Mukesh Kumar Verma^1,2,*, Manohar Yadav¹

Revue Internationale de Géomatique, Vol.34, pp. 855-879, 2025, DOI:10.32604/rig.2025.069914 - 17 November 2025

Abstract Precision Agriculture (PA) is revolutionizing modern farming by leveraging remote sensing (RS) technologies for continuous, non-destructive crop monitoring. This review comprehensively explores RS systems categorized by platform—terrestrial, airborne, and space-borne—and evaluates the role of multi-sensor fusion in addressing the spatial and temporal complexity of agricultural environments. Emphasis is placed on data from LiDAR, GNSS, cameras, and radar, alongside derived metrics such as plant height, projected leaf area, and biomass. The study also highlights the significance of data processing methods, particularly machine learning (ML) and deep learning (DL), in extracting actionable insights from large datasets. By More >

Ihsan Qadir¹, Usama Naeem², Ahmed Nouman³, Aamir Raza⁴, Jun Wu^1,*

Revue Internationale de Géomatique, Vol.34, pp. 831-853, 2025, DOI:10.32604/rig.2025.069020 - 10 November 2025

Abstract The Jhelum River Basin in Pakistan has experienced recurrent and severe flooding over the past several decades, leading to substantial economic losses, infrastructure damage, and socio-environmental disruptions. This study uses multi-temporal satellite remote sensing data with historical hydrological records to map the spatial and temporal dynamics of major flood events occurring between 1988 and 2019. By utilizing satellite imagery from Landsat 5, Landsat 8, and Sentinel-2, key flood events were analyzed through the application of water indices such as the Normalized Difference Water Index (NDWI) and the Modified NDWI (MNDWI) to delineate flood extents. Historical… More >

Shohreh Moradpour^1,#, Shuai Zhao^2,#, Mojgan Entezari¹, Shamsollah Ayoubi^3,*, Seyed Roohollah Mousavi⁴

Revue Internationale de Géomatique, Vol.34, pp. 809-829, 2025, DOI:10.32604/rig.2025.069538 - 06 November 2025

Abstract Accurate spatial prediction of soil organic carbon (SOC) and soil inorganic carbon (SIC) is vital for land management decisions. This study targets SOC/SIC mapping challenges at the watershed scale in central Iran by addressing environmental heterogeneity through a random forest (RF) model combined with bootstrapping to assess prediction uncertainty. Thirty-eight environmental variables—categorized into climatic, soil physicochemical, topographic, geomorphic, and remote sensing (RS)-based factors—were considered. Variable importance analysis (via) and partial dependence plots (PDP) identified land use, RS indices, and topography as key predictors of SOC. For SIC, soil reflectance (Bands 5 and 7, ETM+), topography, More > Graphic Abstract

Miljenko Lapaine^*

Revue Internationale de Géomatique, Vol.34, pp. 793-808, 2025, DOI:10.32604/rig.2025.066916 - 06 November 2025

Abstract The paper investigates the properties of the Lambert equivalent azimuthal projection, which is often used in normal aspect in atlases for maps of the northern and southern hemispheres. The field of research is theoretical in nature and assumes a mastery of mathematics because it deals with map projections. The transverse aspect is commonly used for eastern and western hemisphere atlas maps. In addition, the Hammer projection was created from the transverse aspect of that projection. Therefore, if we want to get to know the Hammer projection better, we must first investigate the Lambert equivalent azimuthal… More >

Yan Eng Tan^*, Siti Nur Aliaa Roslan

Revue Internationale de Géomatique, Vol.34, pp. 777-791, 2025, DOI:10.32604/rig.2025.070997 - 23 October 2025

Abstract Sinkholes, typically associated with karst landscapes, are emerging as significant geohazards in rapidly urbanising regions such as Kuala Lumpur, where human activities like land development, underground infrastructure, and groundwater extraction exacerbate subsurface instability. Despite their destructive potential, sinkholes remain under-monitored in Malaysia due to fragmented data and the lack of predictive spatial tools. This study aimed to develop a web-based, machine learning-driven framework for sinkhole susceptibility mapping to support public awareness, hazard mitigation, and geospatially informed urban planning. The framework was implemented using Google Earth Engine and Google Colab, focusing on Kuala Lumpur and parts… More >

Nur Sabrina Jamal, Nabilah Naharudin^*

Revue Internationale de Géomatique, Vol.34, pp. 751-776, 2025, DOI:10.32604/rig.2025.071091 - 17 October 2025

