ISPRS Open Journal of Photogrammetry and Remote Sensing最新文献

{"title":"Vision-based detection of safe landing zones for resource-constrained UAVs","authors":"Abduraouf Hassan,&nbsp;Rana Azzam,&nbsp;Khaled Salah,&nbsp;Abdulhadi Shoufan","doi":"10.1016/j.ophoto.2026.100140","DOIUrl":"10.1016/j.ophoto.2026.100140","url":null,"abstract":"<div><div>Reliable detection of safe landing zones is a fundamental requirement for autonomous UAV operations in real-world environments. Existing approaches rely on multi-sensor fusion and impose substantial onboard computational, power, and storage demands. Consequently, these methods are impractical for small, resource-constrained UAV platforms. This paper proposes a vision-based safe landing zone (SLZ) detection approach designed for real-time deployment onboard small UAVs. A custom safety-aware dataset is constructed from the ICG Semantic Drone dataset (ICG) (Institute of Visual Computing, 2019). The original semantic segmentation masks are reclassified using a four-level safety scheme that captures terrain suitability and proximity to hazards. A segmentation-to-detection algorithm is introduced to determine the optimal oriented bounding box (OBB) for each connected safe region within the mask. The resulting dataset is used to train compact YOLO-based detectors for real-time SLZ detection. To assess both detection performance and landing decision reliability, we introduce new coverage and decision-centric evaluation metrics, including mean Intersection-over-Allowed, Safe-Area Utilization, Safe Landing Success, and False-Safe Rate. Experimental results demonstrate up to 85% Safe Landing Success with less than 3% False-Safe Rate, while maintaining real-time throughput up to 50<!--> <!-->FPS using models with as few as 2.45<!--> <!-->M parameters. Compared with alternative approaches, our method offers a better balance between safety, accuracy, and efficiency, which makes it well suited for resource-constrained UAVs.</div></div>","PeriodicalId":100730,"journal":{"name":"ISPRS Open Journal of Photogrammetry and Remote Sensing","volume":"21 ","pages":"Article 100140"},"PeriodicalIF":7.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148737383","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":"Spatio-spectro-temporal characterisation and correction of dark current in a snapshot hyperspectral sensor","authors":"Vikas Sharma,&nbsp;Matthew Hayden,&nbsp;Eija Honkavaara,&nbsp;Surya Kant","doi":"10.1016/j.ophoto.2026.100145","DOIUrl":"10.1016/j.ophoto.2026.100145","url":null,"abstract":"<div><div>Low-cost uncooled snapshot hyperspectral sensors mounted on UAV platforms offer new opportunities for field-scale remote sensing high-throughput phenotyping, but their reliability is constrained by sensor-intrinsic artefacts, particularly dark current. In this study, we present the first spatio-spectro-temporal characterisation and correction of dark current in the Senop HSC-2 dual-CMOS Fabry-Perot snapshot hyperspectral camera. Six controlled dark experiments (∼7300 image cubes) revealed that dark current in the sensor is highly structured and reproducible, exhibiting CMOS-specific baseline offsets, monotonic temporal drift, pixel-wise dark signal non-uniformity (DSNU) with wavelength-dependent structure, and persistent hot pixels, and exposure-dependent baseline shifts that do not scale linearly with integration time. These results confirm that conventional single-frame dark subtraction is insufficient for quantitative analysis in uncooled snapshot hyperspectral sensors. Building on this characterisation, a modular correction framework was developed to stabilise the dark signal across spatial, spectral, and temporal domains. Across laboratory datasets, the framework reduced temporal drift by 70-85%, DSNU variance by approximately 37.5%, and suppressed &gt;99.9% of persistent hot pixels, substantially improving radiometric stability. Corrected data exhibited simultaneous spatial uniformity, temporal stability, and spectral integrity, enabling downstream radiometric processing without introducing spectral distortion. Application of Senop HSC-2 to UAV-acquired wheat canopy imagery demonstrated effective transfer to field conditions, improving spectral continuity and robustness of vegetation indices after dark current correction. These results establish a transferable calibration approach for affordable snapshot hyperspectral sensors and demonstrate that rigorous dark current correction is essential for achieving quantitative radiometric performance in UAV-based phenotyping and precision agriculture applications without active thermal control, extending calibration principles traditionally applied in satellite hyperspectral systems to low-cost UAV snapshot sensors.</div></div>","PeriodicalId":100730,"journal":{"name":"ISPRS Open Journal of Photogrammetry and Remote Sensing","volume":"21 ","pages":"Article 100145"},"PeriodicalIF":7.