Environ. Sci. Proc., 2021, IECG 2020

The availability of very high resolution (VHR) satellite imagery (<1 m) has opened new vistas in large-scale mapping and information management in urban environments. Buildings are the most essential dynamic incremental factor in the urban environment, and hence their extraction is the most challenging activity. Extracting the urban features, particularly buildings using traditional pixel-based classification approaches as a function of spectral tonal value, produces relatively less accurate results for these VHR Imageries. The present study demonstrates building extraction using Pleiades panchromatic (PAN) and multispectral stereo satellite datasets of highly planned and dense urban areas in parts of Chandigarh, India. The stereo datasets were processed in a photogrammetric environment to obtain the digital elevation model (DEM) and corresponding orthoimages. DEM’s were generated at 0.5 m and 2.0 m from stereo PAN and multispectral datasets, respectively. The orthoimages thus generated were segmented using object-based image analysis (OBIA) tools. The object primitives such as scale parameter, shape, textural parameters, and DEM derivatives were used for segmentation and subsequently to determine threshold values for building fuzzy rules for building extraction and classification. The rule-based classification was carried out with defined decision rules based on object primitives and fuzzy rules. Two different methods were utilized for the performance evaluation of the proposed automatic building approach. Overall accuracy, correctness, and completeness were evaluated for extracted buildings. It was observed that overall accuracy was higher (>93%) in areas having larger buildings and that were sparsely built-up as compared to areas having smaller buildings and being densely built-up. Full article

Sand is a common construction material used for various purposes, e.g., concrete, mortar, render, screed, and asphalt. The usage depends on its fineness, and its fineness is controlled by its mineralogical composition and physical-mechanical properties. This research aims to determine the chemical and mineralogical composition and the physical-mechanical properties of the Dasht-e-Taatrang Zar sand deposits within the Qarabagh and Bagram districts of Kabul and Parwan provinces in Afghanistan. To achieve the objectives of this research, a review of the existing literature has been combined with new extensive field works for macroscopic studies and sample collection, and laboratory analyses. In total, 23 samples during two phases of field works were collected and subjected to lab works for XRF, Schlich, and XRD analysis to determine the chemical and mineralogical composition; moreover, sieve and Atterberg analysis, specific gravity, soundness, and alkali-silica reaction tests were performed for characterization of the physical-mechanical properties of the studied samples. The results of the tests show that the Taatrang Zar sand deposits are considered as a suitable construction material, and due to their simple accessibility, the deposits have high potential as a construction material supplier for the Kabul new city project (Dehsabz) in Kabul and adjacent Parwan and Kapisa provinces. Full article

The correct representation of the topography of terrain is an important requirement to generate photogrammetric products such as orthoimages and maps from high-resolution (HR) or very high-resolution (VHR) satellite datasets. The refining of the digital elevation model (DEM) for the generation of an orthoimage is a vital step with a direct effect on the final accuracy achieved in the orthoimages. The refined DEM has potential applications in various domains of earth sciences such as geomorphological analysis, flood inundation mapping, hydrological analysis, large-scale mapping in an urban environment, etc., impacting the resulting output accuracy. Manual editing is done in the presented study for the automatically generated DEM from IKONOS data consequent to the satellite triangulation with a root mean square error (RMSE) of 0.46, using the rational function model (RFM) and an optimal number of ground control points (GCPs). The RFM includes the rational polynomial coefficients (RPCs) to build the relation between image space and ground space. The automatically generated DEM initially represents the digital surface model (DSM), which is used to generate a digital terrain model (DTM) in this study for improving orthoimages for an area of approximately 100 km². DSM frequently has errors due to mass points in hanging (floating) or digging, which need correction while generating DTM. The DTM assists in the removal of the geometric effects (errors) of ground relief present in the DEM (i.e., DSM here) while generating the orthoimages and thus improves the quality of orthoimages, especially in areas such as Dehradun that have highly undulating terrain with a large number of natural drainages. The difference image of reference, i.e., edited IKONOS DEM (now representing DTM) and automatically generated IKONOS DEM, i.e., DSM, has a mean difference of 1.421 m. The difference DEM (dDEM) for the reference IKONOS DEM and generated Cartosat-1 DEM at a 10 m posting interval (referred to as Carto10 DEM) results in a mean difference of 8.74 m. Full article

