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The middle Holocene saw major changes in political and socioeconomic organization in Peru. Still, not all Peruvian groups transitioned to food production or engaged in mound or monument construction, yet we know relatively little about those who maintained a mobile lifestyle centered on foraging. Using GIS and statistical analyses to interrogate a database of radiocarbon dates, we assess the Peruvian record of forager distributions through the middle Holocene. We identify patterns consistent with biases stemming from disproportionate research attention, regional and intrasite sampling methodologies, and taphonomy that may be hampering our study of middle Holocene foragers. Further confounding our understanding of foragers during this period are reports of middle Holocene radiocarbon gaps attributed to population decline across South America in response to climate-induced scarcity of freshwater and other resources. We show, however, that this might also be an artifact of sampling in some cases and argue for both increased archaeological attention to middle Holocene foragers and greater awareness of perceptual biases that might influence research design and, therefore, research attention and outcomes. [ABSTRACT FROM AUTHOR]

While green hydrogen production technologies like electrolysis have reached commercial scale, the primary challenge centers on efficient, and economically viable transportation of hydrogen. This study proposes an integrated geospatial techno-economic modeling approach to optimize hydrogen transportation through blending in existing pipelines. The simulations strategically locate green hydrogen production and blending points. The paper evaluates blending ratios, flow dynamics, and operating parameters to optimize hydrogen blending in natural gas pipelines. A techno-economic analysis quantifies costs and revenues across the supply chain, identifying the most economically viable hydrogen blending locations. The approach is validated through a case study in Wyoming, providing insights for industry stakeholders considering hydrogen-natural gas blending as a transition strategy. This integrated method offers a robust decision support tool for leveraging existing infrastructure to realize hydrogen's potential as a sustainable energy vector contributing to the broader goal of cleaner energy alternatives. [Display omitted] • Map energy infrastructure to optimize hydrogen production and injection points. • Simulate blending ratios, flow dynamics, and parameters for system optimization. • Perform a cost-benefit analysis to identify optimal hydrogen blending locations. • Validate the model with a Wyoming case study for industry stakeholder insights. [ABSTRACT FROM AUTHOR]

This paper investigates ancient pastoral mobility in a high mountain area of the Pyrenees. Firstly, modern transhumant routes were analysed using GIS tools in order to understand possible determinant factors (such as terrain slope and altitude, water courses and possible nodes) in the layout of a route used for seasonal livestock movements. The observations obtained were then used to model optimal paths which may have been used by ancient shepherds. Subsequently, an analysis was made of the spatial relationship between the simulated paths and the dispersion pattern of archaeological sites in two time periods: Late Antiquity-Medieval (3rd-14th centuries AD) and Modern-Contemporary (18th-20th centuries AD). The results show significant differences in the spatial distribution of the sites throughout both periods in terms of accessibility and proximity to possible pathways. This variability provides information concerning historical changes in the social structure of pastoral alpine landscapes over long periods of time. [ABSTRACT FROM AUTHOR]

This paper focuses on the first human settlement of the Kohgiluyeh region in southwestern Iran in relation to regional environmental conditions. At an altitude between 500 and 3500 m asl, a range of different ecozones and diversified resources available at short distance compose this highly mountainous region. The first sedentary occupation occurred here during the 8th millennium BC. Applying remote sensing, GIS and geo-topographic landscape analyses to contextualize the available dataset, our study illustrates that in the southern portion of the region fertile lands played a pivotal role for the first settled communities and the stability of their subsistence strategies. Farming became even more important during the later Neolithic phase. Furthermore, Neolithic sites are recorded along the bottom of open slopes, at locations with direct access to the combined resources of the plains and the hilly lands. The first occupation of the region is also documented at high elevation up to 1600 m asl, along narrow valley formations, where limited areas are available for farming. [ABSTRACT FROM AUTHOR]

• FFS maps were produced using CTREE, KNN, SVM, RF, GBM and XGBoost algorithms. • The performance of six machine learning techniques was evaluated. • This study will be the first to use the CTREE algorithm for FFS mapping. • XGBoost gave the best results compared to other models. • The most important factor for producing FFS maps in XGBoost models was annual temperature. Antalya is one of the provinces with the highest number of forest fires in Türkiye. In 2021, 278 forest fires occurred within the administrative boundaries of Antalya Regional Directorate of Forestry. The main objective of this study is to produce forest fire susceptibility (FFS) maps of Antalya province using machine learning (ML) models. In addition to forest fire inventory data, 16 factors, including topographic, environmental, meteorological, and human-driven, were used in the study. Inventory data included 2166 fire ignition points from the General Directorate of Forestry. 70 % of the inventory dataset was used to train the ML models and 30 % to validate the models. Overall accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC) approaches were considered as validation metrics. FFS maps of Antalya were produced using stand-alone ML algorithms, K-Nearest Neighbors, and Support Vector Machines, as well as tree-based Conditional Inference Trees (CTREE), Random Forest (RF), Gradient Boosting Machines (GBM), and Extreme Gradient Boosting (XGBoost) algorithms. To the best of our knowledge, this is the first study using the CTREE algorithm for forest fire susceptibility mapping. Therefore, this study is important for the related literature. The validation results revealed that the XGBoost model outperformed other models. It is thought that the FFS map produced using the XGBoost model will guide forest engineers, wildland firefighting teams, and firefighters to minimize damage and control forest fires. [ABSTRACT FROM AUTHOR]

• LULC changes of three decades from 1991 to 2021 were examined and predicted. • Multi-spectral remote sensing data and RFT were utilized to generate LULC maps. • ACR were considered to analyze the categorical land use change detection. • Impervious land has expanded 10 times within 30 years and will increase in the future. The integration of multi-spectral remote sensing and GIS-based analysis is significant for studying land cover changes, providing valuable insights for informed land management and sustainable development. The present study aims to examine land use land cover (LULC) changes of three decades from 1991 to 2021 and predict the future LULC change in Binh Duong province, Vietnam to explore a future research direction on land use change and associated challenges in the study region. Multi-spectral remote sensing data and random forest tree (RFT) were utilized to generate LULC maps. Areal statistics and annual change rate were considered to analyze the categorical land use change detection. Statistical measures such as user's accuracy, producer's accuracy, kappa coefficient, and confusion matrix were employed to assess the accuracy of LULC classification. To predict future LULC and simulate the spatio-temporal change, we considered previous year LULC maps, independent spatial variables and a combined artificial neural network (ANN) multi-layer perceptron approach. The analysis revealed that there was a huge transition from agricultural lands to residential land with industry and commerce which resulting an expansion of impervious lands and a rapid decline of agricultural land as well as of scrub land and barren lands, and a changeability of forest and plantation, croplands, and waterbodies. Our study revealed that the impervious land has expanded 10 times within 30 years and will increase in the future. [ABSTRACT FROM AUTHOR]

The Bekaa Plain in Lebanon, is a major agricultural region known for its fertile soil and extensive crops cultivation using groundwater resources which is recently became under stress due to population growth, urbanization, and climate change. The main aim of this study is to investigate the rate of groundwater recharge (GwR) into this region using APLIS Model which principally depends on altitude, slope, lithology, infiltration, and soil type. Using GIS-based for a multicriteria mapping approach, in this study additional factors were added to the model, by incorporating rainfall rates, stream density, and fracture density. Results revealed various recharge potential area in the Bekaa Plain, with 52 % classified as high to very high GwR zones, equivalent to approximately 42.5 % of precipitated water, which is a testament to the exceptional capacity of the region to replenish groundwater aquifers. The geographic distribution of GwR categories primarily depends on altitude and lithological characteristics. The exceptional GwR potential of the Bekaa Plain holds immense promise for mitigating water scarcity, fostering agricultural productivity, and ensuring the socioeconomic well-being of communities reliant on groundwater resources. [Display omitted] [ABSTRACT FROM AUTHOR]

