APPLICATION OF RADAR AND OPTICAL SATELLITE IMAGERY DATA IN LANDSLIDE POTENTIAL MAPPING OF SHESHPEER SUB-CATCHMENT IN IRAN
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
APPLICATION OF RADAR AND OPTICAL SATELLITE IMAGERY DATA IN LANDSLIDE POTENTIAL MAPPING OF SHESHPEER SUB-CATCHMENT IN IRAN ; volume:XLII-4/W18 ; year:2019 ; pages:547-552
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLII-4/W18 (2019), 547-552
- Creator
-
Imanian, A.
Tangestani, M. H.
Asadi, A.
- DOI
-
10.5194/isprs-archives-XLII-4-W18-547-2019
- URN
-
urn:nbn:de:101:1-2019102405373698519265
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:21 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Imanian, A.
- Tangestani, M. H.
- Asadi, A.
Other Objects (12)
Radar Satellite Imagery for Detecting Bark Beetle Outbreaks in Forests
The SWADE model for landslide dating in time series of optical satellite imagery
A Systematic Exploration of Satellite Radar Coherence Methods for Rapid Landslide Detection
A systematic exploration of satellite radar coherence methods for rapid landslide detection
Integrating empirical models and satellite radar can improve landslide detection for emergency response
Satellite Imagery in Agriculture
Radar satellite imagery for humanitarian response. Bridging the gap between technology and application
Mapping Antarctic Crevasses and their Evolution with Deep Learning Applied to Satellite Radar Imagery
Mapping Antarctic crevasses and their evolution with deep learning applied to satellite radar imagery
Satellite radar data for back-analyzing a landslide event: the Ponzano (Central Italy) case study
A satellite-based global landslide model
HR-GLDD: A globally distributed dataset using generalized DL for rapid landslide mapping on HR satellite imagery
Radar Satellite Imagery for Detecting Bark Beetle Outbreaks in Forests
The SWADE model for landslide dating in time series of optical satellite imagery
A Systematic Exploration of Satellite Radar Coherence Methods for Rapid Landslide Detection
A systematic exploration of satellite radar coherence methods for rapid landslide detection
Integrating empirical models and satellite radar can improve landslide detection for emergency response
Satellite Imagery in Agriculture
Radar satellite imagery for humanitarian response. Bridging the gap between technology and application
Mapping Antarctic Crevasses and their Evolution with Deep Learning Applied to Satellite Radar Imagery
Mapping Antarctic crevasses and their evolution with deep learning applied to satellite radar imagery
Satellite radar data for back-analyzing a landslide event: the Ponzano (Central Italy) case study
A satellite-based global landslide model
HR-GLDD: A globally distributed dataset using generalized DL for rapid landslide mapping on HR satellite imagery
Radar Satellite Imagery for Detecting Bark Beetle Outbreaks in Forests
The SWADE model for landslide dating in time series of optical satellite imagery
A Systematic Exploration of Satellite Radar Coherence Methods for Rapid Landslide Detection
A systematic exploration of satellite radar coherence methods for rapid landslide detection
Integrating empirical models and satellite radar can improve landslide detection for emergency response
Satellite Imagery in Agriculture
Radar satellite imagery for humanitarian response. Bridging the gap between technology and application
Mapping Antarctic Crevasses and their Evolution with Deep Learning Applied to Satellite Radar Imagery
Mapping Antarctic crevasses and their evolution with deep learning applied to satellite radar imagery
Satellite radar data for back-analyzing a landslide event: the Ponzano (Central Italy) case study
A satellite-based global landslide model