Geochemical risk is caused by the release of hazardous chemicals to the earth surface. Primary diamond deposits are located in difficult mining and geological conditions. They represent natural geochemical anomalies associated with the mineral composition of rocks and groundwater, which contain a number of impurity elements with high toxic properties (Tl, Di, As, Cd, Hg), and increased concentrations of heavy metals (Cu, Zn, Pb, Ti, V and others). The paper presents the physical-geographical and mining-geological conditions of the diamondiferous region, where three large mining and processing divisions operate: Udachninsky, Aikhalsky and Nyurbinsky. pH, organic matter (humus), total nitrogen, and physical clay were identified in the study samples, by using potentiometric, photoelectric colorimetric, spectrophotometric methods, and pipette method for particle size analysis. Gross and mobile forms of trace elements were determined by atomic absorption and emission spectrometry. The groups of elements were identified that determined the natural and man-made anomalies. The accumulation of Cr, Ni, and Co determines the influence of kimberlite magmatism in general. Cu, Sr, and Li are accumulated in the soils of the Daldyn-Alakit diamond-bearing region. Increased concentrations of Mn and Cu are typical in the soils of the Sredne-Markhinsky diamond-bearing region. An assessment of the ecological and geochemical state of the study areas was carried out according to the indicator of total pollution (Zc), which is the sum of the excess of the concentration coefficients of chemical elements accumulating in anomalies. Areas of pollution and zones of the greatest risk are localized, which occupy up to 75% of the total area of industrial sites. They confined to quarry-dump complexes and to areas of impact of tailing dumps of processing plants. Full article

Entering the European Union, the Republic of Croatia took over the INSPIRE directive called the National Spatial Data Infrastructure. A large amount of spatial data can be found through the National Spatial Data Infrastructure Geoportal. Data are available for viewing or downloading via different services, such as a web mapping service or web feature service. Although different spatial data are available, it is hard to access useful information through Geoportal. The aim of this paper is to prepare a spatial database which will gather different spatial data related to environmental engineering and present different queries and the visualization of the results. The main data used are related to protected areas in the Republic of Croatia, which register the environmental pollutants, air quality, exploitation and research fields of mineral resources, waste management, water management, and so forth. Alongside the national spatial data, the Copernicus Land monitoring service EU-DEM, the digital elevation model, is used. The classification of Sentinel-2 MSI data is used to provide land cover. Remotely sensed data are used in queries where aspect, slope, and land cover affect the results. Two predefined SQL queries are discussed. The first query discusses the danger of landslides, and the second query discusses threats from illegal landfills and the effect that they have on the environment. Predefined SQL queries enable users to quickly access needed data, even when the original data is updated. All data, databases, visualization, and results are presented in open access software. Full article

The objective of this study is to analyze the capabilities of multi-temporal TerraSAR-X images to estimate the fine-scale SSM variability over bare agricultural plots (at a spatial scale ranging from 80 to 2800 m²). Time series of X-band satellite images were collected over a study site located in Southwestern France, together with intra-field measurements of key soil descriptors (i.e., SSM, surface roughness, and soil texture). The large dataset enables independent training and validating steps of a statistical algorithm (random forest), SSM being estimated using images acquired at low and high incidence angles. The levels of performance obtained at the plot spatial scale, with R² ranging from 0.64 to 0.67 (depending on the considered incidence angle) and an RMSE close to 5.0 m⁻³.m⁻³, are exceeded by those obtained at a finer scale (700 m², corresponding to buffers with a 15 m radius). At this intra-plot spatial scale, the estimates based on the low incidence angle images are associated with an R² of 0.69 and an RMSE of 4.89 m⁻³.m⁻³, results slightly lower than the performance obtained using high incidence angle images, R² of 0.72 and an RMSE of 4.55 m⁻³.m⁻³. Such magnitude of performance slightly increases over larger intra-plot spatial scales, the values of R² being superior to 0.75 with an RMSE lower than 4.20 m⁻³.m⁻³ over areas of 2800 m² (corresponding to buffers with a 30 m radius). Full article