The increase in water demand and the scarcity of fresh water in arid regions have contributed to the depletion of groundwater. Artificial Groundwater Recharge (AGR) is an advanced strategy that contributes to combating water shortage issues. Limited efforts have been exerted to evaluate and demarcate AGR potential zones in the United Arab Emirates (UAE). The current study aims to delineate AGR potential zone mapping using the traditional analytical hierarchy process (AHP) and a hybrid deep learning model namely, Convolutional Neural Network-Xtreme Gradient Boosting (CNN-XGB) was used for the optimal prediction-based suitability assessment. A total of nine hydrogeological factors were considered for AGR mapping. First, the influence of each parameter was determined based on expert opinion and literature reviews for the AHP approach (0.007 consistency ratio). Second, a hybrid CNN-XGB model (90.8 % accuracy) predicted the AGR and non-AGR classes as part of binary classification and generated an AGR potential zone map. Moreover, the contributing factors were analyzed deeply for the AGR site selection to understand the intercorrelation, importance, and prediction interaction. Using both approaches, a comparative assessment was conducted in the eastern, central, and western parts of Sharjah. The AGR zone based on the CNN-XGB model achieved a precision of (0.8168), recall (0.7873), and F1-score (0.8018). The critical contributing factors for AGR mapping were found to be geology (20%), geomorphology (15%), rainfall (10%), and groundwater level (10%). The AGR map is expected to help explore new sites with potentially higher favourability to retain water, deal with water scarcity, and improve water management in the UAE. [ABSTRACT FROM AUTHOR]

This study observes and records land cover changes in Al-Baha to track urban growth. The study develops a schematic vision of urban mass's current and future shape and distribution and its growth to achieve sustainable urban development, reduce service and social differences between city areas, and integrate urban and rural areas. The study uses inductive methods to monitor urban developments, population growth, and land use through Al-Baha's structural schemes by extracting digital data from satellite imagery to survey historical land cover changes. The mapping software ArcGIS v10.8 processed these digital data and the final map compositions. Through this urban mass study, the research predicted city growth and development. Capabilities and functions must shape urban and rural-urban communities. The development must also consider the National Urban Development Strategy, the relative importance of rural-urban communities, and their expected functional role in influencing the development of small rural communities adjacent to them to reduce migration from rural areas near the city. The study highlighted changes in city land coverage. Al-Baha expanded from 1982 to 1995. Al-Baha's transformation from village to city accelerated, increasing its area from 31 km2 to 44 km2. Many villages beyond 40 were included in the decisions. From 2006–2021, the city's area grew 221%. It increased from 60 km2 to 133 km2 in an urban area, indicating false urban growth. The study stressed the importance of geographic information systems (GIS) and remote sensing (RS). The study recommends urban development in suitable areas because agricultural development is not feasible, especially in the northeast. Land use changes should be prevented by planning regulations because these agricultural areas are essential. Helping urban development move away from agricultural areas, especially on the eastern axis, is crucial. Create new urban centers along Al-Baha's western cliff to attract residents and relieve pressure. Limited linear expansion, especially in the northeast, and more expansive urbanization are also significant. Maps should also show when the Al-Baha region's expansionary scope changed and the urban boundaries that had to be reached by a specific time while development plans were efficiently monitored. [ABSTRACT FROM AUTHOR]

[Display omitted] • Vector species richness is a strong predictor of Chagas disease mortality rates. • The findings give support for the Amplification Effect Hypothesis. • It is important to consider vector diversity when studying vector-borne diseases. Vector species richness may drive the prevalence of vector-borne diseases by influencing pathogen transmission rates. The dilution effect hypothesis predicts that higher biodiversity reduces disease prevalence, but with inconclusive evidence. In contrast, the amplification effect hypothesis suggests that higher vector diversity may result in greater disease transmission by increasing and diversifying the transmission pathways. The relationship between vector diversity and pathogen transmission remains unclear and requires further study. Chagas disease is a vector-borne disease most prevalent in Brazil and transmitted by multiple species of insect vectors of the subfamily Triatominae, yet the drivers of spatial variation in its impact on human populations remain unresolved. We tested whether triatomine species richness, latitude, bioclimatic variables, human host population density, and socioeconomic variables predict Chagas disease mortality rates across over 5000 spatial grid cells covering all of Brazil. Results show that species richness of triatomine vectors is a good predictor of mortality rates caused by Chagas disease, which supports the amplification effect hypothesis. Vector richness and the impact of Chagas disease may also be driven by latitudinal components of climate and human socioeconomic factors. We provide evidence that vector diversity is a strong predictor of disease prevalence and give support to the amplification effect hypothesis. [ABSTRACT FROM AUTHOR]

[Display omitted] The dual use of wind and solar energy holds great promise for low-cost and high-performance green infrastructure. However, for such hybrid systems to operate successfully, comprehensive and simultaneous dimensional planning is required, a goal that single-perspective assessment approaches fail to attain. This paper proposes a novel SpatioTemporal Decision-Making (STDM) model based on Geospatial Artificial Intelligence (GeoAI) for the optimal allocation of onshore wind-solar hybrid plants, with application on a national scale in Iraq. To this end, a wide range of 21 evaluative and restrictive spatial criteria were covered. The temporal synergy factor between renewable resources was considered for the first time in this type of study. Unique global weightings for decision factors were derived using Random Forest (RF) and SHapley Additive exPlanations (SHAP) algorithms supported by sample inventories of wind and solar plants worldwide. Finally, weighted linear combination (WLC) and fuzzy overlay techniques were harnessed in a GIS environment for spatiotemporal suitability mapping of energy systems. According to the RF-SHAP model, the techno-economic criteria demonstrated substantial contributions to the placement of wind and solar systems compared with the socio-environmental criteria. The spatiotemporal suitability map identified three promising opportunities for Iraq at South Dhi-Qar, East Wasit, and West Diyala, with total areas of 780, 2166, and 649 km2, respectively. We anticipate that our findings will encourage government agencies, decision-makers, and stakeholders to increase funding for clean energy transition initiatives. [ABSTRACT FROM AUTHOR]

The process of urbanization is inevitable and its higher rates have been observed in the less developed nations. It has impacted the socio-economic as well as environmental condition of the urban system. The present study intends to demonstrate a methodological framework to utilize the computer applications, like GIS and remote sensing, for analyzing the pattern of urbanization and its impact on the environmental and climatic condition of the study region. The geospatial data has been collected from the satellite imagery and the data pertaining to social and environmental conditions has been collected from the reports obtained from the government agencies. The overlay analysis using GIS has been performed to understand the interactive pattern of the land use and land cover change. Further, the interdependence among variables has been established using regression analysis method. The results of the analysis have been presented using tabulation and graphical methods. [ABSTRACT FROM AUTHOR]

This study aims to analyze the proximity between fast-food restaurant locations and several factors to consider in opening outlets, including public facilities, roads, transportation facilities, community mobility, and distance to industrial areas. The method used in this study is the Weighted Product Method. The Geographic Information System tools are used to obtain location data and perform spatial data settings based on the reference system, as well as calculate the distance matrix between locations. The Weighted Product method is used to provide an assessment analysis regarding the factors to be considered in opening an outlet at a location. [ABSTRACT FROM AUTHOR]

• Erosion and deposition are continuous processes in the Old Brahmaputra River. • Erosion threats to the settlements and surrounding ecosystems. • GIS and RS approaches are used to delineate channel shifting, erosion, and deposition calculation. • The recommended restored channel is expected to reduce riverbank erosion. River meandering causes riverbank erosion, which triggers socioeconomic and environmental issues in the riparian region and raises river sedimentation, thus, needing river restoration. This research depicts a channel restoration model to control river bank erosion and susceptible resource management along the Old Brahmaputra River course based on channel characteristics from 1980 to 2021. The secondary data of Landsat satellite time series and SRTM images were collected from the USGS website, while we used Google Earth images to verify the morphological features. Satellite images were on-screen visualized by ArcMap (10.3) to extract the river channels and measure the erosion and accretion areas. Results showed that the Old Brahmaputra River channel shifted its position due to erosion and accretion. Over the last forty-one years, ∼ 52 km2 area was eroded while ∼ 49 km2 area was accreted, and the average shifting of the river channel was 1.3 km2 per year. Accordingly, the river channel has become more sinuous decade by decade and threatens nearby settlements. Hence, this study proposed a river channel based on previous river channels, where the base channel is from the 2000s, which was more stable and flowed through the middle of the floodplain. Parts of the 1980, 2000, and 2021 river channels were also selected, which are relatively far from the susceptible settlements, to draw the proposed restoring channel. This model is likely to aid in developing government strategies for protecting riverbank erosion and river restoration in the forthcoming period. Finally, this study recommends that this newly proposed channel will be conducive to reducing riverbank erosion and the extreme threat to the settlements and their livelihoods. [ABSTRACT FROM AUTHOR]

