Characterizing the Sea-Ice Floe Size Distribution in the Canada Basin from High-Resolution Optical Satellite Imagery
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
Characterizing the Sea-Ice Floe Size Distribution in the Canada Basin from High-Resolution Optical Satellite Imagery ; day:14 ; month:12 ; year:2021 ; pages:1-20 ; extent:20
The Cryosphere discussions ; (14.12.2021), 1-20 (gesamt 20)
- Urheber
-
Denton, Alexis Anne
Timmermans, Mary-Louise
- DOI
-
10.5194/tc-2021-368
- URN
-
urn:nbn:de:101:1-2021121604151051497732
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
27.08.2022, 07:30 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
- Denton, Alexis Anne
- Timmermans, Mary-Louise
Ähnliche Objekte (12)
A NEW OPTIMIZED RFM OF HIGH-RESOLUTION SATELLITE IMAGERY
Sat-SINR: High-Resolution Species Distribution Models Through Satellite Imagery
Dike-induced aquifer models derived from high-resolution multi-spectral satellite imagery
Estimating the uncertainty of sea-ice area and sea-ice extent from satellite retrievals
Estimating the uncertainty of sea-ice area and sea-ice extent from satellite retrievals
Deep learning for detecting and characterizing oil and gas well pads in satellite imagery
Satellite Imagery in Agriculture
GEOMEMBRANE BASINS DETECTION BASED ON SATELLITE HIGH-RESOLUTION IMAGERY USING DEEP LEARNING ALGORITHMS
Mapping of temperate upland habitats using high-resolution satellite imagery and machine learning
POTENTIAL EXPLORATION OF SEGMENTATION DRIVEN STEREO MATCHING OF VERY HIGH-RESOLUTION SATELLITE IMAGERY
Characterizing the Spatial and Temporal Availability of Very High Resolution Satellite Imagery for Monitoring Applications
Assessing Usefulness of High-Resolution Satellite Imagery (HRSI) for Re-Survey of Cadastral Maps
A NEW OPTIMIZED RFM OF HIGH-RESOLUTION SATELLITE IMAGERY
Sat-SINR: High-Resolution Species Distribution Models Through Satellite Imagery
Dike-induced aquifer models derived from high-resolution multi-spectral satellite imagery
Estimating the uncertainty of sea-ice area and sea-ice extent from satellite retrievals
Estimating the uncertainty of sea-ice area and sea-ice extent from satellite retrievals
Deep learning for detecting and characterizing oil and gas well pads in satellite imagery
Satellite Imagery in Agriculture
GEOMEMBRANE BASINS DETECTION BASED ON SATELLITE HIGH-RESOLUTION IMAGERY USING DEEP LEARNING ALGORITHMS
Mapping of temperate upland habitats using high-resolution satellite imagery and machine learning
POTENTIAL EXPLORATION OF SEGMENTATION DRIVEN STEREO MATCHING OF VERY HIGH-RESOLUTION SATELLITE IMAGERY
Characterizing the Spatial and Temporal Availability of Very High Resolution Satellite Imagery for Monitoring Applications
Assessing Usefulness of High-Resolution Satellite Imagery (HRSI) for Re-Survey of Cadastral Maps
A NEW OPTIMIZED RFM OF HIGH-RESOLUTION SATELLITE IMAGERY
Sat-SINR: High-Resolution Species Distribution Models Through Satellite Imagery
Dike-induced aquifer models derived from high-resolution multi-spectral satellite imagery
Estimating the uncertainty of sea-ice area and sea-ice extent from satellite retrievals
Estimating the uncertainty of sea-ice area and sea-ice extent from satellite retrievals
Deep learning for detecting and characterizing oil and gas well pads in satellite imagery
Satellite Imagery in Agriculture
GEOMEMBRANE BASINS DETECTION BASED ON SATELLITE HIGH-RESOLUTION IMAGERY USING DEEP LEARNING ALGORITHMS
Mapping of temperate upland habitats using high-resolution satellite imagery and machine learning
POTENTIAL EXPLORATION OF SEGMENTATION DRIVEN STEREO MATCHING OF VERY HIGH-RESOLUTION SATELLITE IMAGERY
Characterizing the Spatial and Temporal Availability of Very High Resolution Satellite Imagery for Monitoring Applications