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148738849","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":"JB3D: An aerial video dataset with per-frame camera poses and LiDAR ground truth for multi-view stereo and novel view synthesis benchmarking","authors":"M. Hermann,&nbsp;D. Böhmer,&nbsp;S. Hinz,&nbsp;M. Weinmann","doi":"10.1016/j.ophoto.2026.100149","DOIUrl":"10.1016/j.ophoto.2026.100149","url":null,"abstract":"<div><div>Image-based 3D reconstruction from unmanned aerial vehicles is crucial for many applications like navigation, environmental monitoring, or creating digital twins. However, real-world aerial footage introduces unconstrained motion, scale variation and dynamic elements that challenge current methods. Existing benchmarks address many of these aspects while providing valuable LiDAR ground truth, but only a few ground-based benchmarks provide video data with camera poses, often operating at lower frame rates or lower image resolutions, and most aerial benchmarks primarily offer still images only. To address this issue, we introduce JB3D: an aerial video dataset designed for benchmarking multi-view stereo and novel view synthesis approaches in realistic outdoor environments. Captured over the course of a two-day outdoor festival featuring challenging scenery, including fine structures and dynamic elements such as moving cars and people, JB3D comprises 14 UAV videos at 30 FPS, five LiDAR scans, high-resolution RGB and thermal infrared images. To accurately reflect real-world operating conditions such as infrastructure monitoring, crowd counting, or supporting emergency response forces, all flight trajectories for video acquisition were controlled manually. All the data are registered in a single ECEF/ENU coordinate frame. The novelty compared to other benchmark datasets relates to the per-frame camera poses, for which reference data are provided, too. They enable reconstruction from individual sequences, multi-sequence evaluation and cross-day change detection. Alongside baseline results from conventional, learning-based, and advanced scene representation approaches, we release evaluation and visualization routines (<span><span>https://github.com/JB3D-Dataset/Multi-View-Stereo</span><svg><path></path></svg></span>). In addition, we provide insights into how the strengths and weaknesses of chosen evaluation metrics affect the outcome by employing established metrics, such as L1-abs, F1-Score and Chamfer distance.</div></div>","PeriodicalId":100730,"journal":{"name":"ISPRS Open Journal of Photogrammetry and Remote Sensing","volume":"21 ","pages":"Article 100149"},"PeriodicalIF":7.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148951548","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":"A critical synthesis of uncertainty quantification and foundation models in monocular depth estimation","authors":"Steven Landgraf,&nbsp;Rongjun Qin,&nbsp;Markus Ulrich","doi":"10.1016/j.ophoto.2026.100146","DOIUrl":"10.1016/j.ophoto.2026.100146","url":null,"abstract":"<div><div>Recent foundation models have led to major breakthroughs in monocular depth estimation (MDE), enabling dense 3D reconstruction from single-view imagery across a wide range of domains. However, safe and reliable deployment — particularly for metric depth estimation, which involves predicting absolute distances in real-world units — remains an open challenge. Even state-of-the-art foundation models are prone to critical errors, raising concerns for applications in photogrammetry, robotics, and remote sensing. Equipping these massive Vision Transformers with uncertainty quantification (UQ) is highly non-trivial; standard UQ methods often fail to scale, and it remains an open question how internet-scale pre-training and subsequent metric fine-tuning alter a model’s uncertainty quality. To address these limitations, we integrate five scalable UQ methods with the DepthAnythingV2 foundation model to obtain pixel-wise uncertainty estimates alongside metric depth predictions. We evaluate these combinations across four diverse datasets, including indoor scenes, outdoor urban environments, synthetic-to-real data, and high-resolution aerial imagery. Our findings identify fine-tuning with the Gaussian Negative Log-Likelihood Loss as particularly promising, yielding reliable uncertainty estimates while preserving predictive performance and computational efficiency. By successfully adapting UQ to foundation models, this work advances toward more interpretable and trustworthy MDE pipelines, with direct implications for real-world photogrammetric workflows relying on single-view imagery.</div></div>","PeriodicalId":100730,"journal":{"name":"ISPRS Open Journal of Photogrammetry and Remote Sensing","volume":"21 ","pages":"Article 100146"},"PeriodicalIF":7.