Applied Geomatics最新文献

{"title":"Assessing the metric reliability of NRTK-based surveying systems for multi-scale architectural documentation: experimental tests and real-world applications","authors":"Enrico Breggion,&nbsp;Andrea Martino,&nbsp;Andrea Sattin,&nbsp;Francesco Guerra","doi":"10.1007/s12518-026-00752-9","DOIUrl":"10.1007/s12518-026-00752-9","url":null,"abstract":"<div><p>Network Real-Time Kinematic (NRTK) correction services have lowered the barrier to georeferenced surveying by enabling centimetric GNSS positioning without deploying a local base station, but their “end-to-end” metric reliability in multi-sensor architectural workflows remains strongly dependent on platform-specific error source (Rizos 2002). This paper assesses the geometric consistency achievable when NRTK is used as the sole georeferencing backbone for multi-scale heritage documentation, combining a controlled benchmark with a real-world application on the survey of Villa Farsetti and its park in Santa Maria di Sala, Italy. The benchmark compares four NRTK-enabled platforms (geodetic GNSS, handheld SLAM system, UAV, and DSLR with RTK Hotshoe tagging) against a topographic reference. The field campaign replicates the same NRTK toolchain on the villa’s architectural envelope and landscape, while defining an independent reference via a static GNSS-supported control network and static terrestrial laser scanning (TLS). Quality assessment is designed around point-based check residuals, baseline/scale diagnostics, and dense cloud-to-cloud and M3C2 comparisons to TLS reference clouds (Besl and McKay 1992). The study provides a practical, reproducible validation framework to decide when NRTK-only architectures can support 1:50–1:100 deliverables and when supplementary control is still required.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"18 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12518-026-00752-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148281174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving the accuracy of global geoid models in Persian Gulf and Oman sea using satellite altimetry observations","authors":"Hany Mahbuby,&nbsp;Rezvan Sahragard,&nbsp;Yazdan Amerian","doi":"10.1007/s12518-026-00768-1","DOIUrl":"10.1007/s12518-026-00768-1","url":null,"abstract":"<div><p>The geoid, an equipotential surface of the Earth's gravity field, serves as the fundamental vertical reference for national height systems and closely approximates Mean Sea Level (<i>MSL</i>), particularly over oceanic regions. While global geoid models such as EGM2008 and XGM2019e provide valuable large-scale representations, their accuracy can vary significantly across regions, especially in areas with sparse or low-quality data. In southern Iran, along the coasts of the Persian Gulf and the Oman Sea, high discrepancies have been observed between EGM2008 and GPS/levelling data, emphasizing the need for regional enhancement. This study aims to improve geoid accuracy in the Persian Gulf and Oman Sea by integrating satellite altimetry data from Jason-3 and Sentinel-3A with the global EGM2008 model, which serves as the background geoid. <i>MSL</i> estimate and Mean Dynamic Topography (<i>MDT</i>) model are derived from satellite altimetry observations and 0.125° × 0.125° global ocean <i>MDT</i> product of Copernicus Marine Environment Monitoring Service (CMEMS), respectively. The differences between altimetry-derived geoid heights and those from EGM2008—referred to as residuals—are interpolated on a regular spherical grid and used to locally correct the background model via statistical collocation. Cross-covariance and observation weight matrices are estimated using experimental variograms, covariance functions, and the Gaussian Process Regression (GPR) method to ensure accurate correction values. The resulting regionalized geoid model is validated against GPS/levelling-derived geometric geoid heights along the coastline, demonstrating substantially improved accuracy, with RMSE reduced to approximately 23 cm relative to EGM2008 and 21 cm relative to the more recent XGM2019e model. Spectral analysis further reveals that the constructed geoid primarily improves the long-wavelength structure of the model through regional-scale adjustments, which contributes to its enhanced overall accuracy.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"18 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148281376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal land use dynamics and emerging environmental challenges in Bangladesh: a sentinel-2 based CA-ANN study","authors":"Akramul Haque,&nbsp;Md Alamgir Hossin,&nbsp;Md. Tareq Aziz,&nbsp;Ovi Ranjan Saha,&nbsp;Sujit Kumar Roy","doi":"10.1007/s12518-026-00758-3","DOIUrl":"10.1007/s12518-026-00758-3","url":null,"abstract":"<div><p>This study investigated land-use changes in Bangladesh from 2017 to 2023 using Sentinel-2 data and projected trends for 2023–2030 using the Cellular Automata-Artificial Neural Network (CA-ANN) model. The findings revealed rapid urban expansion, with built-up areas increasing by 73.93% (2017–2020) and 12.89% (2020–2023). By 2030, built-up areas are expected to grow by 51.55%, leading to declines in forest cover (16.65%), water bodies (44.99%), and flooded vegetation (38.01%). These shifts pose severe environmental risks, including habitat fragmentation, biodiversity loss, increased runoff, and hydrological disruptions, exacerbating flood risks and land degradation. Although the study provided a comprehensive national-scale assessment, it did not account for policy shifts and population dynamics, which could influence future land use patterns. These findings emphasize the urgent need for sustainable land management and offer actionable insights for urban planners and policymakers to support sustainable urban growth, ecosystem conservation, and climate adaptation in Bangladesh.