with the objective of bringing to the attention of the traditional forestry sector the advantages of integrating remote sensing data in the planning and execution of field data acquisition. We analysed the relationship between AGB estimates from a subset of the national survey field plot data collected by the Tanzania Forest Service, with a set of remote sensing biophysical parameters extracted from a sample of fine spatial (5 m) resolution RapidEye images using a regression estimator. We processed RapidEye data using image segmentation for 76 sample sites each of 20 km by 20 km (covering 2.3% of the land area of the country) to image objects of 1 ha. We extracted reflectance and texture information from those objects which overlapped with the field plot data and tested correlations between the two using four different models: Two models from inferential statistics and two models from machine learning. The best results were found using the random forests algorithm (R2 = 0.69). The most important explicative factor extracted from the remote sensing data was the shadow index, measuring the absorption of light in the visible bands. The model was then applied to all image objects on the RapidEye images to obtain AGB for each of the 76 sample sites, which were then interpolated to estimate the AGB stock at the national scale. Using the relative efficiency measure, we assessed the improvement that the introduction of remote sensing data brings to obtain an AGB estimate at the national level, with the same precision as the full survey. The improvement in the precision of the estimate (by reducing its variance) resulted in a relative efficiency of 3.2. This demonstrates that the introduction of remote sensing data at this fine resolution can substantially reduce the number of field plots required, in this case threefold.

Description: Obstruction of the racks in bottom intakes due to sediment wedged in the slit of the bars can significantly reduce diverted flow. Notwithstanding the design recommendations that are found in the literature, the problem of rack occlusion continues to occur in built structures. This work focuses on the clogging effects in the circular bars of a bottom rack system using gravels whose median diameter, d50, is close to the spacing between the bars. An experimental campaign including 24 tests, each repeated time times, with six different longitudinal slopes from 0 to 35% and four different specific incoming flow rates, q1, in the range of 0.115 to 0.198 m3/s/m, is presented. The results show the inefficiency of circular profiles in comparison with T-shaped bars. No important influence of rack slope is found that could help to reduce clogging. This works confirms the importance of the selection of bar profile to reduce maintenance labor. A comparison of results with previous works with gravel sediment in T-shaped bars is considered. A methodology to calculate the wetted rack length considering occlusion due to flow with sediment transport is proposed, and the results are compared with those in the bibliography.

Description: Galaxies, Vol. 5, Pages 78: Reheating via Gravitational Particle Production in Simple Models of Quintessence or ΛCDM Inflation Galaxies doi: 10.3390/galaxies5040078 Authors: Jaume de Haro Llibert Aresté Saló We have tested some simple Λ CDM (the same test is also valid for quintessence) inflation models, imposing that they match with the recent observational data provided by the BICEP and Planck’s team and leading to a reheating temperature, which is obtained via gravitational particle production after inflation, supporting the nucleosynthesis success.

Description: This paper proposes a methodology for deriving an agreement map between the Spanish Land Parcel Information System (LPIS), also known as SIGPAC, and a classification map obtained from multitemporal Sentinel-1 and Sentinel-2 data. The study area comprises the province of València (Spain). The approach exploits predictions and class probabilities obtained from an ensemble method of decision trees (boosting trees). The overall accuracy reaches 91.18% when using only Sentinel-2 data and increases up to 93.96% when Sentinel-1 data are added in the training process. Blending both Setninel-1 and Sentinel-2 data causes a remarkable classification improvement ranging from 3.6 to 8.7 percentage points over shrubs, forest, and pasture with trees, which are the most confusing classes in the optical domain as demonstrated by a spectral separability analysis. The derived agreement map is built upon combining per pixel classifications, their probabilities, and the Spanish LPIS. This map can be exploited into the decision-making chain for subsidies payment to cope with the 2020+ European Common Agricultural Policy (CAP).

Description: A novel computational tool, DIMRACK, is presented for the design of the required length of bottom racks in intake systems. The users may consider clear water cases or the rack’s occlusion due to sediment transport in the river. The computational tool uses a methodology based on the experimental works undertaken at the Universidad Politécnica de Cartagena from 2010. This work also presents an extension of the methodology to cover a broad range of void ratios, bar profiles, slopes, and flow rates. Designing nomograms are also proposed. These are two diagrams to allow the approximate graphical computation of the rack length with clear water. In sediment transport cases, an occlusion factor is proposed, obtained from experimental gravel tests. This parameter enables an increment in the rack length due to occlusion, depending on the bar type. The results are compared with those proposed in classical technical manuals. Finally, the results have been compared with ten existing small hydropower plants’ bottom intake designs in Ecuador.

Description: In this study the main results of a detailed analysis of an actual building, which was severely damaged during the Mw 5.1, May 11th 2011, Lorca earthquake (Murcia, Spain) are presented. The dynamic behavior of the building was analyzed by means of empirical and numerical approaches. The displacement response of the building submitted to ambient noise was recorded by using a Real Aperture Radar (RAR). This approach provides a secure remote sensing procedure that does not require entering the building. Based on the blueprints and other available graphical information about the building, a numeric 3D model was also set up, allowing obtaining capacity spectra and fragility curves in the two main resistant directions of the building. The main purpose of this study was to check out the feasibility of the RAR-based method to detect the safety state of a damaged building after an earthquake, without the need of entering unsafe structures. A good consistency of the numerical and experimental approaches and the observed damage was obtained, showing that RAR interferometric-based tools may provide promising supplementary remote sensing methods to safely survey and report about the structural health and the operative conditions of buildings in post-earthquake scenarios.

Description: The expected amplitude of fixed-point sea surface temperature (SST) fluctuations induced by barotropic and baroclinic tidal flows is estimated from tidal current atlases and SST observations. The fluctuations considered are the result of the advection of pre-existing SST fronts by tidal currents. They are thus confined to front locations and exhibit fine-scale spatial structures. The amplitude of these tidally induced SST fluctuations is proportional to the scalar product of SST frontal gradients and tidal currents. Regional and global estimations of these expected amplitudes are presented. We predict barotropic tidal motions produce SST fluctuations that may reach amplitudes of 0.3 K. Baroclinic (internal) tides produce SST fluctuations that may reach values that are weaker than 0.1 K. The amplitudes and the detectability of tidally induced fluctuations of SST are discussed in the light of expected SST fluctuations due to other geophysical processes and instrumental (pixel) noise. We conclude that actual observations of tidally induced SST fluctuations are a challenge with present-day observing systems.