APPLICATION OF RADAR AND OPTICAL SATELLITE IMAGERY DATA IN LANDSLIDE POTENTIAL MAPPING OF SHESHPEER SUB-CATCHMENT IN IRAN
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
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
- Urheber
-
Imanian, A.
Tangestani, M. H.
Asadi, A.
- DOI
-
10.5194/isprs-archives-XLII-4-W18-547-2019
- URN
-
urn:nbn:de:101:1-2019102405373698519265
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:21 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Imanian, A.
- Tangestani, M. H.
- Asadi, A.
Ähnliche Objekte (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