Bangladesh is one of the most vulnerable countries in the world with around 718,000 deaths in the past fifty years. This country is especially in danger for cyclones because of its location in the triangular-shaped Bay of Bengal. The scientific scenario suggests that enlarged sea surface temperature will intensify cyclone movement. Tropical cyclones generate storm surges. Storm surges severely change the coastal environment, damage coastal structures, destroy forests and crops, inundate the coastline with saltwater and cause loss of lives. Due to overcrowding in the mainland in Bangladesh, poor and landless people live on the coast and they face frequent cyclones and associated surges. They affect food and drinking water and there is danger of transmission risks of infectious diseases, such as diarrhea, malaria, eye infections, skin diseases, etc. Some problems following a cyclone are usually created for their low literacy rate and poor knowledge of the environment. The tangible monitoring and warning of cyclones and associated surges should be given more priority for the region. The main objectives of this paper are to highlight the existing activities of the model in storm surges and related areas in the Bay of Bengal. We will explain the progress of a location-specific real-time standpoint prediction system for providing effective and timely surge forecasts. We will also introduce a model through numerical experiments using a severe cyclone in April 1991 to predict the storm surges that will be used to reduce economic losses and the number of deaths during a strong storm surge in the coastal area of Bangladesh. Full article

Water has always been a critical resource for humans and climate change could aggravate supply problems. In this context, groundwater could be an important reservoir of water, especially given the dispersion of places where it can be obtained and the widespread occurrence of surface marks (springs). Historically, places where groundwater is available have been marked by humans using built structures, with stone materials having a major role. These cultural objects tend to become a part of the collective memory and the historical record (when available) and frequently they stay on the original site along time (hence “marking a spot” for groundwater). However, the development of major water supply structures, especially in the 20th century, promoted the negligence of these ancient water sources. We present a general defense of the importance of recording and preserving cultural stone related to water sources, preferably in the original sites. Conservation of groundwater-related structures could help in the future exploration of this geological resource and converge with historical information on the fountains’ discharge, with geological studies of the terrains and geochemical features of the groundwaters involved, in order to characterize the hydrogeological systems and their potential future use (including the preservation of water quality and properties). These studies could promote a synergetic conservation of both heritage and water. Full article

The current COVID-19 pandemic has created havoc in the regular workings of many institutions, such as those dedicated to teaching; therefore, there is an urge for alternatives to traditional face-to-face teaching. However, for certain subjects, such as Earth Sciences, distance-teaching approaches could be seen as counterintuitive to the essential foundations of the subject (where empirical information, especially from fieldwork, is considered paramount for its foundation and growth). In this work, we consider remote operations that could complement, improve, and perhaps even replace the traditional approach for teaching Earth Sciences, potentially producing better learning outcomes, even in relation to laboratory and fieldwork, including studies involving locations outside of planet Earth. Additionally, we consider the possible advantages for other professional settings related to this area, such as those concerning terrain characterization for engineering works, mineral resources, and environmental studies, as well as possible support for space missions and stations in other astronomical bodies (where mineral exploration and extraction could be developed and, hence, benefit from remote operations). Full article

Crystallography concepts are usually among the most demanding subjects for Mineralogy students. Traditional onsite teaching of Mineralogy starts with physical models of crystal polyhedra and frequently also includes the observation of models of crystal structures. These teaching strategies could be difficult to implement under pandemic situations like the present one. But they also have other disadvantages under the usual access conditions as their use by the students is restricted by the number of students in relation to the number of models and by the availability of the models and teaching staff. Additionally, onsite teaching can pose challenges to both students and teachers with temporal or permanent disabilities. We consider here some possibilities of teaching with virtual models of crystal polyhedra, twinning, and crystal structures, based on some of the available freeware options and considering the main concepts taught in the usual Mineralogy syllabus. Full article

