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Digital geological mapping has experienced significant growth over the past three decades due to the advent of commercial geographical information systems, advances in global positioning systems, and the availability of portable hand-held devices, such as mobile personal computers (PCs), smartphones, and tablets. Numerous software packages have been developed to collect, combine, organise, visualise, publish, and share field data with enhanced spatial accuracy and minimal post-field processing. However, many of these tools are not open-source or are not made available to the geoscientific community, remaining specific to given mapping projects or organisations.In this contribution we introduce GEOL-QMAPS, an open-source, QGIS-based solution promoting digital geological mapping in a harmonised, comprehensive and flexible way. It can be used in the field with a tablet PC or via the QGIS-based QField app on iOS or Android mobile devices, enabling synchronisation with desktop QGIS and the creation of field databases. Designed as a general solution, the GEOL-QMAPS solution consists of a QGIS field data entry template and a custom QGIS plugin, both available on free-access online repositories. The plugin allows for the adaptation of dictionaries (i.e., lists of attributes describing geological features), initially set to international nomenclatures, to the guidelines of different mapping projects. The solution also facilitates the loading and consultation of relevant legacy geodatasets (e.g., preexisting field data, geochemical, geophysical maps or punctual datasets). A fact map, created from field data collected across the Archean Sula-Kangari greenstone belt in Sierra Leone, demonstrates the solution's advantages in terms of post-field processing and raw field data sharing.

The use of geotechnology tools combined with the delimitation of watersheds encourages studies of physiographic characteristics, fundamental in planning and decision-making for conservation, use and occupation of the soil. The study aimed to delimit the Canela Fina watershed to verify if it is prone to flooding. Using the QGIS 3.18.1 software. Zürich the methodologies through the Digital Elevation Model (DEM) obtained from the Shutter Radar Terrain Mission (SRTM) with a resolution of 30 m. The basin has an area of 116.50 km2 and a perimeter of 95.90 km. The form factor is 0.31, roundness index 0.15, compactness coefficient 2.49, I-Pai-Wu coefficient 1.59 and hydrographic density of 0.97 channels/km2. The maximum altitude of the basin was 244 m, minimum 180.66, with a maximum slope of 47.68% and average of 7.08%, with a relief ratio of 3.22 m/km. The basin was classified as 4th order, dendritic drainage pattern, sinuosity index was 1.23 and drainage density was 1.41 km/km2. The use and occupation of the soil between the years 1985 to 2020, pasture area increased by 35.60% and urbanized area by 12.64%, forest and grassland formation had a reduction of 36.90% and 39.61%, respectively. It is concluded that the basin is not susceptible to flooding. [ABSTRACT FROM AUTHOR]

The study was carried out to investigate the impact of drought on vegetation in Maharashtra's Parbhani district, utilizing remote sensing techniques. Analysis of Landsat 8 data for 2015 (a drought year) and 2020 (a normal year) reveals fluctuations in the Normalized Difference Water Index (NDWI) closely correlated with rainfall patterns. In 2015, NDWI indicated extreme drought conditions, while in 2020, most areas experienced mild drought. The comparison underscores NDWI's sensitivity to rainfall variability and dry spells. Meteorological factors, geographical features, and human activities influence moisture content in vegetation and soil, reflected in the distribution of drought severity classes. In 2020, a higher percentage of the area fell into the moderate drought category, shifting to extreme drought with reduced rainfall. This incremental shift highlights the susceptibility of the Parbhani district to drought conditions, emphasizing the interplay of natural and anthropogenic factors in drought assessment and management.

A Geospatial Opportunity Mapping (GOMap) tool was created to identify policy unconstrained land in urban cities that is technically feasible for the deployment of solar photovoltaic power stations; and identify buildings with north- or south-facing orientation for the installation of building integrated PV (BIPV). Collaboration with a local Governing authority and a local electricity provider enabled the process to elicit comprehensive policy and technical aspect information respectively that would impact the site selection process. Five policy and four technical aspects are comprised of a total of 36 individual factors displayable by GOMap on a high-resolution city grid with a scoring system implemented to distinguish between factors that encourage or inhibits solar PV deployment. Weightings can be applied, and different scenarios explored including alternative policy changes and infrastructure upgrades. GOMap generates opportunity maps in the form of available land estimates which can be extrapolated by an in-built solar PV model to quantify annual energy generation based on local weather data, array spacing, panel type and array tilt angle. Three scenarios were devised to identify unconstrained land for solar PV deployment with varying levels of policy and technical factor relaxation, and a fourth scenario to identify dwellings for potential BIPV. These scenarios aim to tackle Glasgow City's growing energy demand and fuel poverty issue, the latter of which can supply energy to dwellings categorised as ‘hard-to-heat’ once heating is electrified due to the Scottish Government's Energy Strategy commitment.