Beside the production of hydrogen, the transport is a key component to a successful development of a decarbonized global hydrogen economy. To answer the question, where the required amounts of hydrogen will be produced and along which routes and in which form they will be transported, a sector integrated global hydrogen transport system model needs to be established. This paper provides a flexible method and tool for geographical structuring of sector integrated energy transport systems. It enables the adaptability to existing energy system models and allow for flexible adjustment of the geographical scope. Combined with the integration of pipeline and ship transport it is a novelty, that enables the setup of energy transport systems to perform structured investigation of origin and transport in a future hydrogen economy. The model is validated by comparison with similar studies regarding the directions of hydrogen transport flows. • GIS based method to automate hydrogen transport system development. • Created an accessible and adaptable tool for implementing the method. • Integrated tool with existing energy model, allowing flexible spatial adjustment. • Ensured seamless handover between the tool and energy system modelling framework. [ABSTRACT FROM AUTHOR]

In this paper, wind resource availability was determined by analyzing the meteorological wind energy potential at the hub height of wind turbines. The wind resource potential was identified in specific geographic locations. Technical factors, such as siting requirements and resource availability, were taken into account in the investigation. The economic potential was calculated for each area of Algeria, considering overall losses. Subsequently, the potential for reducing fossil fuel usage was determined through wind to hydrogen estimation. The main components utilized in this work were a Vestas-90 wind turbine (V90–2.0 MW) and an alkaline electrolyzer. The analysis employed a Geographical Information System (GIS) tool. The results demonstrate Algeria's significant potential for wind to hydrogen production, estimated at 1.093 Gt/year without constraints, and reduced to 1.066 Gt/year when considering constraints. The levelized cost of wind to hydrogen production in Algeria varies between 1.51 and 15.37 US $/kg, depending on the chosen wind turbine. The wind to hydrogen production potential identified has the capacity to replace the entire current fossil fuel consumption in the transportation sector, which amounts to 5.28 Mt H 2 /year. The utilization of wind to hydrogen in the transport sector results in a significant reduction of CO 2 emissions, with a calculated avoidance of 45.69 Mt compared to the use of gasoline and diesel. Hydrogen produced from wind energy resources also could be used to support other sectors, including residential, agricultural, and industry in Algeria. • GIS-Based approach is used to evaluate the potential for wind to hydrogen production in Algeria. • The total wind to hydrogen potential in Algeria, when considering constraints, is estimated at 1.066 Gt/year, covering an area of 730,719 km2. • The levelized cost of wind to hydrogen production in Algeria ranges between 1.51 and 15.37 US $/kg, depending on the selected wind turbine (V90–2.0 MW). • The CO 2 emissions avoided in the transport sector are 45.69 Mt compared if the same amount of gasoline and diesel used. [ABSTRACT FROM AUTHOR]

Although equity issues are emphasised in sustainable mobility policy worldwide, there is evidence that cycling planning often prioritises advantaged areas and central zones of cities. To overcome such an inequitable scenario, scholars have called for greater attention towards disadvantaged representatives within the planning and decision-making processes. This study contributes to this debate by exploring the equity impacts of cycling plans and infrastructure allocation in three European cities using a mixed-methods approach. First, through GIS and statistical analysis, we quantitively assessed the equity gap of each cycling plan, measuring the distribution of infrastructure and accessibility gains across socio-economic advantaged and disadvantaged groups. In addition, this study performed an inductive content analysis of each plan to investigate to what extent equity issues are addressed and prioritised in planning practice. The main results suggest the most equitable scenario in a city with a long tradition of cycling planning, which has been providing denser cycling infrastructure to connect important activities and neighbourhoods within central zones and outskirts. Conversely, the implementation of the cycling plan in central areas is likely to overlook disadvantaged socio-economic zones. Despite increasing attention towards accessibility, social inclusion and safety issues within the planning guidelines, findings suggest that the evaluated plans did not prioritise or appraise equity in cycling planning practice. • Providing a dense network in central areas is a common strategy to foster bicycle use. • Disadvantaged groups found in the outskirts are likely to have lower accessibility. • The evaluated cycling plans did not directly prioritise equity issues. • The equity impact of cycling infrastructure provision is overlooked in practice. [ABSTRACT FROM AUTHOR]

Climate changes have exposed many countries to the risks of heavy rains and floods that may lead to the loss of lives and damage to properties. The trend in prioritizing the establishment of stormwater drainage systems in urban areas in Egypt came after the provision and completion of drinking water. This necessitated the implementation of permanent solutions to absorb the unprecedented amounts of rainwater and torrential rain, which were not taken into account when designing the existing sewage networks. Furthermore, there is a lack of water resources and the existing water resources are less than the demand. Therefore, this research study aimed to take advantage of the stormwater that falls on residential neighborhoods by making underground reservoirs or retention ponds to protect these areas from the damage caused by the rains and reusing it in irrigating local green area inside these regions, to achieve sustainable water resources solutions for these areas. Satellite imagery, DEM & ArcGIS are used. A hydrological calculation for 24 different storms, with 4 different return periods for New Cairo City. However, it is the basin of interest that includes public green spaces for rain harvesting and storage for irrigation. For avoiding the risks of heavy rains in a city that hasn't stormwater networks, and get a sustainable solution by using the water from rainfall for irrigation through using sub-areas of some public green spaces such as retention ponds or ground reservoirs, using the runoff volume shall save approximately 6 days of irrigation per storm. [ABSTRACT FROM AUTHOR]

For effective utilization of silica waste discharged from an industrial process for manufacturing synthetic quartz glass, GIS-NaP1 zeolite as an adsorbent for removing Cs+ and Sr2+ from an aqueous solution was hydrothermally synthesized using silica waste as the raw material. The experimental parameters in the hydrothermal process, such as reaction temperature, reaction time and molar ratio of SiO 2 :NaOH:H 2 O, were studied to examine their effects on the formation of zeolites. The samples obtained were characterized by XRD and FE-SEM, and the pore size distribution and the BET surface area were also determined by nitrogen adsorption–desorption. The samples mainly consisted of GIS (NaP1 and NaP2) and ANA (analcime), and the composition varied depending on the synthesis conditions. Under the conditions of a reaction temperature of 140 °C, reaction time of 48 h and SiO 2 :NaOH:H 2 O molar ratio of 1:1.0:39, a NaP1 zeolite sample with small amounts of NaP2 and analcime was successfully obtained. The adsorption kinetics and isotherms for Cs+ and Sr2+ were well described by the pseudo-second-order model and the Langmuir model, respectively. The results demonstrate that the hydrothermal process can effectively transform silica waste into zeolites with good performance for the removal of Cs+ and Sr2+ from aqueous solutions. [Display omitted] • Silica waste from quartz glass manufacturing process was used for zeolite synthesis. • Optimum conditions for hydrothermal synthesis of GIS-NaP1 zeolite were determined. • GIS-NaP1 zeolite effectively removed Cs+ and Sr2+ from aqueous solution by adsorption. • Adsorption process of Cs+ and Sr2+ onto GIS-NaP1 zeolite was analyzed. [ABSTRACT FROM AUTHOR]

The selection of optimal sites for solar based smart hydrogen energy plants (SHEP) requires a spatial evaluation of various conditions, such as technical aspects, economic factors, environmental and social considerations, and as well as the assessment of natural catastrophe conditions within the chosen region. The present study used a multi-criterion decision (MCDA) support model to conduct an optimal site selection analysis for a smart hydrogen energy plant focusing on solar power plants in the Gangwon region of South Korea. Geographic Information Systems (GIS) and big data were utilized to locate and evaluate potential sites for a solar based SHEP project. The evaluation considered 18 sub-factors, including the presence of green energy sources, the demand for hydrogen, existing infrastructure, environmental effect, and the impact of natural disasters. The suitable areas for solar based SHEP installation were identified using a holistic GIS approach by defining appropriate ranks and weights through MCDA. The results showed that 3.74% (627.67 km2) of the study region was very high suitable for constructing solar power plants, particularly in Cheorwon-gun, Chuncheon-si, and Wonju-si regions. The suitability zones determined through the analysis were compared with the global solar plant inventory data, and the results showed good consistency between the two. This suggests that the identified optimal areas can be utilized for the installation of the solar based SHEP. Furthermore, the framework developed in the study can be used to assess the suitable sites for solar energy in other parts of the country. • The issues of identifying the optimal sites for solar-based smart green hydrogen production in South Korea is addresses. • The proposed framework is based on the GIS-MCDA and big data. • Feasibility of sites were assessed based on technical, economic, environmental, and natural catastrophe criteria. • Study shows 3.74% areas suitable for solar power plant construction. • Model validation shows good consistency with existing solar PV installation data. [ABSTRACT FROM AUTHOR]