Groundwater is considered one of the essential natural resources stored beneath the earth's surface by infiltration through various rock layers. Groundwater potential supplies almost 30% of fresh water globally, and in general, 65% of groundwater is used for agricultural irrigation, 25% as drinking water, and the remaining 10% is utilized as industrial water. This study aimed to delineate potential groundwater zones in the central Antalya province, Turkey, using the analytical hierarchy process (AHP) and frequency ratio (FR). Seven thematic layers, including lithology, slope, drainage density, landcover/land use, lineament density, rainfall, and soil depth, were considered as influencing factors for these models. The preparation of all geospatial datasets was carried out in the GIS environment and Google Earth Engine. Additionally, some authorized relevant web portals were also tried for obtaining the required spatial data. The findings of analysis by AHP and FR models showed that Muratpasa, Kepez, and eastern Dosemealti in the eastern part of the study area are characterized by a high potentiality of groundwater. In contrast, the regions in the southern and the western parts covered by igneous rocks and other less permeable sediments, also featuring high and steep slopes, were also followed by a low or very low groundwater potential. Consequently, the results from both models were assessed using the receiver operating curve (ROC) and area under the curve (AUC) for validation. The validation in this study confirmed the higher effectivity of the results achieved by FR than the AHP model. Full article

The Lorraine–Saar Basin is one of the largest geologically and commercially important Paleozoic coal-bearing basins in Western Europe and has considerable coal reserves in numerous coal beds. The basin stands out due to its sedimentary column of up to 6 km and its inversion, resulting in Paleozoic low-amplitude erosion at around 750 m (French part of the basin) and pre-Mesozoic (Permian) erosion between 1800 and 3000 m (the Saar coalfield or German part of the basin). Thermal maturation of organic matter in sedimentary clastic rocks and coal seams has led to the formation of prolific coalbed methane (CBM) plays in many domains throughout the Carboniferous Westphalian and Stephanian sequences. Coal mines here are no longer operated to produce coal; however, methane generated in “dry gas window” compartments at a depth exceeding 3.5 km has escaped here via several major faults and fracture corridors forming “sweet spot” sites. Faults and a dense network of tectonic fractures together with post-mining subsidence effects also increased the permeability of massive coal-bearing and provided pathways for the breathing of environmentally hazardous mine gases. Nearly all CBM plays can be classified as naturally fractured reservoirs. The Lorraine–Saar Basin is not excluded, indeed, because of the experience of geological surveys during extensive coal-mining in the past. The knowledge of geometrical features of fracture patterns is a crucial parameter for determining the absolute permeability of a resource play, its kinematics environment, and further reservoir simulation. The main focus of this contribution is to gain an insight into the style and structural trends of natural cleat patterns in the basin based on the results of X-ray computer tomography (CT) to ensure technical decisions for efficient exploration of CBM reservoirs. To explore the architecture of solid coal samples, we used X-ray CT of a coal specimen collected from Westphalian D coal from exploratory well Tritteling 1. The studied coal specimen and its subvolumes were inspected in three series of experiments. At different levels of CT resolutions, we identified two quasi-orthogonal cleat systems including a smooth-sided face cleat of tensile origin and a curvilinear shearing butt cleat. The inferred cleat patterns possess features of self-similarity and align with directional stresses. Results of the treatment of obtained cleat patterns in terms of their connectivity relationship allowed the presence of interconnected cleat arrays to be distinguished within studied samples, potentially facilitating success in CBM extraction projects. Full article