The article presents the results of soil mapping of the territory using unmanned aerial vehicles and geographic information systems. Data from a geomorphological study of the site are provided. Using leveling survey and SRTM survey data in the QGIS geographic information environment, a digital relief map of the territory with a cross-section height of 1 meter was created. It was found that the height range varies from 53.72 to 61.46 meters above sea level. Data from a geobotanical survey of the territory, carried out with an adjustment for the accuracy of identifying the boundaries of plant associations using aerial photography from a UAV, are presented. 30 plant associations were identified. A study of the morphological and physicochemical properties of soils in the mapped area was carried out. A digital geobotanical and soil map was created in the QGIS geographic information environment. It was revealed that the soil cover is represented by sod-podzolic medium-humus soils of heavy texture with a clear differentiation of the soil profile by the content of the silt fraction. The soils have a strongly acidic reaction of the environment (pHKCl 4.36). The degree of acidity decreases with depth. The value of hydrolytic acidity, depending on the horizon, varies within 5.49-5.84 mmol (eq)/100 g, reaching maximum values in the podzolic horizon. Differentiation of the values of the cation exchange capacity and the degree of saturation of the bases along the profile was revealed, the minimum values are characteristic of the eluvial horizon.

Over the past century, anthropogenic activities have had a significant impact on low-lying deltas. In this article, we utilized Landsat satellite images and sea-level data from the past thirty years to analyze the effects of land use/land cover (LULC) change, vegetation cover, and terrain temperature distribution on the Sundarbans delta. Anticipated LULC change has been simulated using a cellular automata algorithm coupled with an artificial neural network for 50 years into the future, considering climate change and other ecological drivers. The results of our analysis show that the thick, dense mangrove coverage in the Sundarbans has decreased from 65% in 1970 to 59% in 2020. However, the intricate network of channels has increased in width, and their coverage increased from 33% to 43% between 1990 and 2015. The simulations for 2030–2050 show that the mangrove coverage is expected to decline from 63.5% to 56.7% (a decrease of 628 km2), while the total area of waterbodies will increase from 33.9% to 39.8%. By 2080, we predict that the mangrove coverage will decrease by about 269 km2, the waterbodies will increase by 159 km2, the built-up areas will increase by approximately 3.89 km2, and the barren areas or beaches will cover 371 km2 (3.9% of the total area). For the simulation of 2100, we predict that the mangroves will decrease by approximately 48% (4511 km2). The waterbodies will increase to 45%, while the built-up areas and barren beaches will reach up to 117 and 517 km2, respectively. There has been an increase in sea level in the Sundarbans by an average of +17.3, +9.6, + 6.1, +0.6, +1.6, and −4.01 mm/year at Khepupara, Charchanga, Hiron Point, Dladia, Diamond Harbor, and Sagar, respectively. The findings of this article can assist the Bangladesh and Indian governments and policymakers in developing optimal land use plans and implementing successful mangrove forest management and conservation plans in the future.

The study was carried out to investigate the impact of drought on vegetation in Maharashtra’s Parbhani district, utilizing remote sensing techniques. Analysis of Landsat 8 data for 2015 (a drought year) and 2020 (a normal year) reveals fluctuations in the Normalized Difference Water Index (NDWI) closely correlated with rainfall patterns. In 2015, NDWI indicated extreme drought conditions, while in 2020, most areas experienced mild drought. The comparison underscores NDWI’s sensitivity to rainfall variability and dry spells. Meteorological factors, geographical features, and human activities influence moisture content in vegetation and soil, reflected in the distribution of drought severity classes. In 2020, a higher percentage of the area fell into the moderate drought category, shifting to extreme drought with reduced rainfall. This incremental shift highlights the susceptibility of the Parbhani district to drought conditions, emphasizing the interplay of natural and anthropogenic factors in drought assessment and management. [ABSTRACT FROM AUTHOR]

The subject of this work is geospatial analysis in the function of natural disaster risk management. GIS analysis can be applied in predicting the consequences of possible natural disasters, as well as in the case of eliminating damage caused by natural disasters that have already occurred. Analyzes in this project were carried out using freely available geodata from the Internet.

Modern requirements for spatial information greatly exceed the capabilities of classic analog maps, which is why there was a need to adapt cartography itself to these requirements. The advent of computers and the Internet has made it possible for cartography to keep up with the needs of modern society. The map itself is no longer a passive medium that serves only to navigate in space or plan a traffic route but offers different types of interaction with the user. This allows spatial information to be communicated between the cartographer and the user more quickly and easily. In addition to the basic graphic and descriptive part of the map, the maps are enriched with images, sound, and animations that allow users to experience the space shown on the map to the greatest extent possible. This paper will present the application of open-source software for creating a tourist interactive web map for the area of Ključ municipality.

Climate change is a major issue in wastewater management at local and regional levels, as it affects the frequency of flooding and therefore the need to update infrastructure and design regulations. To this end, rainfall data are the main input to hydraulic models used for the design of drainage systems and, in advanced contexts, for their real-time monitoring. Field observations are of great interest and water authorities are increasing the number of existing rain gauges, but at present they are scarce and require maintenance, so their number needs to be considered with their O&M costs. Remote sensors, including both the existing satellite rain products (SRPs) and radar imagery (RI), can complete the spatial distribution of rainfall and optimise the cost of observations. While most SRPs are based on re-analysis and have a lag in availability, RI can be obtained in near real time and is becoming increasingly popular in weather forecasting applications. Unfortunately, actual rainfall forecasts from RI observations are not accurate enough for real-time monitoring of drainage systems. In this paper, the Colour Pattern Regression (CPR) algorithm is used to recalibrate the 6 h rainfall values from RI provided by the Agencia Estatal de Meteorología (AEMET) with the observed rain gauge data, using as a case study the metropolitan area of Palma (Spain).

