Geomatics and Environmental Engineering

Geospatial Framework for Sustainable Land Administration for Low-Income Countries in Africa: Case study of Botswana

Kealeboga Moreri, Mooketsi Segobye, Lopang Maphale, Lone Seboni — Thu, 30 Jul 2026 00:00:00 +0200

Many developing countries lack national policies and frameworks to establish how geospatial information can be incorporated into their global development agenda programs. Such policies and frameworks can help these countries to properly administer land and its resources in their national contexts. As a result, they face challenges in their efforts to achieve sustainability in properly administering land and its resources through the use of geospatial information. These issues can be addressed by a strategic geospatial framework that advocates for inclusive, participatory consensus and evidence-based decisionmaking initiatives. Unfortunately, such a framework does not exist in many developing countries, particularly in Sub-Saharan Africa. Thus, this study proposes a comprehensive and strategic geospatial framework for sustainable development, to provide policy and guidance to land administrators to effectively integrate geospatial information into the sustainable development agenda of Botswana as a case study. A Delphi method involving various experts in land administration was used to develop and validate the novel geospatial framework. The novelty of the proposed framework is that it provides insights on how developing countries can administer land and its resources by achieving Sustainable Development Goals 9 and 11. This study has answered the question of how and where geospatial information can contribute to achieving the outlined SDGs through proper monitoring and progress reporting of land administration issues in a developing country setup.

Estimation of PM2.5 Particulate Matter Using MATLAB and GWR Models Based on Remote Sensing Data in Baghdad City, Iraq

Shaimaa Taleb Alnasrawy, Nadia A. Aziz — Thu, 30 Jul 2026 00:00:00 +0200

Precise and effective air quality forecasting plays a crucial role in predicting and mitigating health risks in communities worldwide. This research focuses on estimating particulate matter (PM2.5) concentrations using geographically weighted regression (GWR) and MATLAB models, utilizing remote sensing data in Baghdad city, Iraq. The estimation process incorporates multiple influencing factors, including aerosol optical depth (AOD), population density, normalized difference vegetation index (NDVI), relative humidity, temperature, wind speed, and elevation. The analysis of the relationship between influencing factors and PM2.5 concentration using grey relational analysis revealed that aerosol optical depth (AOD) exhibited the strongest correlation, whereas population density was the weakest. Furthermore, the results indicated that the PM2.5 concentration model developed using MATLAB, based on remote sensing data and incorporating eight influencing factors, demonstrated the highest accuracy, achieving an R2 value of 0.98 and a root mean square error (RMSE) of 1.7 × 10−10. The performance of the predictive equation for PM2.5 concentration, derived using MATLAB, was assessed by comparing its estimations with ground station measurements obtained from independent locations and time periods. The model achieved a coefficient of determination (R2) of 0.77, indicating that it accounts for 77% of the variability in the observed values. This outcome signifies a strong correlation between the predicted and measured concentrations, confirming that the model effectively represents the underlying relationships with a satisfactory degree of accuracy.

Enhancing the Urban Agglomeration Management Combining UAVs, Deep Learning, and WebGIS in Ho Chi Minh City, Vietnam

Ngoc Huyen Trang Tran, Van Trung Le, Le Phu Vo — Thu, 30 Jul 2026 00:00:00 +0200

Ho Chi Minh City (HCMC), the biggest city and most urban agglomeration in Vietnam, has witnessed the rapid growth of urban expansion over the past several decades. However, the city authorities faced a wide range of constraints in handling urban management and planning issues. Among these, the management practices of urban construction activities and planning tasks are the most challenging due to the low quality of available data, lack of data synchronization between management departments, and the limitations in monitoring construction activities. These have resulted in poor performance in urban planning. In this study, Unmanned Aerial Vehicles (UAVs) were deployed to take photos of the existing construction activities in a residential area of HCMC. The traces of houses will be segmented and extracted automatically using a deep learning (DL) model. Using UAVs combined with DL is a solution that demonstrates high automation, which can create standardized and uniform datasets. A 3D map of the area was created and shared on the WebGIS platform. Comparing the construction status with the legal boundaries of the land plot, the horizontal and vertical construction permit standards will help detect illegal construction objects. The results of the study show that the combination of UAV images and DL shows strong potential for building 3D maps, with the accuracy of the ground and elevation being 4.8 cm and 11.9 cm, respectively. This result suggests a promising solution to assess construction status with an appropriate accuracy corresponding to a map scale of 1:500. Importantly, the achieved 3D map shared on WebGIS is effective for use as a data source between the line government agencies.