Remote sensing and GIS technologies help in decision-making processes to reduce pollution and treatment time. In this study, we aim to investigate using remote sensing data in predicting water quality parameters of the Tigris River. Our approach involves the development of mathematical and statistical models that leverage satellite imagery to predict relevant water parameters. Over 2018 and 2019, fourteen different locations along the Tigris River were surveyed. Measurements for eight parameters were collected simultaneously with satellite images at each location. These parameters included temperature (Temp), electrical conductivity, total dissolved solids (TDS), pH, turbidity, chlorophyll A , blue-green algae, and dissolved oxygen. The spectral bands from Landsat 8 images and spectral indices of soil, vegetation, and water were adjusted as a preprocessing step. Spectral bands and indices were then implemented in the least absolute shrinkage and selection operator (LASSO) to predict the eight water parameters. The evaluation of the prediction model showed that the LASSO model has a determination coefficient (R2) of more than 0.8 for pH and Temp, and the minimum R2 of 0.52 was for TDS. It was found that incorporating spectral indices, as additional features in the prediction models, has significantly improved the models' performance, as demonstrated by an average R2 of 0.7 compared to 0.42 when using spectral bands only. The predictive model for each parameter provided cost-effective alternatives to frequent monitoring of Tigris water quality using field data. The predicted parameters were then utilized to calculate the water quality index (WQI) to indicate water quality along the river. The WQI showed that the river had poor water quality during the year except for April and June, which was very poor. This information will be beneficial in enforcing standards and controlling pollution activities in the study region. [ABSTRACT FROM AUTHOR]

Desertification leads to a decline in land production, resulting from biophysical interaction and human factors with temporal and spatial changes. This paper aims to evaluate the desertification sensitivity using Mediterranean Desertification and Land Use (MEDALUS) approach in the Northwestern El Minya Governorate in Egypt. The study area is one of the promising and important areas for land reclamation and developmental projects. Four indicators; climate, vegetation, management, and soil, were used in this study. Landsat 8 (OLI) satellite image 2021 was processed to calculate NDVI index to assess vegetation quality index. Then, it was classified into land cover classes to calculate the management quality index. ASTERDEM satellite data and the climate data were used in the climate quality index. Seventy soil samples were collected and analyzed for chemical and physical properties to be used for the retrieval of soil quality index. These indicators were integrated and used as input criteria in the model of desertification sensitivity. The physiographic unit extraction indicated that significant landforms were included in the study area namely; Old wadi Sediments, Peniplain, old river terraces, Shoulders, Sand sheets, Rock outcrops, and Sand dunes, Erosional Plains, Hill and Plain out wash. The obtained results showed that the severely sensitive area to desertification was represented by 86.7 % of the study area. The main factors affecting the sensitivity were climate conditions (arid, semi-arid), low soil quality and management in addition to the low vegetation cover. Furthermore, about 3% of the study area was located in the moderate sensitive class while the low sensitive area exhibits 1.06 %. Present study supports decision makers to reduce the constraining environmental conditions. [ABSTRACT FROM AUTHOR]

In recent years, rainfall-induced floods in various Egyptian towns affected several regions, and the area in east Cairo was the worst. The present study aims to detect the rainfall-runoff relationships of the Heliopolis watershed and its sub-basins, to estimate peak discharge and flood volume for the storm event (12 March 2020) and predicting the runoff volume and peak discharge of the flows for various return intervals. This was achieved by applying the Hydrological models (HEC-1and HMS) program using a unit Hydrograph namely SCS-CN. The drainage system and the identification of sub-basins were established using SRTM DEM, 90 m resolution. The maximum daily rainfall per year was investigated and determined for various return times using the statistical analysis tool Hyfran. Results reveal that the peak discharge (Qp) and flood volume value (Qv) of the Heliopolis watershed are 686.8 m3/s and 48039.8 m3, respectively. The obtained results for the various recurrence times during the regression periods of 5 and 100 years, reveal that the peak flood inflow of the Heliopolis basin ranged between 19.47 and 742.16 m3/s and the flood volume ranged between 1,295,110 and 53,752,968 m3. This shows that these valleys move a significant volume of water to be released into the mainstream. The recognition and forecasting of the degree of dangerous rain events can help planners and decision-makers in finding flooded areas before the future development of the new settlements. [ABSTRACT FROM AUTHOR]

Litchi (Litchi chinensis) plantations in new areas without any land suitability assessment putting small farmers at risk of economic loss. The unique capability of the Geographical information system (GIS) for integration, analysis, and interpretation of spatial data has been leveraged for the identification, and mapping of potential litchi cultivation zones in India to help farmers and policymakers make informed decisions. Five climate-derived parameters including the number of days per year having a minimum temperature <12 °C (CumD-Tmin < 12), number of days per year having a minimum temperature <0 °C (CumD-Tmin < 0), number of days per year having a mean temperature <20 °C (CumD-Tmean < 20), highest daily maximum temperature (°C) (Thmax) and average annual rainfall (mm), and eight soil parameters viz. soil depth, clay content, slope, stoniness, drainage conditions, pH, electrical conductivity (EC), organic carbon were identified as suitability parameters. Geospatial data at a grid 0.1° × 0.1° of all the identified climate parameters and spatial layers of eight soil data were analysed using Arc-GIS 10.2. The analytical hierarchy process (AHP) was used for assigning relative weightage to the suitability parameters. Using the weighted sum of feature layers, a climate suitability map, a soil suitability map and finally a litchi cultivation potential zones (LCPZs) map were developed. The northward shift of the suitability zone is indicated under climate change projections. The new approach of identifying suitability parameters in relation to the plant's requirement and its integration in GIS using AHP can be extended to other crops and regions. [ABSTRACT FROM AUTHOR]

[Display omitted] • An explainable machine learning was used for the first time for earthquake probability mapping. • Random forest and neural network models were implemented based on SHAP explanation model. • SHAP was implemented for the first time in Indian sub-continent for earthquake probability mapping. • Explainable ANN accurately illustrates the underlying physical processes. Machine learning (ML) models have been extensively used in several geological applications. Owing to the increase in model complexity, interpreting the outputs becomes quite challenging. Shapley additive explanation (SHAP) measures the importance of each input attribute on the model's output. This study implemented SHAP to estimate earthquake probability using two different types of ML approaches, namely, artificial neural network (ANN) and random forest (RF). The two algorithms were first compared to evaluate the importance and effect of the factors. SHAP was then carried out to interpret the output of the models designed for the earthquake probability. This study aims not only to achieve high accuracy in probability estimation but also to rank the input parameters and select appropriate features for classification. SHAP was tested on earthquake probability assessment using eight factors for the Indian subcontinent. The models obtained an overall accuracy of 96 % for ANN and 98 % for RF. SHAP identified the high contributing factors as epicenter distance, depth density, intensity variation, and magnitude density in a sequential order for ANN. Finally, the authors argued that an explainable artificial intelligence (AI) model can help in earthquake probability estimation, which then open avenues to building a transferable AI model. [ABSTRACT FROM AUTHOR]

The global concern about water quality in coal mining operations is a significant issue. It presents detrimental water-related threats, including pollution, acid mine drainage, and habitat destruction. In this study, an attempt has been made to evaluate the water quality for domestic, irrigation and industrial purposes in the coal mining province of Mahan catchment area, with a particular focus on the impact of coal mining activities. 50 samples from pre-monsoon season of 2018, collected from dug well, tube well, mine water and river water were analyzed. The findings indicate that water in the study area exhibits acidic characteristics, with pH values below the desirable range for drinking water. Elevated electrical conductivity, total dissolved solids, sulphate, total hardness and chloride concentrations are observed, particularly around core mining regions. For irrigation suitability, the study reveals that most of the samples are suitable, based on parameters such as sodium percentage (Na%) sodium adsorption ratio (SAR), magnesium hazard (MH), Kelly's index (KI), permeability index (PI), and residual sodium carbonate (RSC). However, majority of the samples collected from core mines show an elevated range of Na% (>80), SAR (>60), MH (>50), KI (>1), PI (>100), RSC (>2.5) and PS (>5) indicating potential soil permeability issues and crop damage, which restrict its suitability for agricultural use. Furthermore, the assessment of water for industrial suitability by analyzing the scaling and corrosion indices, such as the Langelier index (LI), aggressive index (AI), Ryznar index (RI), Puckorius index (PI), and corrosivity ratio (CR) highlights the presence of a corrosive tendency in majority of the water samples, particularly in the mining areas. [ABSTRACT FROM AUTHOR]

