Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2022 10th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2022 |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (elektronisch) | 9781665470780 |
| ISBN (Print) | 978-1-6654-7079-7 |
| Publikationsstatus | Veröffentlicht - 2022 |
| Veranstaltung | 10th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2022 - Quebec City, Kanada Dauer: 11 Juli 2022 → 14 Juli 2022 |
Abstract
Remote sensing datasets are great resources to map habitat types. In this study, 3D habitat maps were generated using high-resolution multispectral imagery and a LiDAR-derived digital surface model (DSM). Two study areas in the United Kingdom (UK) were selected to investigate the potential of the developed models in habitat classification. The overall classification accuracies for the two study areas were high (91% and 82%), indicating the satisfactory performance of the developed approach for habitat mapping in the study areas. Overall, it was observed that a synergy of high-resolution multi-spectral imagery and LiDAR data could provide reliable 3D information on habitat types.
ASJC Scopus Sachgebiete
- Umweltwissenschaften (insg.)
- Management, Monitoring, Politik und Recht
- Agrar- und Biowissenschaften (insg.)
- Agronomie und Nutzpflanzenwissenschaften
- Agrar- und Biowissenschaften (insg.)
- Bodenkunde
- Erdkunde und Planetologie (insg.)
- Computer in den Geowissenschaften
- Informatik (insg.)
- Information systems
- Entscheidungswissenschaften (insg.)
- Informationssysteme und -management
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2022 10th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2022. Institute of Electrical and Electronics Engineers Inc., 2022.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - 3D Habitat Mapping Using High-Resolution Optical Satellite and Lidar Data
AU - Amani, Meisam
AU - Foroughnia, Fatemeh
AU - Moghimi, Armin
AU - Mahdavi, Sahel
PY - 2022
Y1 - 2022
N2 - Remote sensing datasets are great resources to map habitat types. In this study, 3D habitat maps were generated using high-resolution multispectral imagery and a LiDAR-derived digital surface model (DSM). Two study areas in the United Kingdom (UK) were selected to investigate the potential of the developed models in habitat classification. The overall classification accuracies for the two study areas were high (91% and 82%), indicating the satisfactory performance of the developed approach for habitat mapping in the study areas. Overall, it was observed that a synergy of high-resolution multi-spectral imagery and LiDAR data could provide reliable 3D information on habitat types.
AB - Remote sensing datasets are great resources to map habitat types. In this study, 3D habitat maps were generated using high-resolution multispectral imagery and a LiDAR-derived digital surface model (DSM). Two study areas in the United Kingdom (UK) were selected to investigate the potential of the developed models in habitat classification. The overall classification accuracies for the two study areas were high (91% and 82%), indicating the satisfactory performance of the developed approach for habitat mapping in the study areas. Overall, it was observed that a synergy of high-resolution multi-spectral imagery and LiDAR data could provide reliable 3D information on habitat types.
KW - 3D habitat mapping
KW - habitat
KW - LiDAR
KW - Worldview-2
UR - http://www.scopus.com/inward/record.url?scp=85137902385&partnerID=8YFLogxK
U2 - 10.1109/agro-geoinformatics55649.2022.9859127
DO - 10.1109/agro-geoinformatics55649.2022.9859127
M3 - Conference contribution
AN - SCOPUS:85137902385
SN - 978-1-6654-7079-7
BT - 2022 10th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2022
Y2 - 11 July 2022 through 14 July 2022
ER -