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"18 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148281245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating airborne laser scanning and hydrological modelling to quantify landscape controls on evapotranspiration in anthropogenic environments","authors":"Wioleta Błaszczak-Bąk,&nbsp;Monika Birylo","doi":"10.1007/s12518-026-00757-4","DOIUrl":"10.1007/s12518-026-00757-4","url":null,"abstract":"<div><p>Understanding how human-altered landscapes influence evapotranspiration (ET) remains a major challenge in hydrological modelling. This study develops an integrated framework combining Airborne Laser Scanning (ALS) and the Global Land Data Assimilation System (GLDAS) to quantify the effects of vegetation structure and topographic variability on ET in contrasting anthropogenic environments of northern and central Poland. ALS point clouds were processed to derive vegetation fraction and slope coefficient, which were then incorporated into the GLDAS-based ET estimates through a physically informed correction scheme. The modified approach enables differentiation between industrial, urban, and agricultural areas, linking their morphological characteristics with water and energy exchange processes. Results demonstrate that dense vegetation significantly suppresses ET amplitude by as much as eightfold compared to sparsely vegetated agricultural landscapes, while terrain slope exerts a secondary but measurable damping effect. Despite these spatial contrasts, the temporal synchrony of ET among all sites reveals strong regional climatic control. The method thus provides a scalable means to improve ET representation in hydrological models by explicitly accounting for canopy and terrain influences derived from high-resolution ALS data. This approach strengthens process understanding of water-energy feedback in human-modified environments and contributes to improved coupling between remote-sensing observations and physically based hydrological modelling frameworks. Quantitatively, ET amplitude decreased by approximately fourfold in the industrial, eightfold in the agricultural area, and by about 50% in the urban landscape after ALS-based correction. These reductions, closely linked to vegetation fraction (ranging from 11% to 53%) and terrain slope (4.66–29.29%), highlight the dominant role of canopy structure in regulating ET dynamics across diverse human-modified terrains.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"18 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12518-026-00757-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148281375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal trajectories of built-environment using centroid shift model: a directional understanding of urban evolution","authors":"Ashritha Keerthikumar,&nbsp;Gopal R. Patil,&nbsp;Krishna Mohan Buddhiraju","doi":"10.1007/s12518-026-00767-2","DOIUrl":"10.1007/s12518-026-00767-2","url":null,"abstract":"<div><p>For centuries, the evolution of the built environment has presented complex interactions between different urban features that demand continued research. This study addresses a gap in systematic directional approaches for geospatial urban planning by investigating the complex spatiotemporal evolution of the Mumbai Metropolitan Region (MMR) built environment from 1975 to 2019. To statistically validate this relationship beyond intuitive observations, our research sought to quantify the built environment’s distribution, growth intensity, and orientation. The methodology employed here is the spatial-geometric Centroid Shift Model, computing area-weighted centroids from multi-source satellite data across five distinct periods (1975, 1990, 1999, 2009, and 2019) for the cities within MMR. It quantifies the direction and magnitude of urban growth through shift vectors across cities and computes a net growth direction using vector summation. The study classifies cities into uni, bi, and multi-directional growth patterns based on variation in shift angle and distance, as well as their behaviour. These classifications and spatial metrics inform evidence-based planning strategies for corridor development, densification, or zoning interventions. To further evaluate whether urbanization follows planned infrastructure, cosine similarity is applied between centroid shift angles and transport azimuths. This research provides a robust and foundational framework for a directional understanding of urban growth patterns, filling a critical gap in urban planning methodology. Additionally, the study demonstrates a scalable, data-efficient method that relies on minimal inputs, making it adaptable for other rapidly urbanizing or resource-constrained regions. This novel approach can also optimize assumptions in future growth prediction models.