Abstract Multicriteria Decision Analysis (MCDA) has been integrated with GIS modelling by many studies to aid the decision-making process. This integration enhances modelling by incorporating spatial relationships and using advanced techniques, including the combination of Frequency Ratio (FR) and Analytical Hierarchical Process (AHP), also known as FR-AHP. Although methods like Two-Steps Floating Catchment Area (2SFCA), AHP, and FR are widely applied in measuring accessibility, they have limitations in terms of threshold sensitivity and subjectivity. Hence, this study used FR-AHP, which combines the data-driven strength of FR and the structured decision-making technique of AHP to provide a… More >

Anton Louise P. De Ocampo^*

Revue Internationale de Géomatique, Vol.34, pp. 731-749, 2025, DOI:10.32604/rig.2025.066185 - 10 October 2025

Abstract The effects of climate change are becoming more evident nowadays, and the environmental stress imposed on crops has become more severe. Farmers around the globe continually seek ways to gain insights into crop health and provide mitigation as early as possible. Phenotyping is a non-destructive method for assessing crop responses to environmental stresses and can be performed using airborne systems. Unmanned Aerial Systems (UAS) have significantly contributed to high-throughput phenotyping and made the process rapid, efficient, and non-invasive for collecting large-scale agronomic data. Because of the high complexity and cost of specialized equipment used in… More >

Buddhini Chaturika Jayasinghe¹, Neel Chaminda Withanage¹, Prabuddh Kumar Mishra^2,*

Revue Internationale de Géomatique, Vol.34, pp. 707-729, 2025, DOI:10.32604/rig.2025.067395 - 12 September 2025

Abstract Road Traffic Accidents (RTAs) pose significant threats to public safety and urban infrastructure. While numerous studies have addressed this issue in other countries, there remains a notable gap in localized RTA research in Sri Lanka. In this context, the present study investigates the spatial and temporal patterns of RTAs in the Matara urban area in 2023, with the goal of supporting evidence-based policy interventions. A suite of GIS-based spatial analysis techniques including hotspot analysis, kernel density estimation, GiZscore mapping, and spatial autocorrelation (Moran’s I = 0.36, p < 0.01) was applied to examine the distribution and… More >

Muhamad Ammar Hanif Arif¹, Amir Sharifuddin Ab Latip^1,*, Siti Balqis Mohd Tun¹, Nur Azlina Hariffin¹, Adel Gohari², Mohd Hakimi Abdul Rahman¹

Revue Internationale de Géomatique, Vol.34, pp. 691-705, 2025, DOI:10.32604/rig.2025.065949 - 29 August 2025

Abstract Digital Elevation Model (DEM) refers to a digital map of the surface of the Earth that only shows the bare ground, without any buildings, plants, or other characteristics. However, obtaining unlimited access to DEM data at high and medium resolutions is very hard. Consequently, users often question the accuracy of freely available DEMs and their suitability for various applications. By comparing them to Global Positioning System (GPS) elevation data, this study aimed to identify the most reliable and widely available DEM for various terrains. The objectives of this study were to generate DEMs from different… More >

Almustafa Abd Elkader Ayek¹, Bilel Zerouali^2,*, Ankur Srivastava³, Mohannad Ali Loho^4,5, Nadjem Bailek^6,7, Celso Augusto Guimarães Santos^8,9

Revue Internationale de Géomatique, Vol.34, pp. 669-689, 2025, DOI:10.32604/rig.2025.067137 - 19 August 2025

Abstract This study investigates the spatial and temporal dynamics of key air pollutants—nitrogen dioxide (NO₂), carbon monoxide (CO), methane (CH₄), formaldehyde (HCHO), and the ultraviolet aerosol index (UVAI)—over the period 2019–2024. Utilizing high-resolution remote sensing data from the Sentinel-5 Precursor satellite and its TROPOspheric Monitoring Instrument (TROPOMI) processed via Google Earth Engine (GEE), pollutant concentrations were analyzed, with spatial visualizations produced using ArcGIS Pro. The results reveal that urban and industrial hotspots—notably in Damascus, Aleppo, Homs, and Hama—exhibit elevated NO₂ and CO levels, strongly correlated with population density, traffic, and industrial emissions. Temporal trends indicate significant pollutant fluctuations More > Graphic Abstract