Assessment of forest above ground biomass (AGB) is critical for managing forest and understanding the role of forest as source of carbon fluxes. Recently, satellite remote sensing products offer the chance to map forest biomass and carbon stock. The present study focuses on comparing the potential use of combination of ALOSPALSAR and Sentinel-1 SAR data, with Sentinel-2 optical data to estimate above ground biomass and carbon stock using Genetic-Random forest machine learning (GA-RF) algorithm. Polarimetric decompositions, texture characteristics and backscatter coefficients of ALOSPALSAR and Sentinel-1, and vegetation indices, tasseled cap, texture parameters and principal component analysis (PCA) of Sentinel-2 based on measured AGB samples were used to estimate biomass. The overall coefficient (R²) of AGB modelling using combination of ALOSPALSAR and Sentinel-1 data, and Sentinel-2 data were respectively 0.70 and 0.62. The result showed that Combining ALOSPALSAR and Sentinel-1 data to predict AGB by using GA-RF model performed better than Sentinel-2 data. Full article

Wildland fires frequently happen and develop in hard-to-reach regions, fast covering large areas due to the presence of ignitable matters together with beneficial meteorological circumstances. Human actions and natural events are the main reasons for the appearance of wildland fires. Our study focusses on the idea of using natural resources, namely water assets on the fire-affected territory. Since fire suppression is primarily performed with water, the provision of sufficient water sources in the proximity of the burning area is critical. An investigation of the hydrological characteristics of the territory is needed, especially in the driest months, when most of the wildfire events are expected to occur. The construction of a support point for fire-fighting water supplies in the wildland territories is also a requirement for building a network of water assets in the wildland territories. Full article

Change detection (CD) is an essential tool for the accurate understanding of land surface changes using Earth observation data and is extremely important for detecting the interactions between social and natural occurrences in geoscience. Binary change detection aims to detect changes and no changing areas, since improving the quality of the binary CD map is an important issue in remote sensing images; in this paper, a supervised deep learning (DL)-based change detection method was proposed to generate an accurate change map. Due to the good performance and great potential of DL in the domain of pattern recognition and nonlinear problem modeling, DL is becoming popular to resolve the CD problem using multitemporal remote sensing imageries. The purpose of using DL algorithms and especially convolutional neural networks (CNN) is to monitor the environmental change into change and no change classes. The Onera Satellite Change Detection (OSCD) datasets were used to evaluate the proposed method. Experimental results on the real dataset showed the effectiveness of the proposed algorithm. The overall accuracy and the kappa coefficient of the change map using the proposed method is over 95% and close to one, respectively. Full article

One of the numerous fundamental tasks to perform rescue operations after an earthquake is to check the status of buildings that have been destroyed. The methods to obtain the damage map are in two categories. The first group of methods uses data before and after the earthquake, and the second group only uses the data after the earthquakes that we want, to offer a flexible damage map according to information that we are available to achieve. In this paper, we work on VHR satellite images of Haiti and UNet which is a convolution network. The learning algorithm’s profound changes to improve the results were intended to identify the damage of the buildings caused by the earthquake. The deep learning algorithms require training data and that is one of the problems that we want to solve. As well as previous studies examining pixel by pixel degradation, ultimate precision to increase that shows the success of this approach felt and has been able to reach the overall accuracy of 68.71%. The proposed method for other natural disasters such as rockets, explosions, tsunamis, and floods also destroyed buildings in urban areas is to be used. Full article

Cities in the last century have been suffering from the disorderly and unplanned growth of urban centers. Consequently, innumerable environmental problems started to plague these regions, one of them is the alteration of the surface temperature through the generation of heat islands and the urban canyons, caused by the alterations in the natural landscape. Based on OLI and TIRS images from the Landsat 8 satellite, a soil cover map was generated, an image of Surface Temperature (ST) and the NDBI index, which highlight built-up areas, verifying and identifying urban canyon regions of São Paulo. From the results of the correlation of low, medium, and high waterproofing areas generated by the soil cover map with the soil temperature images and the NDBI index, areas of medium waterproofing that had a (ST) similar to the areas of low waterproofing (28 to 31 °C). In this case, the areas of medium waterproofing should resemble the regions of high waterproofing (34 to 37 °C). Such regions have, as a main characteristic, a low index of trees and a greater number of constructions, which causes an increase in temperature (heat islands). In this case, it is observed that the regions of medium waterproofing are influenced by the height and spacing of the buildings, which generate wind corridors and shading of the surface, decreasing the temperature of the region and generating urban canyons. Thus, it is concluded that it is possible to identify regions of urban canyons through multispectral and thermal images. The methodology used allows a diagnosis of the islands of heat islands and urban canyons and to evaluate actions taken in these areas in order to mitigate the problems that such phenomena can cause, mainly related to the population’s climate and health. Full article