Although a large number of studies have tried to explore the relationship between built environment and pedestrian crash severity in developed countries, there is a lack of similar studies in the context of developing countries. Methodologically, the contributory factors influencing pedestrian crash severity are commonly identified through global logistic regression (GLR) models. However, these models are unable to capture the spatial variation in the relationships between the dependent and independent variables. The local logistic regression model, such as geographically weighted logistic regression (GWLR), can potentially overcome this issue. The application of local logistic regression to model pedestrian crash severity is absent in the literature. Therefore, this study aimed to apply the GWLR technique to explore spatially heterogeneous relationships between natural and built environment-related factors and pedestrian crash severity in Dhaka, the capital city of a developing country: Bangladesh. First, using secondary pedestrian crash data, a GLR model was developed to identify significant contributory factors influencing pedestrian crash severity. Results of the model showed that the probability of fatal pedestrian crash occurrence increased at night, in unlit locations, and during adverse weather conditions. In addition, the likelihood of a fatal crash decreases when medians exist on roads and around institutional land use. Also, the chance of fatal crashes increased on straight and flat roads and at locations with more bus stops. Finally, this study explored spatial variation in the effect intensity of these significant variables across the study area using the GWLR technique. High intensity variation across the study area was found for road geometry and institutional land use factors. On the other hand, low intensity variation was found for light conditions and the presence of median factors. This technique can be applied in any area, and the results would help provide insights into the spatial dimension of traffic safety. • Identify natural and built environment factors influencing pedestrian crash severity in Dhaka, Bangladesh. • Application of geographically weighted logistic regression (GWLR) model for exploring spatially heterogeneous relationships. • Fatal crashes were likely to occur at night, in unlit locations, and during adverse weather conditions. • Fatal crashes were less likely to occur when medians exist on roads and around institutional land use. • The likelihood of fatal crashes increased on straight and flat roads and at locations with more bus stops. [ABSTRACT FROM AUTHOR]

The complexes of historic timber-structure buildings are extremely complicated and have various fire threats. A targeted approach to fire risk assessment of historic timber structures is conducive to focused fire plans. Due to the sparsity of the historical fire event dataset, it is quite challenging to predict the fire risk of heritage buildings based on historical fire events data. In this study, a fire risk index-driven solution is proposed based on machine learning to predict the fire risk level of timber heritage buildings. The suggested fire risk index system emphasizes the specificities of timber and historic structures, and the indicators are processed on temporal, spatial, and attribute scales. Considering the uncertainty of fire risk, this approach objectively rates the historical fire risk of heritage buildings using entropy-weighted TOPSIS. The typical machine learning model, XGBoost, is enhanced by applying the spatially unique values to predict the monthly fire risk level of a single heritage building. It solves the issue that general models only take into account the attribute characteristics of heritage buildings. Through the proposed solution, the monthly fire risk level of the heritage buildings of the Palace Museum of China in 2019 was assessed by the XGBoost model using the fire risk index data of the historical years (2016–2018). The accuracy evaluation showed that XGBoost performed better than other models (GBDT, CatBoost, Adaboost, and SVM), which is expected to provide information support for the safety inspection work of the fire department in the Palace Museum. [ABSTRACT FROM AUTHOR]

Orthometric heights are important for various applications such as GIS, geomatics, engineering, and geoscience. The ellipsoidal heights can be computed by Global Navigation Satellite System (GNSS) as an accurate, rapid, and efficient method for height determination. The accurate geoid is essential to convert the ellipsoidal heights from GNSS to orthometric heights. The research developed a new geoid called "KW-FWGM2022″ specifically for Kuwait. We used a composite global geopotential model from SPW R5 with EGM2008 and the digital elevation model from SRTM1. The Wong and Gore modified with Airy-Heiskanen topographic-isotactic reduction were used to compute the geoid model. To assess the accuracy of the KW-FWGM2022 geoid, GNSS/leveling stations were used and the assessment showed that the model's accuracy was better than 1.8 cm as a standard deviation. This demonstrates that the KW-FWGM2022 geoid model is highly accurate and suitable for use in various GIS and Geomatics applications in Kuwait. [ABSTRACT FROM AUTHOR]

The land use and land cover study (LULC) play an essential role in regional socio-economic development and natural resource management to develop sustainable development in vegetation changes, water quantity and quality, land resources, and coastal management. This study uses remote sensing data to investigate LULC in the Northern Border Region (NBR) in the Kingdom of Saudi Arabia. The purpose of this study is to obtain a better understanding of the patterns and drivers of changes in LULC in the NBR over the past three decades. Remote sensing data from Landsat imagery between 1990 and 2022 were used to classify LULC types, and a time series analysis was performed using Landsat imagery to detect changes over time. The classification finds four main classes: bare land, built-up area, rocks, and vegetation. The results indicate a significant increase in urban development. The outcomes revealed that most urbanization occurred in the outskirts of the cities, where previously there were bare soil lands. The main drivers of urbanization were population growth and economic development. These findings have important implications for city planning, the management of green spaces, and the sustainable development of cities. Maximum Likelihood classifier was used to perform the classification. The accuracy assessment demonstrated satisfactory results, with an overall accuracy of 92.6%. The study paves the way for further monitoring LULC changes in the NBR geographic location. The technique used was adequate to address the objectives of this study. [ABSTRACT FROM AUTHOR]

Renewable energy development and more specifically Wind Farm (WF) installation has been increased during the last years by most countries. A discipline that has been studied thoroughly is the impact of wind turbines on installation locations, during energy production or at the end of their life. Citizens' attitudes, social and environmental factors are among the criteria affecting the selection of WFs installation locations. Various machine learning tools have been used in order to analyze the allocation of the Renewable Energy Systems (RES). In this paper a methodology based on computational geometry and Geographical Information Systems (GIS) is proposed in order to cluster the locations of Wind Turbines (WT) and define the boundaries of the areas that are affected by them. Delaunay Triangulation is selected as the main algorithm, since it is appropriate for handling geospatial data and it uses a geometric approach. Furthermore, algorithms based on graph theory are proposed in order to improve the efficiency of the methodology. The proposed methodology was implemented in locations of WTs in Greece and was compared to other known clustering algorithms. It was found that the locations of WTs in Greece are separated into 158 clusters. Some characteristics of the areas defined by the clusters, such as the distance from the protected areas, the distance from the closest airport and the number of residential areas that are within them, were computed and it was shown that these areas can be separated into 4 groups. The application aims to help policy makers to improve the effectiveness of their decisions by understanding in a better way which areas are more impaired or beneficial by the installation of WFs. • This study deals with the Wind Farm installation problem for an entire country. • Wind Farm locations in Greece are clustered into 158 clusters. • The areas that are more beneficial or impaired by wind turbines are determined. • The mean number of residential areas per cluster is equal to 6. • 79 out of 158 clusters do not contain any residential area. [ABSTRACT FROM AUTHOR]