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148951746","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":"Spatio-temporal compliance monitoring in land administration using an earth observation–enabled LADM framework","authors":"Okan Yılmaz,&nbsp;Mehmet Alkan","doi":"10.1016/j.ophoto.2026.100124","DOIUrl":"10.1016/j.ophoto.2026.100124","url":null,"abstract":"<div><div>Land Administration Systems (LAS) have traditionally been designed as systems where legal records are updated through formal transactions, yet physical reality monitoring remains largely reactive. While these systems effectively record legal rights (tenure), land use restrictions (planning), and development rights (permits), the physical reality of the world is inherently dynamic. Consequently, the monitoring of conformity between de facto changes on the land (e.g., unauthorized construction, land use discrepancies) and the legal functions defined within LAS must evolve to keep pace with this dynamism. In rapidly developing nations such as Türkiye, verifying the compliance of physical development with spatial plans necessitates continuous spatio-tempoaral monitoring. This necessity also extends to the detection of cadastral boundary encroachments. While the archive of the earth surface provided by aerial photography and satellite imagery enables the 2D and 3D comparison of legal and physical status, the temporal archival of these records serves the 4th dimension of land administration. This study aims to design the LADM Country Profile for Türkiye regarding land administration functions and to facilitate the compliance checking of legal-physical status using remote sensing data. The functionality of the proposed model was tested at the instance level using temporal satellite imagery derived from Google Earth Engine (GEE). The results obtained from various case studies demonstrate that the proposed Türkiye Country Profile offers comprehensive solutions for sustainable land-use governance.</div></div>","PeriodicalId":100730,"journal":{"name":"ISPRS Open Journal of Photogrammetry and Remote Sensing","volume":"20 ","pages":"Article 100124"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147859407","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":"New approaches of handling waves in photo-bathymetry","authors":"Hans-Gerd Maas ,&nbsp;Hannes Sardemann ,&nbsp;Christian Mulsow ,&nbsp;Laure-Anne Gueguen ,&nbsp;Gottfried Mandlburger","doi":"10.1016/j.ophoto.2026.100127","DOIUrl":"10.1016/j.ophoto.2026.100127","url":null,"abstract":"<div><div>Stereo-photogrammetric measurements under water with a camera placed outside the water require modelling refraction. In the case of a wavy, non-stationary natural water surface, this requires spatio-temporal modelling, which may become rather complex. This paper gives an overview on novel methods for consideration of non-stationary water surfaces in photogrammetric approaches recently developed in a joint research project between TU Dresden and TU Wien. We first introduce a comprehensive and rigorous model, which reconstructs the water surface from multi-view imagery with cubic splines in a simultaneous bundle block adjustment, allowing us to introduce water bottom point coordinates together with camera orientation parameters and water surface model parameters as unknowns. The model is then extended to spatio-temporal water surface modelling based on short multi-view image sequences.</div><div>As an alternative approach, we introduce pixel-wise median filtering of short image sequences on the time axis to handle dynamic, wavy water surfaces, which allows to largely mitigate the distortions of underwater objects caused by the wavy water surface. In the resulting image, the water surface appears smoothed, and the 3D reconstruction underwater can be performed as if the water surface was horizontal. Such a sequence-based approach can either be formulated in image space or in object space. Both approaches, the image sequence median filtering and the simultaneous bundle block adjustment, are then combined into a two-step procedure for water bottom point and water surface parameter determination, avoiding effects of over-parametrization in practical applications with a rather large number of unknowns. First results obtained in several practical tests of the developed approaches indicate a substantial accuracy increase in underwater 3D point coordinate determination by about one order of magnitude, compared to processing the data under the assumption of a flat horizontal water surface.