In this work, the view of a series of practical research-and-educational activities and mentorship within the institute Research Station of the Russian Academy of Sciences in Bishkek (RS RAS) are presented. STEM learning on-site, specifically related to the Earth sciences, is important. RS RAS in Bishkek is studying geodynamics, stressed and deformed state and deep structure of Tien Shan, seismotectonic, and geoenvironmental and engineering-geological aspects. All field activities have been continued and have been made by special groups of maximum 3 persons. At the RS RAS, a mentorship program within the organization for mentees is introduced. However, COVID-19 quarantine forced us to make mostly online seminars for organization staff and provide online educational training for the students of American University of Central Asia (AUCA) and Kyrgyz Russian Slavic University (KRSU). Under the support of the Rossotrudnichestvo, the agreement on scientific and technical cooperation between the Kyrgyz National University named after Jusup Balasagyn and the RS RAS was signed on 30 September 2020. I admit that the new remote technologies should be included in future development because the accessible geophysical equipment degrades rather quickly and especially because of daily use and temperature changes. Full article

In order to prevent serious damages from a possible earthquake and to determine the possible losses, in settlements under earthquake risk, it is very important to extract building inventory information for further determination of the performance of existing buildings. As conventional methods, such as field investigations, can be time-consuming and costly on an urban scale, approaches that are able to speed up these processes and reduce the costs are required. Determining at least some of the data required to determine the seismic performance of an existing building using alternative methods instead of conventional methods will provide a significant advantage. The study aims to investigate the potential of PlanetScope satellite imagery for extracting building inventory information. Thus, the main objectives of the study are to extract buildings using deep learning methods and to determine the height and the construction period of the buildings. For this purpose, two 3 m PlanetScope satellite images were used over the study area located in Eskisehir, Turkey. Over 30 buildings were located in the study area. The results showed that with PlanetScope Imagery detached buildings can be detected with high accuracy using deep learning methods, their heights can be calculated and the construction period can be determined. For future studies, the obtained information is planned to further be processed in a geographical information system (GIS) for building inventory and to be used for seismic vulnerability assessment studies of existing buildings. Full article

Owing to the effect on people, livestock, and materials, air pollution is a global hazard. To this end, stakeholders have taken on the challenge of quantifying the environment with the use of tools and eventually using the data produced to provide solutions to the problems. However, low-cost sensors and the IoT have come to the rescue due to the high cost and operational complexity of equipment and methodologies in environmental monitoring. They are relatively inexpensive and reliable. It is on this assumption that we have decided to use the World Air Quality satellite data supplied by air matters.com. This study is a 40-day preliminary work in which air quality (AQI, PM_2.5, PM₁₀, NO₂, CO, SO₂, and O₃) and meteorological (temperature, humidity, and wind speed) parameters were monitored. The data collected are for five locations in Lagos State, Nigeria (Ojodu, Opebi, Ikeja, Maryland, and Eti-Osa). The data obtained were subjected to basic descriptive, multivariate and time series statistical analyses. The findings showed that the AQI of all locations presented the levels of contamination as 'Unhealthy for Vulnerable Groups', there were relationships between the parameters monitored and meteorological influences, and the effects of natural and man-made activities may be the sources of the elevated pollutants throughout the locations. Full article

