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1.
Towards the development of a landslide activity map in Slovenia
Mateja Jemec Auflič, Krištof Oštir, Tanja Grabrijan, Matjaž Ivačič, Tina Peternel, Ela Šegina, 2024, izvirni znanstveni članek

Povzetek: To create the landslide activity map, we implemented and tested the procedure to fully utilise the 6-day repeatability of the Sentinel-1 constellation in three pilot areas in Slovenia for the observation period from 2017 to 2021. The interferometric processing of the Sentinel-1 images was carried out with ENVI SARScape, while the interpretation of the persistent scatterers InSAR data was done in three steps. In the first step, a preliminary interpretation of the landslide areas was performed by integrating the PS InSAR data into a GIS environment with information that could be relevant to explain the movement patterns of the PS InSAR points. In the second step, a field validation was performed to check the PS InSAR in the field and record the potential damage to the objects indicating the slope mass movements. In the third step, the deformations were identified, and areas of significant movement were determined, consisting of clusters of at least 3 persistent scatterers (PS) with a maximum spacing of 10 m. The landslide activity map was created based on the landslide areas categorised into four classes based on the geotechnical analyses, yearly velocity data obtained by PS InSAR, and validation of annual velocity data obtained by in-situ and GNSS monitoring and field observation. A total of 21 polygons with different landslide activities were identified in three study areas. The overall methodology will help stakeholders in the early mapping and monitoring of landslides to increase the urban resilience.
Ključne besede: landslides, EO data, sentinel, time series, methodology, Slovenia
Objavljeno v DiRROS: 30.04.2024; Ogledov: 41; Prenosov: 6
.pdf Celotno besedilo (73,45 MB)

2.
Land surface phenology from satellite data : technical report
Urška Kanjir, Ana Potočnik Buhvald, Mitja Skudnik, Liza Stančič, Krištof Oštir, 2022, elaborat, predštudija, študija

Ključne besede: phenology, forest, remote sensing, MODIS, Sentinel-2, vegetation indices
Objavljeno v DiRROS: 29.12.2022; Ogledov: 461; Prenosov: 129
.pdf Celotno besedilo (4,52 MB)

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