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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
ISSN 1682-1750 · Copernicus Publications · 15.056 artikel di indeks
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Advances in Stereo Matching for Disparity Estimation from Satellite Imagery: Traditional Scanline Aggregation Methods versus Deep Learning-Based RAFTStereo
Stereo image analysis plays a critical role in geospatial domains, enabling the generation of high-resolution disparity maps from satellite imagery, and these maps are essential for producing accurate 3D surface models used in applications such as terrain modeling, urban planning, and environmental…
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Investigation of NH3 Concentrations around Livestock Farms in Balıkesir and Bursa
Ammonia (NH3) is both an air pollutant and a contributor to particulate matter, which has significant effects on human health. The main source of NH3 is agriculture, especially livestock farming. This study evaluated NH3 levels in Balıkesir and Bursa for 2019–2023 via IASI retrievals, EMEP emission…
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Assessing Mangrove Ecosystem Health and Identifying Optimal Planting Regions Using Remote Sensing and GIS in the UAE
Mangrove forests play a critical role in carbon sequestration, biodiversity preservation, and coastal resilience, making their conservation and restoration essential in climate change mitigation. This study uses traditional field evaluations and remote sensing and geoinformatics (GIS) methods to…
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Metaverse-Enabled Digital Twins for Business and Smart Cities: Toward A Human-Centered Framework for Digital Transformation
Digital Twin (DT) technologies are increasingly changing how businesses and cities model, assess, and enhance complex systems. Traditional DTs have served as static representations of tangible assets, providing monitoring and predictive functionalities. However, minimal stakeholder engagement and a…
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Experiencing Machine learning for identifying the immunomodulator character of the medicinal plants
Medicinal plants are well known for their immunomodulatory properties, providing potential therapeutic applications in infectious diseases, autoimmune disorders, and cancer. However, determining and identifying these properties using conventional experimental approaches is often time-consuming…
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Optimizing Photovoltaic Detection in High-Resolution Satellite Imagery Using GIS, DeepLabv3+, and Transformer-Based Models: A Case Study of the Marrakesh-Safi Region
Solar energy has become a major contributor to global renewable energy strategies, offering a sustainable alternative to fossil fuels. Photovoltaic (PV) systems, which convert sunlight into electricity, play a central role in this transition. As the demand for large-scale solar energy projects…
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Predicting Leishmaniasis Risk in Morocco Using Machine Learning, GIS, and Domain Adaptation : A case study of Beni Mellal-Khenifra Region
Leishmaniasis remains a persistent global public health challenge, particularly in regions where ecological and socioeconomic conditions favor vector proliferation and disease transmission. In Morocco, the provinces of Beni Mellal and Khenifra are among the most severely affected, necessitating the…
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Improving the accuracy of GOCO06s global geoid model on Sardinia Island (Italy) using Ordinary Kriging interpolation in GIS
The geoid is the equipotential surface of the Earth's gravity field that best approximates mean sea level. In many applications of geomatics the availability of a geoid model is fundamental as it allows to transform the ellipsoidal heights provided by the GNSS (Global Navigation Satellite System)…
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The accuracy analysis of the Visual-SLAM and LiDAR-SLAM methods: A case study
Simultaneous Localisation and Mapping (SLAM) is a technique that allows a vehicle to determine its location and map its surroundings simultaneously. This study was carried out to produce a 3-dimensional (3D) model of the environment using the SLAM technique by processing the data obtained from…
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Synthetic and real data for training and testing ground camera-based UAV tracking
The high versatility and affordable price made Unmanned Aerial Vehicles (UAVs) very popular in many civil applications. Despite their usage often takes advantage of automatic flight mode, this flight modeality is usually limited to the good working conditions of Global Navigation Satellite Systems…
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Estimating Ground-Level Carbon Monoxide Concentrations Using Machine Learning Techniques: The Metropolitan City of Milan Case Study
This work presents a structured data-driven framework for estimating ground-level carbon monoxide (CO) concentrations in the Metropolitan City of Milan (MCM) by integrating Sentinel-5P satellite observations, Copernicus Atmosphere Monitoring Service reanalysis data, and ERA5 meteorological…
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Advancing Building Footprint Extraction with Multi-Stage Regularization Techniques
This paper introduces an automated building extraction method combining CNN segmentation with multi-stage regularization. We address urban mapping challenges including boundary inaccuracies and topological errors through: (1) neighborhood matrix processing for local refinement, (2) spectral graph…
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Climate Hazard Assessment for Dairy Farming in Aydin, Türkiye: Preliminary Results from the CliResDairy Project
This paper presents the preliminary findings of a climate hazard assessment for the dairy farming sector in Aydin, Türkiye, conducted under the Climate Resilience Enhancement in Dairy Farming (CliResDairy) Project. Aydin is a vital agricultural province, ranking fourth nationally for its cultural…
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Road Maintenance Prioritization (RMP) System
This study develops a transparent, weighted framework for assessing road condition and prioritizing maintenance at the segment level. Traffic data (AADT/ESAL) are fused with climate and terrain layers extracted via Google Earth Engine (GEE) into a national spatial database. A Final Road Condition…
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Pixel-Based Classification of Olive Trees Using Multi-Spectral UAV Images and Vegetation Indices
Olives are one of the world's most important harvested crops and the most studied fruit trees. In this context, studies on olive tree identification using state-of-the-art data acquisition methods are a prominent topic today. In this study, images obtained using an unmanned aerial vehicle equipped…
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Law of Sines Based Approach for the Accurate Orientation Determination
Thanks to developing sensor technologies and autonomous systems, modelling buildings with environmental data and the digital twin approach are becoming increasingly important. This study examines the environmental perception, obstacle detection, and directional correction capabilities of an…
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Deep Learning-Driven Wildfire Detection in Türkiye Using Sentinel-2 Imagery and Convolutional Neural Networks
Wildfires, intensified by climate change and anthropogenic factors, represent a major threat to ecosystems, infrastructure, and human life. Early detection is critical for effective prevention and mitigation. This study presents a Convolutional Neural Network (CNN)-based system designed to detect…
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An Automated Data Validation Approach for Power Distribution Networks using Grid Partitioning and Multi-faceted Quality Scoring
Accurate Geographic Information System (GIS) data is fundamental to the reliable management, planning, and operation of modern power distribution networks. Conventional validation methods, however, often rely on network-wide rule-based checks or manual inspections, which are inefficient at…
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Overcoming Optical Gaps: Evaluating SAR–Optical Consistency for Cotton Phenology
Reliable monitoring of cotton phenology is challenged by cloud-induced gaps in optical satellite observations, especially during key growth stages. This study evaluates the temporal consistency between C-band Synthetic Aperture Radar (SAR) features from Sentinel-1 and vegetation indices from…
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AI-Based Framework for Rapid Extraction of InSAR Coherence from COMET-LiCSAR Portal
Interferometric Synthetic Aperture Radar (InSAR) coherence analysis is a powerful remote sensing technique for detecting ground surface changes caused by natural disasters like wildfires. However, its application has been limited by the large file sizes and high computational demands of Synthetic…
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