The streamflow has sensitivity to precipitation and temperature changes, the flow rates of the subbasins with higher elevations are higher than the flow rates of the subbasins with lower elevations. Changes between precipitation elasticities and runoff coefficients were compared, flow and temperature changes were compared on the chart. There is no correlation between precipitation elasticities and runoff coefficients, streamflow increases and decreases in the same direction with precipitation but inversely with temperature. [Display omitted] • We studied the runoff coefficient and precipitation elasticity together to develop a new perspective on Upper Murat River Basin. • The main source of uncertainty in water supply projects is accurately predicting the rate of the flow parameter. • Linear regression analysis and Mann-Kendall trend test were applied to detect trend in hydrological and meteorological data. • While temperatures have increased in most part of the basin, precipitation and flow have not decreased at the same rate. • Due to the effect of change in temperature, the rate of change in precipitation differs from the rate of change in flow. This study was carried out to examine rainfall-runoff relationship in the Upper Murat River Basin in Turkey. Murat River Basin, which forms the study area, includes Tunceli, Muş regions and Upper Murat within the Upper Euphrates in Eastern Anatolia, forms the southern branch of the upper basin of the Euphrates River and corresponds to the Middle Euphrates section. Previous studies were carried out for entire Murat River Basin. The novelty of this study is that it focuses on Upper Murat Basin, and gives a different perspective to rainfall-runoff relationship by considering precipitation elasticity in addition to the existing studies. To figure out the basin characteristics, geographic information system based on digital elevation model was used. Annual mean flow records of four flow observation stations (1969–2019), annual total precipitation records and mean temperature records of seventeen meteorological observation stations (1964–2019) were used in the analyses. Rainfall-runoff and temperature-runoff relationship are shown on the graph. Trend analyses were performed by linear regression and Mann-Kendall trend test. Flow parameters were determined for all sub-basins and entire Upper Murat River Basin. The rational method and Thiessen polygons were used to determine flow coefficients. Besides, precipitation elasticities were determined by using elasticity equation to determine the sensitivity of streamflow to climate changes. Determining trends in precipitation, streamflow and temperature values, determination of flow coefficients and precipitation elasticities enabled a comparative rainfall-runoff analysis of the basin. Although there is no exact correlation between the results compared, a new perspective on the basin is presented. Runoff coefficients of sub-basins change between 0.42 and 0.72. Runoff coefficient for entire upper basin is 0.49. In precipitation elasticities, the values calculated for relevant sub-basins for last forty years change between 0.24 and 0.56. Precipitation elasticity for entire upper basin is 0.66. According to the results of the trend analysis, an upward trend was detected in precipitation at 2 stations, a downward trend at 3 stations, an upward trend was detected at 9 stations in temperatures, and a downward trend at 1 station in flows. [ABSTRACT FROM AUTHOR]

• A novel method is proposed to find the suitable locations for large-scale PV farms. • The method ranks suitable locations by determining sequential optimum locations. • Criteria weights are adjusted based on PV plant capacity. • The land of cost is included as a criterion in the decision process. Effective and sustainable climate-friendly policies to reduce carbon dioxide emissions in line with the 2020 European Green Deal are necessary. Accordingly, renewable energies assumed a critical role, rendering the site selection of these systems very crucial. The present study proposes a novel approach to the site selection of large-scale photovoltaic (PV) plants using a combination of analytic hierarchy process (AHP) and geographic information system (GIS). In the study, the weights of criteria used for selecting solar PV panels are adjusted according to the installed capacity of the PV plant. The land of cost is included as a criterion in the AHP for the first time in PV plant site selection. Besides, a novel method called optimality-based site growing (OBSG) is introduced to further analyze the suitable sites obtained from GIS simulations and to determine the most suitable locations of PV farms. The proposed method is demonstrated with a case study of Türkiye, and the results show that the method effectively determines the most suitable locations for large-scale PV plants. [ABSTRACT FROM AUTHOR]

• Floodplain conservation requires long-term knowledge of floodplain hydrology. • hyd1d provides interpolation algorithms for 1d hydraulics and gauging data. • hydflood provides extrapolation algorithms of hyd1d results into floodplains. • Together hyd1d and hydflood enable fast hydrological modelling on floodplains. • Input data, software and output are provided openly. Floodplains are environments characterized by fluctuating water levels. Spatial and temporal heterogeneity of habitat conditions driven by hydrology are the key factor for their high biodiversity because strong environmental filtering either creates favorable conditions for specialized organisms or eliminates competing generalists. hyd1d and hydflood are two R packages for simplified hydrological modelling in two large central European floodplains – along the rivers Rhine and Elbe in Germany – that enable users to simulate the dynamics of water level changes, flood extents and durations with high spatial and temporal resolution over long time periods and vast areas. They are simplified in the sense of not being based on physical equations, but they implement fast computing interpolation of 1d hydraulic data and GIS extrapolation algorithms. Annual and long-term products provide the possibility to predict the distribution of floodplain habitats. All input datasets are highly integrated into the packages and automatically updated. Computationally expensive products such as annual flood durations between 1960 and 2022 are provided as open data. The software itself is provided as open source software through CRAN and in public code repositories. With minimal efforts users can apply the software within the given conditions or integrate other river systems through data and source code contributions. [Display omitted] [ABSTRACT FROM AUTHOR]

• The present study measured the C factor value using NDVI time series, extracted from Landsat 8 OLI imageries. • The forest areas of the basin are more prone to soil erosion, compared to any other LULC category. • Upraised slope significantly affects soil loss rate and sediment yield. • Around 174.31 Km2 (9.16 %) land area contributed 57.54 % of gross soil loss. • The upstream parts of the river basin are highly susceptible to soil erosion. As a major contributor of land degradation, water borne soil erosion poses a threat to environmental and socioeconomic sustainability worldwide. Recently, various anthropogenic factors have aggravated soil erosion related problems in most of the humid and semi arid parts of the developing countries like India. Therefore, accurate quantification of the spatially distributed soil erosion along with the identification of erosion hot spots is of paramount significance for designing extensive management strategies to combat erosion hazard. The present study aimed to estimate mean annual soil loss in a tropical river basin such as Kumari river basin (KRB, area: 195125 ha) in the Chotanagpur plateau region in India. In addition, the study also quantified mean sediment yield and identified the main sediment sources within the basin. For these purposes, the present study introduced a raster based spatially distributed approach that integrated RUSLE and sediment delivery ratio (SDR) models with remote sensing (RS) and GIS. The results depicted that annual soil loss within the basin varied from 0 to 208.34 t ha – 1 yr – 1 with an average of 1.92 t ha – 1 yr – 1. The computed annual soil loss was about 364.05 × 103 tonnes, of these, 209.46 × 103 (∼58 %) were lost from only 8.93 % of the total basin area at intolerable rate. Similarly, the estimated sediment yield within the basin ranged from 0 to 64.53 t ha – 1 yr – 1 with a mean of 1.15 t ha – 1 yr – 1 and followed a similar distribution pattern of soil erosion. Being characterized by steep topography, the forest patches in the upstream part of the basin showed the most critical erosion risk. The methodology adopted in the current research displayed acceptable correctness and enabled spotting of most vulnerable areas of water erosion and critical sediment sources, initiating a comprehensive anticipating aid for the implementation of proper land management and soil conservation plans. This perspective is surmised to be helpful for extensive study of water erosion in other tropical river basins. [ABSTRACT FROM AUTHOR]

ICT tools based on abstract spaces can be considered as the "younger sibling" of GIS tools. While GIS tools based on real spaces, i.e. those that are easy for users to imagine, are developing more and more, tools based on abstract spaces are still in their infancy. The aim of this article is to show the possibilities and directions of application of ICT tools based on abstract spaces and to present the current state of their application. The article shows which elements of GIS technology can be used in tools based on abstract spaces and what differentiates the discussed types of spaces. The approach to the proposed tools was made from three points of view. First - the types of abstract spaces were presented. Second - the areas of their application were indicated along with the application of higher information functions (such as spatial data collection for abstract spaces, their single- and multi-area visualisation, environmental analysis and assessment, planning, inspiration and support of decision-making processes presented in abstract spaces). And thirdly, they were framed from the point of view of modern technologies such as AI (Artificial Intelligence), VR (Virtual Reality), AR (Augmented Reality) or hyperlinks. The reflections were concluded with an analysis of the current state of application of the technology in question in Polish public administration offices. The results of the surveys show that the proposed solutions are not currently used in city halls and are at the conceptual stage. The topic of AI is well known among the respondents. This is probably due to the popularity of the concept in popular science publications. Respondents show much less interest in the area of abstract spaces. Furthermore, they are of the opinion that their GIS solutions do not support this type of space, or if they do, they have no idea how to use it. [ABSTRACT FROM AUTHOR]

The article deals with the application of GIS in different types of cities. The development of GIS technology is opening up new applications. In addition to the collection and cartographic visualisation of data, higher-level information functions such as automatic analysis, control, spatial planning or decision support can be realised. GIS technology can also be used to visualise abstract spaces. The article deals with the application of GIS in different types of cities. The article is intended to be the result of an analysis of the direction of the use of GIS technology in public administration in Poland. For this purpose, a model was developed to examine the state of GIS technology application. Two criteria were used to determine the state: groups of factors influencing the use of GIS technology (organisational, functional, informational and technical) and the level of maturity of GIS tools. Four levels were distinguished (from zero, i.e. no application of GIS technology, to a third level indicating the strategic importance of the tools studied). To this end, an empirical study was developed to determine the level of maturity of the application of the tools in question. After analysing the results, it can be concluded that the systems studied are still evolving. From the perspective of the proposed model, it can be assumed that the development of GIS tools has reached the second level in most of the surveyed offices. However, it will still be difficult to develop the software if not all the currently available GIS software capabilities are used. [ABSTRACT FROM AUTHOR]