Radon concentrations in the tourist part of the Cango cave were measured using 25 strategically placed electret ion chambers. Airflow rates were also measured and found to be less than 1 m/s throughout the cave. An IDW interpolated radon concentration overlay was constructed using QGIS and overlayed on maps of the cave. The maximum radon concentration of 2625 Bq/m3 was measured in the Grand Hall, located in the central part of the cave following a narrow passage. The initial part of the cave near the entrance exhibited normal cave breathing characteristics, with radon concentrations of less than 300 Bq/m3. The deepest section of the cave, however, demonstrated an unexpected decrease in radon levels, temperature, and humidity. The average radon concentration in the Cango cave, measured at 1265 Bq/m3, is relatively low compared to other caves worldwide that need mitigation measures according to the International Commission on Radiological Protection (ICRP).

This study assesses the applicability of different-resolution multispectral remote sensing images for mapping and estimating the aboveground biomass (AGB) of Carpobrotus edulis, a prominent invasive species in European coastal areas. This study was carried out on the Cávado estuary sand spit (Portugal). The performance of three sets of multispectral images with different Ground Sample Distances (GSDs) were compared: 2.5 cm, 5 cm, and 10 cm. The images were classified using the supervised classification algorithm random forest and later improved by applying a sieve filter. Samples of C. edulis were also collected, dried, and weighed to estimate the AGB using the relationship between the dry weight (DW) and vegetation indices (VIs). The resulting regression models were evaluated based on their coefficient of determination (R2), Normalised Root Mean Square Error (NRMSE), p-value, Akaike information criterion (AIC), and the Bayesian information criterion (BIC). The results show that the three tested image resolutions allow for constructing reliable coverage maps of C. edulis, with overall accuracy values of 89%, 85%, and 88% for the classification of the 2.5 cm, 5 cm, and 10 cm GSD images, respectively. The best-performing VI-DW regression models achieved R2 = 0.87 and NRMSE = 0.09 for the 2.5 cm resolution; R2 = 0.77 and NRMSE = 0.12 for the 5 cm resolution; and R2 = 0.64 and NRMSE = 0.15 for the 10 cm resolution. The C. edulis area and total AGB were 3441.10 m2 and 28,327.1 kg (with an AGB relative error (RE) = 0.08) for the 2.5 cm resolution; 3070.04 m2 and 29,170.8 kg (AGB RE = 0.08) for the 5 cm resolution; and 2305.06 m2 and 22,135.7 kg (AGB RE = 0.11) for the 10 cm resolution. Spatial and model differences were analysed in detail to determine their causes. Final analyses suggest that multispectral imagery of up to 5 cm GSD is adequate for estimating C. edulis distribution and biomass. [ABSTRACT FROM AUTHOR]

The distribution of wild animals and their monitoring over large areas raises many logistical and technical difficulties that hinder the collection of observation data. The use of Geographic Information Systems (GIS) has increased significantly in recent years. QGIS, an open-source GIS software dedicated to the processing of geospatial data, enables the development of dedicated plugins for specific workflows. The open-source PelaSIG plugin has been developed in Python for QGIS 3 to facilitate and standardise the different steps before and after distance sampling surveys. It brings together a set of tools for survey preparation, automatic data checking, visualisation and presentation of survey effort and sightings to provide an adapted workflow. This plugin is currently designed to process dedicated aerial datasets collected with the SAMMOA software during marine megafauna surveys (i.e., marine mammals, seabirds, elasmobranchs, sea turtles, etc.). Here, we first describe the different tools already available, and then, we present an application with the dataset from the aerial survey of the ACCOBAMS Survey Initiative (ASI) conducted in 2018 over the Mediterranean Sea and using a multitarget protocol. [ABSTRACT FROM AUTHOR]

Offshore wind energy is becoming an increasingly important element in the decarbonisation of energy systems. This study aims to estimate the technical potential for offshore wind energy in the Polish exclusive economic zone (EZZ) of the Baltic Sea. Such estimates are necessary to plan the expansion of energy infrastructure. This paper proposes a multi-criteria analysis for the estimation of offshore wind potential and site selection using QGIS software (QGIS Desktop 3.28.6). The criteria include wind velocity, water depth, distance from nature conservation areas, distance from submarine cables and gas pipelines, distance from shipping routes, distance from fishing areas, distance from shipwrecks, and distance from the coastline. The best sites are identified through the Analytic Hierarchy Process (AHP). The results show that the total suitable marine area of 16,218.67 square kilometres can be divided into three parts, in which the highly suitable area for offshore wind farms accounts for 17.55%, the moderately suitable area accounts for 48.56%, and the marginally suitable area accounts for 10.26%. Two different wind turbine placement configurations are being considered, in which wind turbines with a nominal capacity of 15 MW are laid out: 2.5 km and 2 km apart from each other. The corresponding overall electrical capacities only in highly suitable areas equal ca. 9 GW and 15 GW, respectively. If this area is extended to also include the moderately suitable parts, these values increase to ca. 31 GW and 50 GW. The results indicate that the technical potential of offshore wind in the Polish EEZ is significant and should be taken into account when designing the future electricity generation mix. [ABSTRACT FROM AUTHOR]

