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ISPRS Open Journal of Photogrammetry and Remote Sensing
Scopus
ISSN 2667-3932 · Elsevier · 126 artikel di indeks
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Artikel Jurnal
Monitoring tropical forests with light drones: ensuring spatial and temporal consistency in stereophotogrammetric products
Light drones provide a cheap and effective tool to monitor forest canopy, especially in tropical and equatorial contexts, where infrastructure and resources are limiting. In these regions, good quality optical satellite images are rare, yet the stakes are maximal to characterize forest function…
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Transformer-driven monocular high-resolution DTM generation on mars via multimodal integration of CaSSIS imagery and MOLA altimetry
High-resolution digital terrain models (DTMs) are essential for geomorphological analysis of planetary surfaces, yet Martian topography remains constrained by the coarse resolution of global datasets such as MOLA and by the limited coverage of stereo-derived products. In this work, we present…
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Artikel Jurnal
Enhancing point cloud semantic segmentation via scalable domain adaptation with LoRA-enabled PointNet++
Semantic segmentation of airborne LiDAR point clouds enables a broad range of urban and environmental applications. However, domain shifts between training and operational data, as well as the frequent emergence of new semantic classes, pose significant challenges for deploying deep learning models…
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Calibration strategies for optical underwater 3D-sensors – a comparison of approaches
Precise three-dimensional reconstruction of underwater objects is required in many different applications. Optical 3D sensors are interesting due to their high accuracy potential and to their capability of simultaneous full-field measurements. Calibration of these systems for underwater use is…
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A critical synthesis of uncertainty quantification and foundation models in monocular depth estimation
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…
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Artikel Jurnal
LB-DL method: A hybrid framework of Laplacian-Beltrami with deep learning models for spectral–spatial enhancement of wildfire monitoring remote sensing imagery
Satellite imagery and remote sensing are suitable tools for monitoring and surveillance of the Earth. The use of this data to address various environmental challenges, from surveillance to risk management, is of great interest. In one of the applications of interest, satellite imagery is used for…
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Transferring instance and semantic segmentation across terrestrial laser scanning time series: towards automated forest monitoring plot measurements
Monitoring forest structural changes over time is important for sustainable management and ecological research. This requires repeated measurements on site, increasingly obtained using terrestrial laser scanning (TLS). However, conventional TLS-based methods are computationally intensive and not…
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Artikel Jurnal
Enhancing macrophyte sub-classification through neighborhood-independent full-waveform LiDAR
In the clear, shallow waters of the littoral zone, bathymetric LiDAR, SONAR, and photogrammetry have proven suitable for mapping both the underwater landscape and vegetation. In the past, all three methods have been used to map underwater vegetation, but automated workflows for sub-classification…
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Spatio-spectro-temporal characterisation and correction of dark current in a snapshot hyperspectral sensor
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…
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Artikel Jurnal
Multispectral airborne laser scanning dataset for tree species classification: MS-ALS-SPECIES
The shift from stand-level to individual-tree-level forest assessments supports improved species mapping and biodiversity monitoring, particularly in boreal ecosystems where tree species like aspen ( Populus tremula L.) play a keystone role. Airborne laser scanning (ALS) is the standard for such…
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Artikel Jurnal
Through-water and underwater photogrammetry for fossil exposure survey in shallow waters
Subaqueous fossiliferous outcrops constitute valuable yet poorly documented paleontological archives, particularly in fluvial environments where accessibility, hydrodynamic reworking, and rapid surface degradation hinder systematic investigation. This study introduces an application of…
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Artikel Jurnal
Enabling aerial localization and object detection through monocular height estimation: A hybrid deep learning solution
Accurate Digital Surface Models (DSMs) are fundamental to critical urban applications, including flood risk assessment, communication network line-of-sight planning, and 3D city modeling. However, traditional DSM generation relies heavily on expensive airborne LiDAR campaigns or multi-view stereo…
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Vision-based detection of safe landing zones for resource-constrained UAVs
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…
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Disentangling geometry and texture: An investigation into large-scale RGB-DSM pre-training for 3D urban understanding
Recent Earth observation foundation models have achieved strong transfer performance using large-scale self-supervised pre-training, but most remain primarily spectral or RGB-based and do not explicitly exploit geometric information from digital surface models (DSMs). This limits their…
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Artikel Jurnal
Topography-aware registration refinement of Landsat 8/9 L1TP products with Sentinel-2 L1C and NAIP orthoimages
Satellite orthoimage products are widely available, yet residual geometric misregistration across independently processed products remains common, limiting their direct interoperability for multi-source and multi-temporal analysis. This paper introduces a residual Multi-Layer Perceptron…
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Artikel Jurnal
SMOL-MapSeg: Segmenting historical maps by legend-oriented prompting
Historical maps offer valuable insights into Earth’s surface changes but pose challenges for modern segmentation models due to inconsistent visual styles and symbols. While deep learning models like UNet and pre-trained foundation models perform well in domains such as autonomous driving and…
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Artikel Jurnal
Evaluation of lab-based, hybrid, and in-situ radiometric calibration for TLS
Radiometric compensation is essential for obtaining accurate reflectance values from terrestrial laser scanning (TLS) intensities, yet it remains unclear which strategy best compensates for the impact of measurement configuration (angle of incidence (AOI), and distance) in terms of precision and…
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Artikel Jurnal
SIO-Mapper: A framework for lane-level HD map construction using satellite images and OpenStreetMap with no on-site visits
High-definition (HD) maps, particularly those containing lane-level information regarded as ground truth, are crucial for vehicle localization research. Traditionally, constructing HD maps requires highly accurate sensor measurements collection from the target area, followed by manual annotation to…
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Artikel Jurnal
Semi-automatic orientation and monoplotting of oblique images using the moniQue QGIS plugin: A case study of the Pasterze glacier in Austria
Monoplotting is a common technique for documenting landscape changes from a single image by intersecting image rays with a given elevation model. However, estimating the unknown camera parameters based on manually identified ground control points is time-consuming and hence prevents the large-scale…
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Artikel Jurnal
Mapping understorey tree invasion in a drought-affected forest using multi-view UAV imagery and deep learning
Advances in deep learning (DL) and structure from motion (SfM) photogrammetry combined with off-the-shelf unoccupied aerial vehicles (UAVs) and high-resolution cameras enable unprecedented plant species mapping accuracy. While these tools have been mainly applied to flat terrain or upper forest…