The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/14095777

Adriaan van Natijne; Thom bogaard; Freek van Leijen; R.F. Hanssen; Roderik Lindenbergh (2022): World-wide InSAR sensitivity index data set for landslide deformation tracking. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/14095777.v1

Dataset

• Other Earth Sciences

Deformation tracking, InSAR, Landslides, Sensitivity index, Sentinel-1

Data derived from a digital elevation model acquired 2010-2015.

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Adriaan van Natijne , Thom bogaard , Freek van Leijen , R.F. Hanssen , Roderik Lindenbergh

The application of InSAR deformation measurements is feasible in a geometry sensitive to deformation. Our sensitivity index is a static analysis of the lower bound of the sensitivity of Sentinel-1 to the downslope deformation of a potential landslide.

The full process is explained in the linked paper (_{https://doi.org/10.1016/j.jag.2022.102829}). Provided here is a global data set of the sensitivity index derived from the Copernicus digital elevation model (COP-DEM_GLO-30, 2019_1).

Individual sheets of 1°×1° are identified by their lower left corner in WGS84. Sheets are combined in archives of 10°×10°, numbered by the truncated sheet indices (e.g. S49_00_W053.tiff is in S40_W050.zip). A sheet index is provided in _{S_v1.gpkg} and as an interactive map. No data is provided over Armenia and Azerbaijan, as these areas were not included in the public Copernicus data. The underlying Python script (_{20210208_CopernicusSpherical.py}) is provided with the data.

• 2022-06-08 first online, published, posted

4TU.ResearchData

GeoTiff

World-wide InSAR sensitivity index for landslide deformation tracking

• https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198

• OPEn-air laboRAtories for Nature baseD solUtions to Manage hydro-meteo risks (grant code 776848) [more info...] European Commission

Delft University of Technology, Faculty of Civil Engineering and Geosciences, Department of Geoscience & Remote Sensing
Delft University of Technology, Faculty of Civil Engineering and Geosciences, Department of Water Management