The extraction of drainage network and watershed information is prerequisite for the study of watershed characteristics like morphometric analysis, which provides a basis for hydrological planning and modeling. The advanced tools of algorithms, Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM) data and Geographical Information System (GIS) software are used to extract drainage networks and their watershed boundaries. These tools are complicated to use or produce more errors in the extraction of elevation and drainage networks when applied to flat areas. For removal of errors and to improve the accuracy in preparation of DEM and extraction of drainage network, Burada Kalava River Basin, Andhra Pradesh, India has been taken for application of accuracy improvement algorithms. An automatic generation of drainage network and watershed using digital elevation model results in positional errors due to variations in slope and topography. This study aimed to generate a catchment area and stream network that closely represent the natural stream network and the streams' real positions. The step-by-step methodology using GRASS-interfaced Quantum GIS algorithms are given for pre-processing of DEM data to improve the positional accuracy before automatic extraction of the stream network and catchment area to resemble the real situation of the watershed. Secondly, efforts are made to analyze the DEM during automatic generation of the stream network and catchment area by assigning various area threshold values, including the application of pour point coordinates in improving the stream network and watershed characteristics. The results are verified and validated with the field information in order to improve the accuracy levels of DEM quality in generation of drainage network and catchment area. [ABSTRACT FROM AUTHOR]

Scientific studies concentrated in Antarctica hold great value and importance for humanity. Research projects are conducted in various disciplines on the continent, where nearly 100 research stations from 30 countries are established. Despite the challenges posed by Antarctica's natural structure, unique environment, difficult working conditions, and limited logistics opportunities, scientific research conducted there is indispensable due to the valuable information it offers. In pursuit of accessing this information, Turkish Antarctic expeditions have been organized since 2017. In this study, a polar data center was established through a web-based geographic information system (WebGIS), a significant infrastructure for the continuity of scientific studies. The implemented projects and raw/processed data from previous expeditions in diverse subjects and disciplines, including geology, geophysics, geography, hydrology, meteorology, oceanography, glaciology, atmospheric physics, chemistry, microbiology, and remote sensing, were incorporated into this information system. Studies in Antarctica have primarily focused on observing the effects of global warming, necessitating the monitoring of past and current data related to sea ice, sea level, and coastal changes. The data also encompasses seismic, volcanic, tectonic, and Global Navigation Satellite System (GNSS) monitoring. As suggested by the Antarctic Treaty, a user-friendly website was designed and made accessible for research projects, data, and publications. An entity relationship diagram was created for the fields to be included in the database. These fields were structured as tables using structured query language (SQL) queries in PgAdmin. A workspace and storage area were created in GeoServer, and a connection was established with PostGIS. Layers of spatial and nonspatial data from the PgAdmin application were added to the GeoServer workspace. The data transferred to GeoServer were presented in an OpenLayers web map with Web Map Service (WMS) and Web Feature Service (WFS) according to Open Geospatial Consortium (OGC) standards. Additionally, a mini web map was designed using the desktop Quantum GIS (QGIS) application and GIS Cloud collaboration, displaying GNSS and meteorological (weather) observation stations on the continent. A dynamic web project was employed for coding in Eclipse software, where backend coding was done with JavaScript. SQL was used as a part of the backend to integrate data from the database per request. Frontend coding for the website's visual side was completed with HTML, CSS, and JavaScript. As a result, a WebGIS platform was developed where researchers can register, add projects, and publications, and view data on a map. Users can download, analyze, and utilize the available data. The data center's existence underscores the importance of polar science and serves as an incentive for further research. [ABSTRACT FROM AUTHOR]

Floods are destructive, very detrimental, and require a long time to recover. To overcome the impact of flooding on the people of East Aceh Regency, research related to the mapping of flood-prone areas in East Aceh District. In the mapping process using Quantum Geographic Information System (QGIS) Desktop and the research methodology used is Composite Mapping Analysis (CMA) which consists of the process of determining the class of each parameter, determining the weight of each parameter by combining each parameter which includes the scoring process for each parameter, then overlaying the parameters used, performing calculations and producing a relative weight or spatial mean, and combining the spatial mean to produce a value for the weight of each flood parameter. The results of the study obtained the weight of rainfall of 23.85%; land slope parameter of 27.25%; the land height parameter is 24.7%5 and the flow density parameter is 24.15%, and the result is that the area of flood-prone areas has been divided into 3 classes, that is the very vulnerable class has an area of 230.099 ha (42.6%), the vulnerable class has an area of 224.732 ha (41.6%), and the bit vulnerable class has an area of 85.416 ha (15.8%). [ABSTRACT FROM AUTHOR]