Biosphere Reserves are laboratories of sustainability that provide local solutions to global challenges. They promote research, education and the creation of communities of practice that jointly generate knowledge that may be applicable in decision-making. The context of the global COVID-19 pandemic posed a great challenge to all teaching and learning processes and so to the co-creation of knowledge. In response, we developed an online teaching environment (webinar) to enhance the value of ecosystems and analyze the perception of youth, a key interest group in participatory governance of the territory, in relation to the provision of ecosystem services in the Biosphere Reserve in Indonesia. We took the experience of the Project “Ecosystem Services Assessment of the Basque Country” as a reference and developed a questionnaire on the perception of the provision of local ecosystem services. Our results contribute to establishing a baseline to understand the relationship of youth with the territory and to setting up an international scientific cooperation. This experience showed that the promotion of online solutions can help counteract the negative effects of the global pandemic on teaching and learning processes and also empower local actors in sharing local management in the territory. Full article

This paper aims at addressing the potential of polarimetric indices derived from C-band Radarsat-2 images to estimate the surface soil moisture (SSM) over bare agricultural soils. Images have been acquired during the Multispectral Crop Monitoring (MCM) experiment throughout an agricultural season over a study site located in southwestern France. Synchronously with the acquisitions of the 22 SAR images, field measurements of soil descriptors were collected on surface states with contrasting conditions, with SSM levels ranging from 2.4% to 35.3% m³·m⁻³, surface roughness characterized by standard deviation of roughness heights ranging from 0.5 to 7.9 cm, and soil texture showing fractions of clay, silt and sand between 9%–58%, 22%–77%, and 4%–53%, respectively. The dataset was used to independently train and validate a statistical algorithm (random forest), SSM being estimated using the polarimetric indices and backscatter coefficients derived from the SAR images. Among the SAR signals tested, the performance levels are very uneven, as evidenced by magnitude of correlation (R²) ranging from 0.35 to 0.67. The following polarimetric indices present the best estimates of SSM: the first, second and third elements of the diagonal (T11, T22, and T33), eigenvalues (λ1, λ2, λ3 from Cloude–Pottier decomposition), Shannon entropy, Freeman double-bounce and volume scattering mechanisms, the total scattered power (SPAN), and the backscattering coefficients whatever the polarization state, with correlations greater than 0.6 and with RMSE ranged between 4.8% and 5.3% m³·m⁻³. These performances remain limited although they are among the best SSM estimates using C-band images, comparable to those obtained with other approaches (i.e., empirical, physical based, or model inversion). Full article

In this work, we present a series of educational activities that rely on geological tools to dive into the science of core standards. In this sense, Geology is not the subject to be studied, but the educational resource: we learn with Geology, rather than about Geology. Water is the common element to all activities, and the exploration of Mars (its geology, atmosphere, life conditions, etc.) becomes the engaging background. The primary objective of these activities consists of promoting the basis of scientific reasoning in students. Hence, we tested them with pre-service teachers, in order to investigate their opinions and comments about the strengths and weaknesses of our proposal as regards critical reasoning. Since the activities are so easy to carry out and they could be adapted to an online format, they might become an example of the kind of teaching-learning resources teachers should implement and/or carry out during lockdown conditions. Full article

Groundwater can be considered a non-polluting, renewable energy source. It can be used as a fluid in industrial, commercial, and residential building heating and air-conditioning systems. Usually, the water table is deep enough, so atmospheric conditions have a negligible influence on water temperature. Consequently, annual temperature variations are minor, and groundwater can therefore also be considered a reliable energy source. This paper presents some aspects of groundwater heat pump (GWHP) well design and addresses problems that can occur during their exploitation. The heat pump system consists of two types of well: extraction wells and recharge wells. This paper shows that the distance between the two is a crucial parameter that affects the efficiency of the whole system. An example of well design for a production hall groundwater heat pump is given. The wells were constructed in the northern part of Croatia. Geological and the hydrogeological conditions at the site, regarding water temperature and soil hydraulic conductivity, are highly favorable. Due to insufficient distance between wells, thermal breakthrough occurred, i.e., water temperature in the extraction well rose, which resulted in the lower efficiency of the GWHP system. Full article