Spatiotemporal Assessment of Hydroclimatic Change and Environmental Vulnerability in Central and Southern Iraq Using Geospatial Techniques

Alaa G. Khalaf, Raad A. Abbood, Imzahim A. Alwan, Abdulrazzak T. Ziboon — Tue, 18 Aug 2026 00:00:00 +0200

Climate and hydrology-related stresses arise in central and southern Iraq as a result of both the impacts of climate change and declining river flows, and long-term assessments are still limited. This study aims to address two questions: how have climatic and environmental conditions changed over time in the study area, and what is the relationship between climate change and drought in the region. A Geographic Information System (GIS) with remote sensing data was utilized to study climatic, hydrological, and ecological variables. The Mann–Kendall test and Sen’s slope estimator were used for trend analysis. To assess the vegetation and surface water conditions, the Vegetation Condition Index (VCI) and Normalized Difference Water Index (NDWI) were utilized. The final results illustrated a strengthening pattern of hydroclimatic stress, with a significant decline in rainfall alongside a rise in mean temperature and land surface temperature, which led to increased evaporation rates and declined relative humidity. The surface water decreased from 22 to 15% and the percentage of land affected by extreme drought expanded from 37 to 43%. Also, growing winds and dust storm events underscore a self-enhancing feedback mechanism associated with land degradation. These changes are further intensified by declining inflows from the Tigris and Euphrates rivers because of upstream control over these river systems.

Long-Term Evolution of Water Quality and Interactions with Climate Change. Case of the Bab Louta Reservoir (Taza, Morocco)

Wed, 14 Oct 2026 00:00:00 +0200

Bab Louta Dam, located about 15 km from Tahla town in Morocco, has shown significant interactions between changes in water quality and climate change since it was filled in 2001. The objective is to conduct a study of the water quality, assess the effects of climate change on the ecological balance, and analyse water quality trends using appropriate technical tools. The results obtained showed a satisfactory quality of the Bab Louta reservoir for the production of water for food use, a firm thermal stratification, the occurrence of anoxic conditions in deep waters towards the end of the summer period, and the presence of undesirable elements, particularly manganese, iron, and hydrogen sulfide, requiring advanced conventional treatment. The plankton analysis shows a notable algal biomass and a marked trend towards a eutrophic state. This study made it possible to identify the mechanisms by which climate change affects the water quality of the Bab Louta dam and its ecological balance, to establish correlations between different physicochemical, hydro biological, and climatological parameters, to carry out a predictive analysis of water quality in relation to future climate changes, and to propose remedies for water quality problems related to future climate changes.

Geomatics-Based Assessment of Walkable Market Accessibility and Traffic Impacts in Planned Urban Areas: Implications for Sustainable Residential Planning in Delhi

Tarun Ghawana, Anna Klimach, Agnieszka Dawidowicz — Sat, 03 Oct 2026 00:00:00 +0200

Market distribution within planned urban settlement areas may still produce accessibility disparities and traffic imbalances. These dynamics can weaken pedestrian vitality and threaten the quality of residential spaces.
This study aims to examine how the distribution of regulated markets influences walkability-based accessibility and adjacent traffic flows in planned residential areas of Delhi. The objective is to identify spatial patterns that either sustain or degrade urban residential environments and to investigate the potential of integrated spatial analysis in risk mitigation.
Using geospatial datasets-based congestion indicators, the study applies buffer analysis, and hotspot analysis to: (i) map market distribution; (ii) assess gaps in walkable catchments; and (iii) quantify links between market accessibility and road traffic intensity.
The findings reveal significant spatial inequities in walkable access to formal markets and demonstrate that areas with insufficient market catchments show low traffic utilization, whereas highly concentrated areas correspond with traffic saturation. These insights provide a replicable, data-driven model for strategically improving walkability, mitigating congestion, and preventing residential space degradation in rapidly urbanizing regions.

Corrigendum to “A Novel Housing Price Estimation Model Integrating GIS and DNN: A Case Study of Istanbul” (vol. 20, no. 4, 2026)

Sat, 10 Oct 2026 00:00:00 +0200

In the originally published article, incorrect affiliation and ORCID information were provided for Hossein Azadi due to an unintentional error in the author information submitted with the manuscript.