The subject of this work is geospatial analysis in the function of natural disaster risk management. GIS analysis can be applied in predicting the consequences of possible natural disasters, as well as in the case of eliminating damage caused by natural disasters that have already occurred. Analyzes in this project were carried out using freely available geodata from the Internet. [ABSTRACT FROM AUTHOR]

Modern requirements for spatial information greatly exceed the capabilities of classic analog maps, which is why there was a need to adapt cartography itself to these requirements. The advent of computers and the Internet has made it possible for cartography to keep up with the needs of modern society. The map itself is no longer a passive medium that serves only to navigate in space or plan a traffic route but offers different types of interaction with the user. This allows spatial information to be communicated between the cartographer and the user more quickly and easily. In addition to the basic graphic and descriptive part of the map, the maps are enriched with images, sound, and animations that allow users to experience the space shown on the map to the greatest extent possible. This paper will present the application of open-source software for creating a tourist interactive web map for the area of Ključ municipality. [ABSTRACT FROM AUTHOR]

Gully erosion affects the landscape and human life in many ways, including the destruction of agricultural land and infrastructures, altering the hydraulic potential of soils, as well as water availability. Due to climate change, more areas are expected to be affected by gully erosion in the future, threatening especially low-income agricultural regions. In the past decades, quantitative methods have been proposed to simulate and predict gully erosion at different scales. However, gully erosion is still underrepresented in modern GIS-based modeling and simulation approaches. Therefore, this study aims to develop a QGIS plugin using Python to assess gully erosion dynamics. We explain the preparation of the input data, the modeling procedure based on Sidorchuk's (Sidorchuk A (1999) Dynamic and static models of gully erosion. CATENA 37:401–414.) gully simulation model, and perform a detailed sensitivity analysis of model parameters. The plugin uses topographical data, soil characteristics and discharge information as gully model input. The plugin was tested on a gully network in KwaThunzi, KwaZulu-Natal, South Africa. The results and sensitivity analyses confirm Sidorchuck's earlier observations that the critical runoff velocity is a main controlling parameter in gully erosion evolution, alongside with the slope stability threshold and the soil erodibility coefficient. The implemented QGIS plugin simplifies the gully model setup, the input parameter preparation as well as the post-processing and visualization of modelling results. The results are provided in different data formats to be visualized with different 3D visualization software tools. This enables a comprehensive gully assessment and the derivation of respective coping and mitigation strategies. [ABSTRACT FROM AUTHOR]

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The dynamics of land use and land cover are profoundly affected by the growth, mobility, and demand of people. Thematic maps of land use and land cover (LULC) help planners account for conservation, concurrent uses, and land-use compressions by providing a reference for analysis, resource management, and prediction. The purpose of this research is to identify the transition of land-use changes in the Saroor Nagar Watershed between 2008 and 2014 using the Modules for Land Use Change Evaluation (MOLUSCE) plugin (MLP-ANN) model and to forecast and establish potential land-use changes for the years 2020 and 2026. To predict how these factors affected LULC from 2008 to 2014, MLP-ANN was trained with maps of DEM, slope, distance from the road, and distance to a waterbody. The projected and accurate LULC maps for 2020 have a Kappa value of 0.70 and a correctness percentage of 81.8%, indicating a high degree of accuracy. Changes in LULC are then predicted for the year 2026 using MLP-ANN, which shows a 17.4% increase in built-up area at the expense of vegetation and barren land. The results contribute to the development of sustainable plans for land use and resource management. [ABSTRACT FROM AUTHOR]

This research paper aims to identify the best Smart City in the world, by investigating the rankings of Smart Cities, based on its main characteristics and implemented policies. The purpose of this study is to provide a comprehensive understanding of what makes a city “Smart” and to highlight the successful strategies employed by the top-ranked Smart Cities. The research employs a qualitative analysis approach, utilizing thematic maps created with the QGIS software. This methodology allows for a detailed examination of various factors contributing to a Smart City’s status, including but not limited to, technological integration, sustainable practices, and citizen participation. The expected results of this study is to report and analyze the best smart cities, according to the Smart City rankings, and also to shed light on the key elements and policies that contribute to their success. These findings could serve as a benchmark for other cities striving to achieve ‘Smart’ status. Furthermore, the thematic maps will visually represent the distribution and implementation of Smart policies, providing a clear and comprehensive overview of the Smart landscape in the top-ranked cities. This research has the potential to contribute to the field of urban development and planning, particularly in the context of Smart Cities. It could guide policymakers and city planners in designing and implementing effective strategies to transform their cities into more sustainable, efficient, and livable spaces.