</div></div>","PeriodicalId":100730,"journal":{"name":"ISPRS Open Journal of Photogrammetry and Remote Sensing","volume":"20 ","pages":"Article 100127"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148178588","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":"UAS pose estimation based on image-assisted total stations","authors":"Lucas Dammert ,&nbsp;Jan Rhomberg-Kauert ,&nbsp;Camillo Ressl ,&nbsp;Tomas Thalmann ,&nbsp;David Monetti ,&nbsp;Hans-Berndt Neuner ,&nbsp;Gottfried Mandlburger","doi":"10.1016/j.ophoto.2026.100125","DOIUrl":"10.1016/j.ophoto.2026.100125","url":null,"abstract":"<div><div>The estimation of the pose, which is the position and orientation of a multi-sensor system, is a crucial part of the mapping process. The pose of an Uncrewed Aerial Systems (UAS) is typically estimated using satellite and inertial navigation systems, but it can also be estimated based on image-assisted total station (IATS) observations. Independent and absolute pose estimation based on IATS complements conventional GNSS/IMU-based orientation estimates and can improve the orientation. This is of particular relevance for survey scenarios where neither absolute nor relative ground control is available, which applies to most bathymetric survey scenes. In our study, we introduce a methodology for IATS-based orientation estimation alongside a simulation study and a practical implementation. We leverage direction vectors, derived from image observations of the IATS, to spherical targets on the UAS. We introduce these vectors in a least-squares adjustment to estimate the orientation angles of the platform. In a static, terrestrial experiment, we reached standard deviations of roll, pitch, and yaw angles between <span><math><mrow><mn>0</mn><mo>.</mo><mn>10</mn><mspace></mspace><mstyle><mo>deg</mo></mstyle><mspace></mspace><mtext>to</mtext><mspace></mspace><mn>0</mn><mo>.</mo><mn>15</mn><mspace></mspace><mstyle><mo>deg</mo></mstyle></mrow></math></span>, which confirms the uncertainty estimates of our Monte-Carlo simulation. For a real-world airborne experiment at the pre-alpine Pielach River, where a multi-copter UAV was used, we obtained deviations of <span><math><mrow><mn>0</mn><mo>.</mo><mn>26</mn><mspace></mspace><mstyle><mo>deg</mo></mstyle><mspace></mspace><mtext>to</mtext><mspace></mspace><mn>0</mn><mo>.</mo><mn>49</mn><mspace></mspace><mstyle><mo>deg</mo></mstyle></mrow></math></span> between two independent IATS. The results show that the most accurate angle is the yaw, with a deviation of <span><math><mrow><mn>0</mn><mo>.</mo><mn>26</mn><mspace></mspace><mstyle><mo>deg</mo></mstyle></mrow></math></span>, thus, validating the complementarity of the proposed method to the IMU. When evaluating the IATS-based orientations with poses estimated in a bundle-block adjustment, the deviations range from <span><math><mrow><mn>0</mn><mo>.</mo><mn>5</mn><mspace></mspace><mstyle><mo>deg</mo></mstyle><mspace></mspace><mtext>to</mtext><mspace></mspace><mn>1</mn><mo>.</mo><mn>0</mn><mspace></mspace><mstyle><mo>deg</mo></mstyle></mrow></math></span>.</div></div>","PeriodicalId":100730,"journal":{"name":"ISPRS Open Journal of Photogrammetry and Remote Sensing","volume":"20 ","pages":"Article 100125"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147945342","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":"Diagnostic spectral features for plastic litter detection in freshwater environments","authors":"Christine Atuhaire ,&nbsp;Ronald Semyalo ,&nbsp;Lydia Mazzi Kayondo ,&nbsp;Joyce Nakatumba Nabende ,&nbsp;Lydia Nakimbugwe ,&nbsp;Umar Katongole ,&nbsp;Anthony Gidudu","doi":"10.1016/j.ophoto.2026.100126","DOIUrl":"10.1016/j.ophoto.2026.100126","url":null,"abstract":"<div><div>Developing spectral-based algorithms for detecting plastics in natural environments requires an understanding of the spectral properties of plastic materials. However, spectral characterization of plastics and identification of diagnostic spectral features for plastic detection in natural freshwater environments remain unexplored. Unlike earlier studies that identified diagnostic spectral absorption features of plastics based on a single dominant background (either water-only or sand-only), we sought to identify features that account for the coexistence of multiple dominant background materials within the field of view. Spectral measurements were performed on plastic samples collected from the shores of Lake Victoria in Uganda using an SR-3501 Spectroradiometer. Three background surfaces (water, sand and vegetation) representative of the natural environment were selected and used as backgrounds for conducting spectral measurements. Several absorption features in plastic spectra, which aligned with earlier studies, were detected. However, the strength of these absorption features varied significantly across background surfaces, with coefficients of variation exceeding 20% for most features. Diagnostic spectral features for plastics were therefore identified based on freshwater shore zones. Absorption features centered at 1086 nm, 1660 nm, 1681 nm, 1714 nm, 1729 nm, 2054 nm, 2132 nm and 2156 nm were identified as diagnostic of plastic materials. Particularly, the 1729 nm feature was detected in more plastic samples than any other, making it particularly useful for developing plastic detection algorithms. While previous studies identified plastic absorption features in the ⁓930 nm-978 nm and ⁓1140 nm-1220 nm spectral ranges, this study revealed that, within these ranges, plastics and backgrounds have similar absorption characteristics and therefore cannot be spectrally differentiated using these absorption features.