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| Formato: | Recurso digital |
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2026
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| Acceso en línea: | https://doi.org/10.5281/zenodo.18929451 |
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| _version_ | 1866901956914577408 |
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| author | Cusicanqui, Diego Laxroix, Pascal Bodin, Xavier |
| author_facet | Cusicanqui, Diego Laxroix, Pascal Bodin, Xavier |
| contents | <p>This dataset provides an <strong>expert-interpreted inventory of moving areas</strong> mapped from <strong>InSAR deformation signals</strong> in high-mountain environments. Each feature corresponds to a polygon delineating a zone where the <strong>deformation signal is spatially coherent</strong> over the considered observation period (i.e., a “moving area” suitable for geomorphological interpretation). The inventory was compiled to support <strong>regional-scale mapping</strong>, <strong>process-based interpretation</strong>, and—critically—the <strong>training and benchmarking of machine-learning algorithms</strong> for automated detection/classification of moving terrain from InSAR products.<br><br>All mapped moving areas were <strong>geomorphologically interpreted</strong> (e.g., rock glaciers, deep-seated gravitational slope deformation, landslides, other moving surfaces where relevant). For each polygon, the dataset reports a <strong>velocity range / kinematic class</strong> derived from the InSAR signal and expressed following the <strong>Rock Glacier Inventories and Kinematics (RGIK) guidelines</strong> for handling kinematic information and moving areas on rock glaciers. Where classification is uncertain (e.g., low coherence, seasonal decorrelation, mixed signals), the dataset documents the uncertainty through conservative labeling and/or attribute flags (if included).<br><br>InSAR-derived motion is sensitive to <strong>geometry (LOS projection)</strong>, <strong>temporal decorrelation</strong>, and <strong>atmospheric artefacts</strong>, and may not capture rapid failures or motion orthogonal to the radar line-of-sight. Users should therefore treat the inventory as an <strong>interpreted product</strong> (not a complete census of all instabilities) and propagate uncertainties when using it for hazard assessment or model calibration.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18929451 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Moving areas Inventory based on InsSAR wrapped interferograms Cusicanqui, Diego Laxroix, Pascal Bodin, Xavier <p>This dataset provides an <strong>expert-interpreted inventory of moving areas</strong> mapped from <strong>InSAR deformation signals</strong> in high-mountain environments. Each feature corresponds to a polygon delineating a zone where the <strong>deformation signal is spatially coherent</strong> over the considered observation period (i.e., a “moving area” suitable for geomorphological interpretation). The inventory was compiled to support <strong>regional-scale mapping</strong>, <strong>process-based interpretation</strong>, and—critically—the <strong>training and benchmarking of machine-learning algorithms</strong> for automated detection/classification of moving terrain from InSAR products.<br><br>All mapped moving areas were <strong>geomorphologically interpreted</strong> (e.g., rock glaciers, deep-seated gravitational slope deformation, landslides, other moving surfaces where relevant). For each polygon, the dataset reports a <strong>velocity range / kinematic class</strong> derived from the InSAR signal and expressed following the <strong>Rock Glacier Inventories and Kinematics (RGIK) guidelines</strong> for handling kinematic information and moving areas on rock glaciers. Where classification is uncertain (e.g., low coherence, seasonal decorrelation, mixed signals), the dataset documents the uncertainty through conservative labeling and/or attribute flags (if included).<br><br>InSAR-derived motion is sensitive to <strong>geometry (LOS projection)</strong>, <strong>temporal decorrelation</strong>, and <strong>atmospheric artefacts</strong>, and may not capture rapid failures or motion orthogonal to the radar line-of-sight. Users should therefore treat the inventory as an <strong>interpreted product</strong> (not a complete census of all instabilities) and propagate uncertainties when using it for hazard assessment or model calibration.</p> |
| title | Moving areas Inventory based on InsSAR wrapped interferograms |
| url | https://doi.org/10.5281/zenodo.18929451 |