Mapas axiais vêm sendo progressivamente substituídos por mapas do tipo “Road Centre Line” (RCL) como o Open Street Map, devido a uma maior facilidade de obtenção dos dados e preparação do mapa base para as análises quantitativas da Sintaxe Espacial. Com a oferta de ferramentas gratuitas, isso vem sendo cada vez mais acessível a um maior número de pesquisadores e pesquisadoras. Entretanto, esse processo ainda gera dúvidas e desafios aos(às) usuários(as), especialmente quando se deseja que ele seja automatizado para evitar retrabalho e possibilitar a reprodução por outros interessados. Nesse contexto, testamos três ferramentas gratuitas para a preparação e elaboração de mapas configuracionais – Space Syntax Toolkit (SST), PST e sDNA –, comparando suas funcionalidades, pontos fortes e pontos fracos. Para isso, usamos uma amostra em Florianópolis e percorremos todas as etapas do processo, com especial ênfase para a filtragem e seleção das vias e a preparação geométrica para adequação ao formato necessário para os cálculos sintáticos. Ao final, comparamos as medidas de Integração Global alcançadas pelas três ferramentas, demonstrando que os resultados são muito similares, e sugerimos um fluxo de trabalho para automatizar esse processo através de modelos gráficos do QGIS, que podem ser reutilizados, aprimorados e ajustados para contextos específicos.

Chamwino district, central Tanzania is a semi-arid granitic complex province, where groundwater is the major source of water for domestic and other uses. However, groundwater in the area is affected by salinity, thus, lowering the availability of potable water for various uses, decrease in crop production, taste less, wastage of soap, and abnormal pain. Due to this, this study sought to characterize groundwater using hydrogeochemical facies and signatures in order to identify the factors influencing the distribution of salt water in the Chamwino Granitic Complex. A total of 141 groundwater samples were collected from wells spatially distributed within the study area from January 2023 to April 2023, (a season of relatively low rainfall). All samples were subjected to in situ analyses of physicochemical parameters pH, temperature (T), total dissolved solids (TDS), electrical conductivity (EC), and salinity using a multi-parameter water analyzer and analyses of major ions (Ca2+, Mg2+, K+, Na+, Cl−, SO42−, HCO3−, and NO3−). The study revealed that the dominant cations in the groundwater are Na+ > Ca2+ > Mg2+, and the anions are Cl− > HCO3− > SO42. Five geological formations (granodiorite, tonalitic orthogenesis, migmatite, tonalite, and alluvium) were identified, and each is characterized by its unique groundwater facie. In the areas that are dominated with granodiorite, the major hydrogeochemical facies were Ca–HCO3, Na–Cl, Ca–Na–HCO3, Ca–Mg–Cl, and Ca–Cl water types; tonalitic orthogenesis was dominated by Ca–HCO3, Na–Cl, Ca–Mg–Cl, and Ca–Cl water types; migmatite was dominated by Ca–HCO3, Na–Cl, Ca–Mg–Cl, and Ca–Cl water types; tonalite was dominated by Na–Cl, Ca–Mg–Cl, and Ca–Cl water types; and alluvium was dominated by Na–Cl and Ca–Mg–Cl and Ca–Cl water types. The common hydrogeochemical facies in all five geological units are Na–Cl, Ca–Mg–Cl, and Ca–Cl water types. It is revealed that the groundwater in the study area is alkaline in nature and slightly saline with salinity level between 0.2 mg/L (fresh water) and 2.8 mg/L (brackish water) with mean 1.07 mg/L (of 141 samples). The factors controlling groundwater salinity distribution are mainly rock-water interaction and ion exchange reactions. Groundwater salinity in the study area is largely attributed to the abundance of Na+, Ca2+, Cl− and SO42−. Abundance of Na+ and Ca2+ is the results of both, weathering of feldspar minerals particularly plagioclase (Na–Ca feldspars) which are the major mineral in granites, and evaporation crystallization cycles of evaporates in semi-arid areas such as Chamwino. Also, such evaporation crystallization cycles account for the abundance of Cl− and SO42− especially in areas dominated by alluvium. However, anthropogenic activities as evidenced by elevated nitrate up to 212.6 mg/L in congested areas are also likely to contribute in area) to the elevated Cl− and SO42−. In other geological units such as tonalitic orthogneiss, migmatite and granodiorite, there was an ostensible mixing of saline water with fresh water from local recharge as indicated by the abundance of HCO3− ions. Nonetheless, the hydrogeochemical characterization of groundwater in the Chamwino granitic complex suggests that there is little possibility for groundwater to evolve to a carbonate water type (fresh water) because the groundwater salinity is mainly geogenic, unless artificial recharge through rainwater harvesting is applied.

The need for quality water in Africa for agriculture cannot be overemphasized amidst the current global water crises. The focus of this study sought to evaluate the quality of groundwater for irrigation purposes while unearthing the emerging challenges in the study area. In total, 202 groundwater samples were collected, and several parameters were tested. The study employed QGIS and multi-criteria decision analysis to examine zones of suitable groundwater quality for agriculture. Findings from the study indicate that the primary water types were Na–HCO3 and Ca–HCO3. The overall accuracy (OV) of the land use land cover (LULC) map using the Random Forest (RF) algorithm was 94.5%. The analysis revealed that SpH influences GpH at p = 0.02891 (p < 0.05) and SOM and SOC influence GNO3 at p = 0.044 (p < 0.05). The overlay analysis spatially classified the groundwater in the study area into three categories of suitability with ariel coverage showing areas of good quality (1,534.34 km2), moderate quality (1,933.35 km2), and poor quality (1,815.21 km2). The results from this study uncovered that 72.33% of the samples were within the desirable limits and it can be concluded that the quality of groundwater in the area is acceptable for irrigation. HIGHLIGHTS This paper examines different surficial factors.; This study presents several cases (quality versus LULC, slope, and soil).; The paper examines the suitable areas for irrigation as per the available groundwater quality.;

