JAXA’s new high-resolution land use land cover map for Vietnam using a time-feature convolutional neural network
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
1 Online-Ressource.
- Language
-
Englisch
- Bibliographic citation
-
JAXA’s new high-resolution land use land cover map for Vietnam using a time-feature convolutional neural network ; volume:14 ; number:1 ; day:16 ; month:2 ; year:2024 ; pages:1-20 ; date:12.2024
Scientific reports ; 14, Heft 1 (16.2.2024), 1-20, 12.2024
- Creator
-
Truong, Van Thinh
Hirayama, Sota
Phan, Duong Cao
Hoang, Thanh Tung
Tadono, Takeo
Nasahara, Kenlo Nishida
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1038/s41598-024-54308-1
- URN
-
urn:nbn:de:101:1-2404240830097.016538037127
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:45 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
- Truong, Van Thinh
- Hirayama, Sota
- Phan, Duong Cao
- Hoang, Thanh Tung
- Tadono, Takeo
- Nasahara, Kenlo Nishida
- SpringerLink (Online service)
Other Objects (12)
VALIDATION OF THE GLOBAL HIGH-RESOLUTION GLOBELAND30 LAND COVER MAP IN EUROPE USING LAND COVER FIELD SURVEY DATABASE - LUCAS
REVIEW OF HIGH-RESOLUTION GLOBAL LAND COVER
MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAP
LCM2021 – the UK Land Cover Map 2021
CLASSIFICATION OF LAND COVER AND LAND USE BASED ON CONVOLUTIONAL NEURAL NETWORKS
QUALITY EVALUATION OF LAND-COVER CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK
LCM2021 – The UK Land Cover Map 2021
BENCHMARKING OF CONVOLUTIONAL NEURAL NETWORK APPROACHES FOR VEGETATION LAND COVER MAPPING
TOWARDS BETTER CLASSIFICATION OF LAND COVER AND LAND USE BASED ON CONVOLUTIONAL NEURAL NETWORKS
Towards better classification of land cover and land use based on convolutional neural networks
High-resolution land use/cover forecasts for Switzerland in the 21st century
Area-averaged evapotranspiration over a heterogeneous land surface: aggregation of multi-point EC flux measurements with a high-resolution land-cover map and footprint analysis
VALIDATION OF THE GLOBAL HIGH-RESOLUTION GLOBELAND30 LAND COVER MAP IN EUROPE USING LAND COVER FIELD SURVEY DATABASE - LUCAS
REVIEW OF HIGH-RESOLUTION GLOBAL LAND COVER
MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAP
LCM2021 – the UK Land Cover Map 2021
CLASSIFICATION OF LAND COVER AND LAND USE BASED ON CONVOLUTIONAL NEURAL NETWORKS
QUALITY EVALUATION OF LAND-COVER CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK
LCM2021 – The UK Land Cover Map 2021
BENCHMARKING OF CONVOLUTIONAL NEURAL NETWORK APPROACHES FOR VEGETATION LAND COVER MAPPING
TOWARDS BETTER CLASSIFICATION OF LAND COVER AND LAND USE BASED ON CONVOLUTIONAL NEURAL NETWORKS
Towards better classification of land cover and land use based on convolutional neural networks
High-resolution land use/cover forecasts for Switzerland in the 21st century
Area-averaged evapotranspiration over a heterogeneous land surface: aggregation of multi-point EC flux measurements with a high-resolution land-cover map and footprint analysis
VALIDATION OF THE GLOBAL HIGH-RESOLUTION GLOBELAND30 LAND COVER MAP IN EUROPE USING LAND COVER FIELD SURVEY DATABASE - LUCAS
REVIEW OF HIGH-RESOLUTION GLOBAL LAND COVER
MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAP
LCM2021 – the UK Land Cover Map 2021
CLASSIFICATION OF LAND COVER AND LAND USE BASED ON CONVOLUTIONAL NEURAL NETWORKS
QUALITY EVALUATION OF LAND-COVER CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK
LCM2021 – The UK Land Cover Map 2021
BENCHMARKING OF CONVOLUTIONAL NEURAL NETWORK APPROACHES FOR VEGETATION LAND COVER MAPPING
TOWARDS BETTER CLASSIFICATION OF LAND COVER AND LAND USE BASED ON CONVOLUTIONAL NEURAL NETWORKS
Towards better classification of land cover and land use based on convolutional neural networks
High-resolution land use/cover forecasts for Switzerland in the 21st century