Despite the general political efforts to normalise bicycle use in cities, empirical evidence indicates that cycling investments tend to prioritise central and wealthy neighbourhoods rather than economically disadvantaged and peripheral areas. Among the potential causes, scholars claim that the lack of awareness about the social impacts of cycling and the general absence of equity-oriented appraisal methods during planning and decision-making processes may perpetuate the uneven distribution of bicycle-related investments. In response, this paper introduces a novel planning support tool for assessing the relative equity impact of bicycle planning (TIRE), which provides a micro-scale spatial assessment of the effects of cycling network allocation on the accessibility levels of distinct socioeconomic groups, allowing a vertical equity assessment with high spatial detail. In order to apply the tool to a real-case scenario, the cycling strategy under implementation in Lisbon, Portugal, was assessed as a testbed. The results were presented to local planning practitioners in an experiential workshop, enabling participants to define strategies supported by the tool and evaluate its user-friendliness and usefulness for planning practice. TIRE revealed hotspots in the city where the cycling network distribution is equitable and areas where disadvantaged representatives have levels of accessibility below the municipality average, thus requiring special attention during the bicycle planning process. In addition, the tool supported local planning practitioners in identifying target areas and equity-oriented strategies, increasing awareness about the equity impacts of cycling infrastructure allocation. • The inner city has higher levels of accessibility than the outskirts. • Disadvantaged groups have less access to opportunities than advantaged ones. • The tool increased planners' awareness of an equity-oriented planning paradigm. • The tool supported planning practitioners in developing new strategies. • Planners positively evaluated the tool in all dimensions of experienced usefulness. [ABSTRACT FROM AUTHOR]

Geospatial techniques are useful to understand the groundwater resources assessment, development, and management. Groundwater mapping is essential to counter the excessive withdrawal of groundwater and fulfil the need of drinking, irrigation water in hard rock areas. Currently, the main problem is facing the groundwater level is decreasing due to less rainfall, climate changes and increasing demand, which is under in the hot zones. This results can be more useful for future challenges, sustainable development and demand to Jakham river basin. The main objective of this paper to demarcated the groundwater potential zones (GWPZ) using geospatial techniques for the hard rock region with the reference of aquifer parameters. In this paper, we have used to total eight thematic layers such as geomorphology, land use, soil, topographic elevation, slope, post-monsoon groundwater level (GWL), net recharge, and transmissivity, which are prepared from satellite data and field verification. All thematic layers were integrated for assigning the weights to demarcation of the groundwater potential zones in the RS and GIS environment. The selected thematic layers and features were assigned weightage and normalized by the analytic hierarchy process (AHP) technique. Finally, the thematic layers were systematically integrated using weighted overlay analysis within a GIS environment. We have classified into five GWPZ classes i.e. very high, high, moderate, low, and very low for basin area using GIS, and AHP methods. The study area result indicated that high and moderate zone, which is confined in the central part of the basin, covers 2.43 % and 43.88 % area, respectively. The low (49.21 %) and very low (4.25%) GW potential zone is under the confined aquifer in the high slope and rock outcrops formations near the basin boundary. The final GWPZ map was validated with groundwater level fluctuation data, which illustrates the accuracy of the adopted approach. This unique approach and conclusions of this work may also help to develop the framework and policies for swiftly analyzing groundwater recharge planning, development and locating the artificial recharge structures in the other semi-arid, arid and hard rock regions. [ABSTRACT FROM AUTHOR]

The current study presents the first bathymetric map of Toshka Lakes in Egypt using the bathymetric method that is based on the combination of in situ measurements, Remote Sensing, and GIS technologies. Such a combination allows an accurate determination of the three-dimensional shapes and volumes of inland water basins, as shown by its implementation in the survey of the Toshka Lakes. The determined total surface area of the Toshka Lakes is 2321.64 km2, holding a cumulative capacity of 53.28 billion m3 (almost equal to Egypt's annual water income from the Nile). Being today the Toshka Lakes in a mature stage, the results of the morphometric and hypsometric analyses provide useful information for water conservation. The lakes are also expected to gradually shrink in size, similar to what happened in the past decades. Therefore, besides providing a digital database useful for water management, the proposed study is fundamental for appraising, with more realistic expectations, the future changes in the water basins in the Toshka Depression. This article documents the current status of the Lakes and enables researchers and decision-makers to predict their changes in volume and area with depth in the future. [ABSTRACT FROM AUTHOR]

In the Mediterranean regions, habitat degradation, alteration, and even destruction were major causes of the rarefaction of species in their natural environment. In the last decade, these phenomena are further amplified by the reduction of natural vegetation cover, urban sprawl, and climate change. In addition, the degradation of plant cover through cropping, and intensive agricultural practices causes soil erosion, habitat destruction, and loss of biodiversity. While to reduce these risks, it is necessary to assess and monitor Land Use Land Cover changes that will be crucial information for managing natural resources and guiding decision-making processes in their development plans. This is the case of a Mediterranean coastal region, Sousse, Tunisia which is characterized by its landscape diversity and the richness enhanced by the coastal and marine fauna and flora. The methodology is based on the use of Remote Sensing and Geographical Information System where different tools and functions have been employed such as Maximum Likelihood classification validated with field truth, thematic changes using classification change matrix, etc. The establishment of a multi-scalar landscape approach revealed changes in land use on a regional scale between 2007 and 2017. The landscape of Sousse region has been strongly modified by the action of Man where we note a significant growth of built-up areas and a regression of cultivated areas. From 11.84 % to 14.14 %, and from 28.83 % to 21.70 %; respectively. Hence, the growing risk of fragmentation of natural habitats, forests and agricultural areas. The development plan proposed in favor of biodiversity conservation offers a concrete example and can be useful for developing appropriate land use policy for sustainable region in Tunisia and similar Mediterranean regions. This is an essential study for all land use planning proposals as a guide to landscape conservation, enhancement and protection. [ABSTRACT FROM AUTHOR]

This paper provides insights into shoreline morphodynamics and ridge-plain physiographic compartmentalization along the migrating Zion Beach-ridge Plain, a mainland-attached strand along the high-energy, wave-dominated SW coast of Lake Michigan. Results of UAS-based topographic monitoring during the recent decadal lake-level high (2018–2020) captured the earliest phase of the ridge-formation process along several beach sites. This process-based study of net-erosional (i.e., littoral updrift) and net-accretionary (i.e., littoral downdrift) parts of the system offers much-needed context for assessing relict strand architectures. Embayed beach-ridge plains of the Laurentian Great Lakes have long served as paleo-environmental archives. They form from water-level changes and can be used to interpret isostacy. The preservation of beach ridges here is facilitated by unidirectional infilling. Much less is known about how nearshore littoral processes impact unconfined strand systems and whether useful paleoenvironmental information absent within embayed system analogs might be elucidated from their complex architecture. We herewith promote a model of punctuated development. Major episodes of shoreline transgression are manifested as continuous ridgelines of topographic prominence that, along the northern, erosive strand, truncate older ridges and are onlapped by younger ones. These major discontinuities reflect environmental changes greater in magnitude than decadal water-level oscillations observed to have formed ridgelines in recent decades. The temporal offset across the most lakeward of these major erosional strandlines is on the order of 1 kyrs and it formed between 1.8 ka and 0.9 ka, based on available C-14 ages, coincidental with a regional shift in dominant storm-wind pattern to one promoting higher-energy littoral dynamics. [ABSTRACT FROM AUTHOR]

Ecuador is a country in which only a third of the municipalities classify their waste before it is collected by garbage collection services. The country generates 4.06 million metric tons of waste each year, which is constituted of 62% of organic, 25% of recyclable and 13% are of another type of wastes. Of this total, only 4% is recycled, diminishing the space for landfills and increasing the cost of solid waste management. For this reason, the need for urban solid waste recycling systems has become very important. A waste transfer station is an important component of a waste management system and functions as a link between a community´s solid waste collection program and the final waste disposition. The study area was Grand Guayaquil which is the conglomeration of Guayaquil city and its closed neighbor surrounding cities (Duran, Samborondon, and Daule) from the province of Guayas in Ecuador, where waste transfer stations are used to temporarily store, and classify nonhazardous recyclable waste, sold by informal waste pickers, for after commercialization to recycling facilities. The main objective of this paper was to gain more insights into the geo-location of waste transfer stations, together with the quantification and characterization of recyclable waste they store for further reselling in five different cities of the province of Guayas, Ecuador. By knowing the location of these waste transfer stations and the types of recyclable materials they accept, future research can design a reverse logistic system which includes the informal collection sector. [ABSTRACT FROM AUTHOR]

