The present paper deals with a wide range of issues related to the environmental quality in learning spaces, such as thermal and visual comfort, as well as energy efficiency. All of these issues fall under the umbrella of the UN Agenda 2030 and Sustainable Development Goals (SDGs). Upon reviewing publications of past studies, interviews were conducted and questionnaires were distributed in public high schools in the province of Alicante, located in the Southeast of Spain. Sixteen high schools were selected for the interviews. Fifteen in the city of Elche, which is the total amount of the high schools in the city. One additional high school that was considered important for this research was included in the study due to the characteristics of the building design, excessively exposed to weather conditions. Significant differences were observed between schools built before 2000 and those built after that date. The latter, surprisingly, not more thermally and visually comfortable or energy efficient. The knowledge gained from our investigation will be of great benefit for architects, designers, engineers, school planners and principals in order to establish stronger connections between infrastructures and SDGs. A chart linking recommendations with specific SDGs is also included in this study.
Water scarcity is a widespread problem in arid and semi-arid regions such as the western Mediterranean coastal areas. The irregularity of the precipitation generates frequent droughts that exacerbate the conflicts among agriculture, water supply and water demands for ecosystems maintenance. Besides, global climate models predict that climate change will cause Mediterranean arid and semi-arid regions to shift towards lower rainfall scenarios that may exacerbate water conflicts. The purpose of this study is to find a feasible methodology to assess current and monitor future water demands in order to better allocate limited water resources. The interdependency between a vegetation index (NDVI), land surface temperature (LST), precipitation (current and future), and surface water resources availability in two watersheds in southeastern Spain with serious difficulties in meeting water demands was investigated. MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI and LST products (as proxy of drought), precipitation maps (generated from climate station records) and reservoir storage gauging information were used to compute times series anomalies from 2001 to 2014 and generate regression images and spatial regression models. The temporal relationship between reservoir storage and time series of satellite images allowed the detection of different and contrasting water management practices in the two watersheds. In addition, a comparison of current precipitation rates and future precipitation conditions obtained from global climate models suggests high precipitation reductions, especially in areas that have the potential to contribute significantly to groundwater storage and surface runoff, and are thus critical to reservoir storage. Finally, spatial regression models minimized spatial autocorrelation effects, and their results suggested the great potential of our methodology combining NDVI and LST time series to predict future scenarios of water scarcity.
A review of vegetation indices as applied to Landsat-TM and ETM+ multispectral data is presented. The review focuses on indices that have been developed to produce biophysical information about vegetation biomass/greenness, moisture and pigments.In addition, a set of biomass/greenness and moisture content indices are tested in a Mediterranean semiarid wetland environment to determine their appropriateness and potential for carrying redundant information.The results indicate that most vegetation indices used for biomass/greenness mapping produce similar information and are statistically well correlated.
Changes in agriculture are associated to the availability of resources and the economic and social demands. One of the more important transformations is to change rainfed into irrigated crops to increase the yield. In most of the cases, water resource and irrigation reservoirs are needed to maintain the yield. However, evaporation from ponds can be an important economic loss and an unsustainable strategy for water management, especially in arid and semiarid regions. Efficient methods for water storage should be established. In this study, a selected area located close to the city of Cartagena (Murcia) and the south of Alicante (Spain) has been studied, where there was an important transformation from rainfed to irrigated crops. Because of the high temperatures and insolation, the increment of the number of reservoirs detected by using remote sensing data and GIS tools may be inefficient for water management. The characterization of these reservoirs, to quantify the potential loss of water due to evaporation, has been done. The use of these tools for analysis could be interesting to find more efficient storage solutions (i.e., better spatial distribution of reservoirs, an increment of depth, and reduction of surface exposure) for improving the water storage and management.
Reservoirs play an important role in water management and are key elements for water supply. Monitoring is needed in order to guarantee the quantity and quality of stored water. However, this task is sometimes not easy. The objective of this study was to develop a procedure for predicting volume of stored water with remote sensing in water bodies under Mediterranean climate conditions. To achieve this objective,multispectral Landsat 7 and 8 images (NASA) were analyzed for the following five reservoirs: La Serena,La Pedrera, Beniarrés, Cubillas and Negratín (Spain). Reservoirs water surface was computed with the spectral angle mapper (SAM) algorithm.After that, cross-validation regression models were computed in order to assess the capability of water surface estimations to predict stored water in each of the reservoirs. The statistical models were trained with Landsat 7 images and were validated by using Landsat 8 images. Our results suggest a good capability of water volume prediction from free satellite imagery derived from surface water estimations. Combining free remote sensing images and open source GIS algorithms can be a very useful tool for water management and an integrated and efficient way to control water storage,especially in low accessible sites.
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