</div></div>","PeriodicalId":100730,"journal":{"name":"ISPRS Open Journal of Photogrammetry and Remote Sensing","volume":"20 ","pages":"Article 100126"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147859409","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":"DSM generation from VHR spaceborne imagery using deep learning-based land-cover-aware GCP extraction","authors":"Karlheinz Gutjahr,&nbsp;Ana Gregorac,&nbsp;Janik Deutscher,&nbsp;Roland Perko","doi":"10.1016/j.ophoto.2026.100123","DOIUrl":"10.1016/j.ophoto.2026.100123","url":null,"abstract":"<div><div>Accurate digital surface model (DSM) generation from very high-resolution satellite stereo imagery remains constrained by the labor-intensive requirement for manual ground control point (GCP) measurement. This work presents a fully automated deep learning framework that eliminates this bottleneck by combining SuperPoint feature detection with LightGlue matching to generate both tie-points (TP) between stereo image pairs and GCPs via correspondence with reference ortho-images. Both rely on the transformer architecture, on self- and cross-attention, and outperform traditional methods like SIFT, SURF, or ORB in terms of accuracy and speed. A critical innovation integrates land-cover-aware filtering to mitigate systematic height errors arising from geometric misalignments between reference ortho-images and digital elevation models, particularly in urban environments where inaccurate ortho-rectification produce unreliable GCP heights. The land cover itself is classified with a CCN-based architecture, specifically, a U-Net derivation with categorical focal loss and custom augmentation strategy in the training phase. Applied to a tri-stereo Pléiades dataset over Eisenstadt, Austria, the method automatically generates around 2000 filtered GCPs that achieve sub-meter planar accuracy (0.5m RMS in easting/northing) and approximately 2m vertical accuracy after block adjustment of rational polynomial coefficient sensor models. The proposed land-cover-aware method yields a lower RMS error in height of 0.55m w.r.t. the automated method. By replacing manual GCP measurement with deep learning-based automation and land-cover-aware quality control, this work completes the end-to-end workflow for rapid, high-precision DSM production across diverse terrain types, with direct applicability to urban mapping, change detection, and continental-scale monitoring missions.</div></div>","PeriodicalId":100730,"journal":{"name":"ISPRS Open Journal of Photogrammetry and Remote Sensing","volume":"20 ","pages":"Article 100123"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147631650","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":"Accuracy analysis and improvement of worldwide elevation models by ICESat-2 data","authors":"Karsten Jacobsen ,&nbsp;Gürcan Büyüksalih ,&nbsp;Cem Gazioglu","doi":"10.1016/j.ophoto.2026.100115","DOIUrl":"10.1016/j.ophoto.2026.100115","url":null,"abstract":"<div><div>Global or near global elevation models than TanDEM-X Edited Digital Elevation Model (EDEM), ALOS World 3D (AW3D), SRTM and ASTER GDEM (GDEM) show some systematic errors which can be determined and respected by accurate reference Digital Elevation Models (DEMs). Of course, if accurate DEMs are available, they can be used instead, but with ICESat-2 satellite LiDAR profiles accurate reference data are available that can be used to improve the freely available DEMs worldwide. The density of the ICESat-2 LiDAR ground points for the ATL08-data is limited to approximately 100 m in orbit direction and even just up to over 1 km between the orbits, but this is sufficient for improving the free DEMs. The correction can involve a simple elevation shift, a model tilt, or a correction by higher-order systematic errors.</div><div>A comparison with reference data from aerial survey revealed a bias in the range of ∼2m, which could also be due the aerial photogrammetric reference data. A comparison of the ICESat-2 data with the freely available AW3D and EDEM yielded satisfactory results, after improvement by bias and model tilt correction. The original RMSZ of EDEM compared to the reference DTM could be reduced from 2.23m to 1.30 m by height model tilt and shift determined by ICESat-2 and for AW3D from originally 1.81 m–1.64 m. In this data set, the influence of systematic errors is limited, it reduced the deformations slightly, but the accuracy numbers only had a negligible improvement. SRTM and ASTER GDEM should no longer be used due to their significantly lower accuracy compared to EDEM and AW3D.</div></div>","PeriodicalId":100730,"journal":{"name":"ISPRS Open Journal of Photogrammetry and Remote Sensing","volume":"19 ","pages":"Article 100115"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037617","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}