The present study assessed the spatio-temporal dynamics of phytoplankton community structure and diversity using GIS platform, and their ecohydrological interactionsof a tropical reservoir located in Eastern India. Altogether, 74 species of phytoplankton belonging to 54 genera under seven taxonomic algal groups were recorded whose average annual abundance was 74.11 × 104 ± 17.73 × 104 cells l−1. Among seven algal groups, Chlorophyta, Cyanophyta, Bacillariophyta and Euglenophyta were remarkably influencing the total phytoplankton population contributing 97% of the total phytoplankton population in the reservoir. Cyanophyta absolutely dominated in the total phytoplankton compositions, and contributed a major share of 54% at the annual average level, however the species richness was maximum under the group Chlorophyta (35 genera). In total, thirteen phytoplankton taxa emerged as dominant (γ = < 0.02) across seasons. Among them, Phormidium sp. solely contributed (16.16%) to the total phytoplankton population, marked as dominant one in the reservoir. The diversity indices indicated the greater phytoplankton diversity in the lotic zone as compared to the transitional and lacustrine zone, showing significant variations (p <0.05) across seasons. PERMANOVA analysis exhibited a significant temporal variations of phytoplankton abundance (F=1.15, p=0.02) as well asenvironmental variables (F=1.82, p<0.05), but no significant spatial variations were recorded. The Principal Component analysis (PCA) revealed water temperature, transparency, total hardness, pH, specific conductivity, total alkalinity and nutrients parameters viz., phosphate, nitrate and silicate were the most important abiotic factors having the significant influence on the phytoplankton community compositions. Canonical Correspondence Analysis (CCA) depicted the environmental factors such as temperature, total alkalinity, total hardness, transparency, pH, and nutrients (NO 3 -N, PO 4 -P and SIO 4 -Si) were the determinants for the distribution of overall phytoplankton population especially the dominant phytoplankton species of the reservoir. The findings provide a better understanding of the influence of ecohydrology on phytoplankton community of a community managed reservoir and also discuss management and researchable issues considering the feeding guild of reservoir fishes and phytoplankton assemblage for ecosystem based conservation and management. [ABSTRACT FROM AUTHOR]

Healthcare spatial accessibility requires a better understanding and evaluation, especially during pandemic outbreaks like the recent COVID-19 pandemic. The main goal of this study is to measure and assess community-level spatial accessibility in Amman city to various COVID-19 related healthcare resources that could provide any urgent medical care for suspected or confirmed COVID-19 cases. To address this aim, the Enhanced 2-step floating catchment area (E2SFCA) method combined with several geospatial techniques were performed. The main E2SFCA results show the differences in the capacities and spatial accessibility of health facilities within Amman city, as well as how the variations are captured at different regions. The resulted spatial accessibility scores were presented in interactive Geo-spatial maps, analyzed, and compared for several health resources in public, private, and educational hospitals. The current research findings stated that although there are enough healthcare facilities to service almost the entire city, inappropriate health facility distribution, rather than a lack of resources, has resulted in coverage gaps in some areas. The center zones had been fully serviced, or perhaps over-served, by a large number of facilities. The other zones, on the contrary, were partially served or were even underserved by a certain number of resources. [ABSTRACT FROM AUTHOR]

Floods are potentially devastating natural hazards that can threaten human life and ecosystems. The serious impact caused by floods is the reason for the urgent need to provide an appropriate flood susceptibility map (FSM). Floods can be triggered by various meteorological events, such as storms in coastal areas. On 14 March 2019, Cyclone Idai produced massive and severe flooding inundation in the coastal city of Beira, Mozambique. The extensive flood damage in Beira necessitated providing an accurate FSM and analyzing the factors associated with flooding. This study integrated the data of synthetic aperture radar (SAR), geographic information system (GIS), and two deep learning models, namely, the group method of data handling (GMDH) and convolutional neural network (CNN), to generate a precise FSM. We compared the performance of CNN and GMDH models in generating the FSMs for a case study of the March 2019 flood in the Beira Area, Mozambique. The result showed that the models produced a similar pattern of FSM, where the areas near the river, having a lower slope and lower altitude, have a higher flood risk. The FSM generated by CNN and GMDH models were compared to find a better model for flood risk assessment. The prediction performance of CNN model (AUC = 0.90 and RMSE = 0.022) was better than the result of GMDH model (AUC = 0.87 and RMSE = 0.089). The study should be used to mitigate the flood disaster and reduce flood risk in the future. [ABSTRACT FROM AUTHOR]

The objective of this paper was to examine the interaction between brine discharge and catchment water of a desalination plant in Tenes Algeria using a modelling study under various hydrodynamic conditions. Simulations were performed with a CORMIX code for different scenarios related to the variations of natural conditions such as meteorological as well as the speed and direction of wind and current. To better exploit the results of the simulations and for a good visibility of the propagation of the brine discharge in the marine environment, three velocity cases were plotted (favorable, intermediate, and unfavorable), the planes of the plume in space (x, y) on QGIS3.16 .18, considering the position of the water intake point. A considerable increase in salinity, which sometimes exceeded 42 g/L, was noted in the catchment supply water at the desalination plant due to insufficient dilution of the brine plume. According to the simulation results obtained under the worst conditions. It was suggested to increase the distance between the capture point and the discharge point from 290 m to at least 500 m, by shifting the coordinates of the current capture point west. Based on simulations the dilution results were very promising with the excess concentration dropping from 6 to 1.8 g/L at the catchment point. Modifications to the system were recommended to improve its efficiency, even under unfavorable conditions. [ABSTRACT FROM AUTHOR]

Objectives: Striking disparities in access to radiation therapy (RT) exist, especially among racial and ethnic-minority patients. We analyzed census block group data to evaluate differences in travel distance to RT as a function of race and ethnicity, socioeconomic status, and rurality.Methods: The Directory of Radiotherapy Centers provided the addresses of facilities containing linear accelerators for RT. We classified block groups as majority (≥ 50%) American Indian/Alaska Native (AI/AN), black, white, Asian, no single racial majority, or Hispanic regardless of race. We used the Area Deprivation Index to classify deprivation and Rural-Urban Commuting Area codes to classify rurality. Generalized linear mixed models tested associations between these factors and distance to nearest RT facility.Results: Median distance to nearest RT facility was 72 miles in AI/AN-majority block groups, but 4 to 7 miles in block groups with non-AI/AN majorities. Multivariable models estimated that travel distances in AI/AN-majority block groups were 39 to 41 miles longer than in areas with non-AI/AN majorities. Travel distance was 1.3 miles longer in the more deprived areas versus less deprived areas and 16 to 32 miles longer in micropolitan, small town, and rural areas versus metropolitan areas.Conclusions: Cancer patients in block groups with AI/AN-majority populations, nonmetropolitan location, and low socioeconomic status experience substantial travel disparities in access to RT. Future research with more granular community- and individual-level data should explore the many other known barriers to access to cancer care and their relationship to the barriers posed by distance to RT care. [ABSTRACT FROM AUTHOR]

In the era of communication technology and its integration with the learning process, the role of the educational institutions has significantly changed, especially after the expansion of Internet use and the rise of what's currently known as "Internet-based learning environments". After the COVID-19 pandemic, it was necessary for researchers to search for alternatives to the traditional pedagogical approaches of maps teaching so as to cultivate well-educated learners able to adapt to rapidly changing technology-enhanced learning. Hence, the aim of this study is to develop the learning process in the Geography and Geographic Information Systems (GIS) departments in the faculties of Cairo University. To the best of the researchers' knowledge, this is the first study in Egyptian universities and research associations that utilized GIS and open-source technology to use such a system in classroom pedagogical settings. For achieving this aim, GIS capabilities and a bunch of open-source technologies were utilized to build online maps archiving system that provides rapidly discover, preview, and retrieve digital maps of different types from multiple repositories through several query operations. This will facilitate the teaching process for both staff and students and will make it more interactive and safer. To ensure the efficiency of the designed system, it was tested by a set of tools (Checklist and Questionnaires). The findings of the study point to the proposed system as contributing in significant ways to developing the learning process, increasing students' interaction with maps, and providing the necessary learning tools. [ABSTRACT FROM AUTHOR]