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"18 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148281244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monitoring morphological changes of Alpine glaciers using GEDI: Evaluation of potentials and challenges","authors":"Alireza Hamoudzadeh,&nbsp;Roberta Ravanelli,&nbsp;Mattia Crespi","doi":"10.1007/s12518-026-00746-7","DOIUrl":"10.1007/s12518-026-00746-7","url":null,"abstract":"<div><p>Glaciers are essential components of Alpine ecosystems and are increasingly vulnerable to climate change, making their routine monitoring a critical task. In this study, we present a novel approach based on Global Ecosystem Dynamics Investigation (GEDI) Light Detection and Ranging (LiDAR) altimetry data. Fully implemented within Google Earth Engine (GEE), the proposed workflow includes an efficient outlier removal procedure that relies solely on the information available within GEDI data. We demonstrate the application of this workflow to three Alpine glaciers across nine GEDI acquisitions and evaluate its performance through comparisons with reference Digital Surface Models (DSMs) derived from aerial and drone photogrammetry. The application of the proposed workflow yielded glacier profiles along GEDI tracks providing valuable surface elevation information. The results show an overall strong agreement (correlation &gt; 0.99 and overall mean R² of 0.99) with the reference DSMs, as well as low overall median difference of 0.76 m. Our findings suggest that GEDI is capable of detecting seasonal variations in glacier morphology. Although GEDI does not offer complete coverage of a glacier, as photogrammetric block imagery typically does, its higher acquisition rate, even over small glaciers, makes it a valuable complementary data source. Integrating GEDI with other established approaches, such as photogrammetric and LiDAR surveys, can therefore enhance the continuity and consistency of glacier monitoring over time.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"18 3","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148172842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urban land cover characterization using PRISMA hyperspectral imagery and machine learning algorithms","authors":"Zohaib,&nbsp;Sawaid Abbas","doi":"10.1007/s12518-026-00747-6","DOIUrl":"10.1007/s12518-026-00747-6","url":null,"abstract":"<div><p>Rapid urbanization and environmental pressures cause heat stress, loss of open spaces, expansion of impervious surfaces, and flood risk, highlighting the need for precise spatial data for resilient planning and sustainable urban development. Hyperspectral remote sensing integrated with machine learning (ML) offers new opportunities to understand complex urban land use and land cover (LULC) patterns. This study evaluates the potential of PRISMA hyperspectral imagery for characterizing LULC in a diverse urban environment. We employed six machine learning classifiers: Random Forest (RF), Gradient Tree Boosting (GTB), Artificial Neural Network (ANN), Support Vector Machine (SVM), Classification and Regression Tree (CART), and K-nearest Neighbors (KNN) to map different land cover types. The algorithms used 1712 sample points, with a split ratio of 70% for training and 30% for validation, along with extensive hyperparameter tuning. The performance of these algorithms were evaluated using Overall Accuracy (OA), Kappa index, and performance overall (POA), based on metrics such as recall, F1-score, precision, accuracy (ACC), and Matthews correlation coefficient (MCC). The results demonstrate that PRISMA hyperspectral imagery can accurately identify complex land cover types across urban landscapes, with the SVM classifier outperforming others (OA = 93.16%, POA = 2.8087), compared to ANN, RF, and GTB classifiers. Urban classes were discriminated with high accuracy, demonstrating the potential of PRISMA to recognize heterogeneous built-up conditions. The findings of this study also demonstrate how PRISMA can provide the geospatial information for policy, enabling urban monitoring and supporting climate-sensitive, resilience-focused urban planning.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"18 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148172291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GIS-based delineation of groundwater potential zones in the Mehran Plain using meta-heuristic optimization techniques","authors":"Alireza Vafaeinejad,&nbsp;Sasan Mahmoudi Jam,&nbsp;Alireza Sharifi","doi":"10.1007/s12518-026-00749-4","DOIUrl":"10.1007/s12518-026-00749-4","url":null,"abstract":"<div><p>Groundwater is a critical resource for sustainable development and agriculture in arid regions, such as the Mehran Plain, where accurate delineation of potential zones is essential. This study delineates Groundwater Potential Zones (GWPZs) by integrating GIS with four meta-heuristic optimization algorithms: Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), and Invasive Weed Optimization (IWO). Fourteen thematic layers were weighted using each algorithm to generate GWPZ maps. The novelty of this research lies in the systematic performance comparison and dual-scenario weighting (well-density (well-d) and specific yield (Sy)) of these meta-heuristics. We validated the GWP maps against a Groundwater Flow Intensity-Direction (GFID) map. Quantitative results show that PSO_well-d achieved the highest accuracy with a spatial overlap of 80.2% and an RMSE of 0.202. The ‘Very Suitable’ zones cover 15.4% of the plain, primarily in the western sectors. The integration of GIS with meta-heuristic optimization provides an efficient, data-driven framework for groundwater resource planning in environmentally stressed regions.