This study explores how combining virtual reality (VR) and augmented reality (AR) with geographic information systems (GIS) revolutionizes data visualization. It traces the historical development of these technologies and highlights key milestones that paved the way for this study’s objectives. While existing platforms like Esri’s software and Google Earth VR show promise, they lack complete integration for immersive GIS visualization. This gap has led to the need for a dedicated workflow to integrate selected GIS data into a game engine for visualization purposes. This study primarily utilizes QGIS for data preparation and Unreal Engine for immersive visualization. QGIS handles data management, while Unreal Engine offers advanced rendering and interactivity for immersive experiences. To tackle the challenge of handling extensive GIS datasets, this study proposes a workflow involving tiling, digital elevation model generation, and transforming GeoTIFF data into 3D objects. Leveraging QGIS and Three.js streamlines the conversion process for integration into Unreal Engine. The resultant virtual reality application features distinct stations, enabling users to navigate, visualize, compare, and animate GIS data effectively. Each station caters to specific functionalities, ensuring a seamless and informative experience within the VR environment. This study also delves into augmented reality applications, adapting methodologies to address hardware limitations for smoother user experiences. By optimizing textures and implementing augmented reality functionalities through modules Swift, RealityKit, and ARKit, this study extends the immersive GIS experience to iOS devices. In conclusion, this research demonstrates the potential of integrating virtual reality, augmented reality, and GIS, pushing data visualization into new realms. The innovative workflows and applications developed serve as a testament to the evolving landscape of spatial data interpretation and engagement.

Introduction: Tegal Panggung is a high population density sub-district of 26,326 inhabitants/km2. Most residents utilize wells to meet their water demands, but fecal coliform bacteria were found in several wells at Tegal Panggung. This type of contamination source is typically from on-site wastewater treatments. However, wastewater from Tegal Panggung is treated at a centralized wastewater treatment plant. This study is aimed at identifying the factors leading to the presence of fecal coliform bacteria in Tegal Panggung. Methods: Factors reviewed in this study were the amount of waste, drainage, cattle pens, toilets, types of wells, and building density. Statistical methods and GIS were applied to determine the influence of the factors on the presence of fecal coliform and to map its distribution along with potential sources of pollution. The number of wells tested was 32, with a research period from September to October 2021. The statistical methods used are the Kolmogorov-Smirnov Normality Test, the Spearman Correlation Test, and the spatial analysis method, which was carried out using QGIS. The statistical tests were conducted to determine the correlation value between fecal coliform and pollutant. Results and Discussion: The study showed that only 40.62% met the standard requirements when there should be no fecal coliform contents in well water. Conclusion: Based on the Spearman Correlation Test, it can be deduced that the factors affecting the presence of fecal coliform within 10 meters radius are garbage and of 30 meters radius are toilets and building density.

The problem of noise pollution in Baghdad, the capital city of Iraq, is getting worse every day as a result of the increased volume of traffic. This presents a considerable risk, particularly on the main roads that connect densely populated neighborhoods such as the Al-Sadr City district with the central neighborhoods of the capital. In order to inform decision-makers in urban development and environmental policy about the high values of noise pollution that require remediation and regulation, noise maps are produced. However, two fundamental problems are generally faced in creating a more reliable noise map in the shortest possible time: the excessive time requirements for measuring noise and determining the method of map creation. Therefore, the role of geographic information system (GIS) software in producing noise maps is evident due to the difficulty of increasing the spatial density of measurements and integrating them with spatial information. Hence, an appropriate interpolation method is required. In this article, Moran’s I index was calculated to assess the spatial autocorrelation of measured traffic noise points. A comparison was made between the Smart Map Plugin ordinary kriging (OK) and the inverse distance weighting (IDW) deterministic interpolation method to determine the best method for producing noise maps for the main entrance and exit roads of Al-Sadr City. The noise values were modeled using the best-performing method. Furthermore, the predictive raster data are displayed in the spatial context as a starting point and reference for identifying and understanding the levels of traffic noise in the selected study area. The locations of selected points for measuring traffic noise values were determined in an organized and homogeneous manner, where noise points for the main entrance and exit roads were opposite each other, and the distance between consecutive noise points on each road was 100 m. Traffic noise measurements were carried out at each selected point using the SVAN977 sound and vibration analyzer. At each measurement point, three noise values (LAeq, Max, Min) were obtained during the three peak times, 7–9 AM, 12–2 PM, and 4–6 PM. QGIS software was used to compare the two interpolation methods, with its strength lying in the use of plugins that facilitate spatial analysis, processing tools, and algorithms. The Smart Map Plugin provided facilities to choose the appropriate semi-variogram in the OK interpolation method. The root mean square error was used to compare the two interpolation methods in order to determine the most suitable method for producing traffic noise maps in the study area. The results indicated that the Smart Map Plugin using OK outperformed the IDW method, as spatial distribution pattern and homogeneity affect the accuracy of interpolation. Moreover, based on the analysis of the three noise attributes (LAeq, Max, Min), the performance of the Smart Map Plugin (OK) was found to be better than IDW when the Moran’s I value was high.