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"18 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148173282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing shoreline dynamics in southwestern Madagascar, using DSAS tools","authors":"Sitrakiniaina Ramarokoto,&nbsp;Léa R. J. Raharijaona,&nbsp;Rijasoa H. Ravonjimalala,&nbsp;Rina Ramahandrisoa,&nbsp;Josoa R. Randriamalala","doi":"10.1007/s12518-026-00750-x","DOIUrl":"10.1007/s12518-026-00750-x","url":null,"abstract":"<div><p>The phenomenon of Shoreline erosion may cause significant ecological and economic losses, including degradation of biodiversity and deterioration of infrastructure. To date, the majority of studies on shoreline dynamics have concentrated on the description of its temporal evolution. Nevertheless, there is a paucity of research addressing the factors that modulate these coastal dynamics. The present study aims to identify the principal factors influencing the shoreline dynamics, with a focus on the coasts of southwestern Madagascar, which encompass extensive mangrove areas. In order to observe the processes of coastal retreat (erosion) and advance (accretion), satellite images from different dates (1990/2000/2010/2020) were analysed using Digital Shoreline Analysis System (DSAS) tools. These processes were also associated with set variables that have the potential to act as drivers of shoreline dynamics. These included coastal land use (presence/absence of mangroves), distance to the nearest river mouth, Bouguer anomaly, which serves as a proxy for tectonic subsidence risk, and foreshore slope. The variables were derived from three distinct sources: the 2020 vegetation map of the study site, the digital topographic map of Madagascar, and the Bouguer gravity anomaly map of Madagascar. Ultimately, a co-inertia analysis was employed to determine the relative importance of the variables in shoreline dynamics. The shoreline of the study site is predominantly subjected to erosion, which appears to be worsening over time. The occurrence of shoreline erosion was found to be significantly linked to proximity to river mouths and high Bouguer anomaly. Mangroves have played a negligible role in shoreline accretion, while their absence is the primary factor in erosion.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"18 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148173283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance analysis of global PPP-zenith tropospheric delay estimation using mixed GPS/GLONASS observations","authors":"Ashraf Farah","doi":"10.1007/s12518-026-00751-w","DOIUrl":"10.1007/s12518-026-00751-w","url":null,"abstract":"<div><p>GNSS signals suffer delay through different layers of earth’s atmosphere. The troposphere layer causes a delay to GNSS observations due to a change in the refractive index of the medium. The troposphere could create a delay of more than 2 m at zenith and 20 m at lower satellite-elevation angles of 10 degrees and below. Precise Point Positioning (PPP) is a standalone approach that uses undifferenced and differenced single and dual frequency pseudo-range and carrier phase observations along with precise satellite orbit and clock products to produce centimetres to millimetres positioning in real time and post-processing mode. The Zenith Tropospheric Delay (ZTD) is estimated alongside with the position unknowns in PPP. PPP-ZTD estimates are useful for meteorological applications. IGS (International GNSS Service) is a voluntary federation of over 200 self-funding agencies in more than 100 countries. IGS provides the highest-quality GNSS data, products, and services in support of the GNSS community. IGS provides ZTD for its permanent stations with utmost accuracy of 4 mm. This research investigates accuracy of PPP-ZTD estimates comparing with IGS-ZTD estimates (reference) for seven different latitude IGS stations in southern and northern hemisphere. PPP-ZTD were estimated using mixed GPS/GLONASS observations through CSRS-PPP online service. The study covers four different weeks to reflect different seasons. it can be concluded that PPP-ZTD estimates have strong agreement with IGS-estimates. PPP-ZTD differences with IGS-estimates have mean, maximum, minimum and standard deviation of 1.5 mm, 3.1 cm, 2.2 cm and 6 mm respectively.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"18 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148172683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}