Groundwater is an important process in the watershed hydrological system. Serayu watershed, the largest in Central Java Province, has bio-physic spatial variability that influences groundwater recharging. The aim is to derive the groundwater potential zone of the Serayu watershed. Five thematic maps used and applied for groundwater potential analysis, were lithology, land use land cover, lineament density, drainage density, and slope gradient. Distribution of Lithology data, Digital Elevation Model (DEM), and Landsat 8 image were analyzed to thematic raster with 1 x 1 km resolution. Weighted index was calculated regarding the relation of five influence parameters then were overlaid and calculated by using QGIS-calculator. Groundwater classified into five categories, namely poor, low, moderate, good, and very good. Based on the final groundwater potential map, 0.02% of 3,727 km2 is poor category, however most of Serayu watershed have moderate to good (48.77 and 29.77 %, respectively). The percentage of very good (10.57%) and low (10.87%) classes were rather similar. Spatial variability of groundwater distribution indicates the complex characteristics of the Serayu watershed, so more serious attention from the perspective of research and management of water resources in the future, is needed.

El uso de las tecnologías de la información y la comunicación (TIC) en la educación superior se ha generalizado en los últimos años. Su presencia y utilización en la disciplina de Geografía está empezando a plantear nuevos retos y formas de acceder al conocimiento. La Geografía estudia un campo de conocimientos muy amplio que abarca desde el estudio de los fenómenos físicos, la economía, hasta los movimientos migratorios humanos. En este contexto se presenta una innovación docente basada en el aprendizaje de conceptos de Geografía, mediante la utilización de los Sistemas de Información Geográfica (SIG) en el aula. En el estudio participaron 125 alumnos del Grado en Ingeniería Eléctrica y del Grado en Ingeniería Química Industrial. Previamente fue elaborado un cuestionario de conocimientos previos donde se identificaron las necesidades de aprendizaje del alumnado. La metodología utilizada fue cuantitativa y cualitativa organizada en diferentes sesiones de trabajo, en el marco de las asignaturas Topografía y Sistemas de Información Geográfica, y Expresión Gráfica. Los resultados obtenidos denotan una elevada satisfacción del alumnado ante el uso de los SIG (software libre QGIS v. 3.28) y de la herramienta tecnológica Kahoot mediante la cual se realizó el cuestionario de evaluación. Estos datos coinciden con la satisfacción del alumnado que reflejan otros estudios sobre Kahoot (Reynolds et al., 2021). También mostraron que el uso de los SIG resultó ser una herramienta muy ventajosa para el aprendizaje, mejorando el rendimiento académico, y transmitiendo un alto grado de satisfacción para más del 80% del alumnado que así lo identifica, y asegura su importancia para su futuro profesional.

The distribution of wild animals and their monitoring over large areas raises many logistical and technical difficulties that hinder the collection of observation data. The use of Geographic Information Systems (GIS) has increased significantly in recent years. QGIS, an open-source GIS software dedicated to the processing of geospatial data, enables the development of dedicated plugins for specific workflows. The open-source PelaSIG plugin has been developed in Python for QGIS 3 to facilitate and standardise the different steps before and after distance sampling surveys. It brings together a set of tools for survey preparation, automatic data checking, visualisation and presentation of survey effort and sightings to provide an adapted workflow. This plugin is currently designed to process dedicated aerial datasets collected with the SAMMOA software during marine megafauna surveys (i.e., marine mammals, seabirds, elasmobranchs, sea turtles, etc.). Here, we first describe the different tools already available, and then, we present an application with the dataset from the aerial survey of the ACCOBAMS Survey Initiative (ASI) conducted in 2018 over the Mediterranean Sea and using a multi-target protocol.

Este trabalho tem como tema a fragmentação urbana diante das problemáticas sociais e vulnerabilidades ambientais características do século XXI: analisa a expansão urbana em Chapecó-SC, uma cidade média do Oeste catarinense no contexto das regiões agroindustriais. Com o objetivo de compreender as transformações, dinâmicas e tendências ocorridas em termos econômicos, sociais e ecológicos, entrelaçadas à urbanização do território, foi aplicado o método de análise espaço-temporal por geoprocessamento. Para essa análise, foram consideradas as variáveis de dinâmicas populacionais, transições do Produto Interno Bruto e as transições da cobertura e uso da terra no intervalo de 1985 a 2015, mapeamento realizado pelo projeto MapBiomas. Os resultados obtidos mostram que a fragmentação da mancha urbana é um fenômeno em curso nas cidades médias em desenvolvimento. Nelas, as vias estruturais se consolidam como propulsores da expansão urbana, não sendo mais as contiguidades espaciais as únicas soluções para as relações sociais, humanas e econômicas da cidade, mas acessibilidade, infraestrutura e as conexões com as dinâmicas globais de desenvolvimento.