Repository logo
Home
Research Outputs
Collections
Statistics
Shared Repository Homepage
  1. Home
  2. Cultural Heritage Shared Repository Service
  3. Royal Botanic Gardens, Kew
  4. Article
  5. Canopy height Mapper: A google earth engine application for predicting global canopy heights combining GEDI with multi-source data.

Canopy height Mapper: A google earth engine application for predicting global canopy heights combining GEDI with multi-source data.

Resource type
Journal article
Creator (person)
Alvites, Cesar
ORCIDORCID logo
O'Sullivan, Hannah
ORCIDORCID logo
Francini, Saverio
ORCIDORCID logo
Marchetti, Marco
ORCIDORCID logo
Santopuoli, Giovanni
ORCIDORCID logo
Chirici, Gherardo
ORCIDORCID logo
Lasserre, Bruno
ORCIDORCID logo
Marignani, Michela
ORCIDORCID logo
Bazzato, Erika
ORCIDORCID logo
Date published
November 18, 2024
Funder
Funder nameAwards
European Commission, European Union
Establishing Urban Forest-based Solutions In Changing Cities (EUFORICC), the ForestWard Observatory to Secure Resilience of European Forests (FORWARDS) project. - National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.5 - Call for tender No.3277
Ministero dell’Istruzione, dell’Università e della Ricerca, Italy
PRIN 2020 Research Project of National Relevance (protocol 2020E52THS - Missione 4 Component 2, “Dalla ricerca all'impresa”, Investment 1.4, Project CN00000033 - Project Code ECS0000038 – Project Title eINS Ecosystem of Innovation for Next Generation Sardinia – CUP F53C22000430001- Grant Assignment Decree No. 1056
Horizon 2020 Framework Programme, European Union
The Systemic solutions for upscaling of urgent ecosystem restoration for forest related biodiversity and ecosystem services (SUPERB) project, grant number 101036849, call LC-GD-7-1-2020
European Forest Institute, Finland
European Forest Institute's Network Fund (grant G-01-2021)
Natural Environment Research Council, United Kingdom
Grant number NE/P012345/1
Journal title
Environmental Modelling & Software
Volume
183
Article number
106268
Publisher
Elsevier BV
Place of publication
Amsterdam, Netherlands
ISSN
1364-8152
eISSN
1873-6726
Date accepted
November 10, 2024
Official URL
https://doi.org/10.1016/j.envsoft.2024.106268
Related URL
https://linkinghub.elsevier.com/retrieve/pii/S1364815224003293
Rights statement
In Copyright
Licence
https://creativecommons.org/licenses/by/4.0/
DOI
10.1016/j.envsoft.2024.106268
Keywords
Remote sensing
Sentinel
GEE web app
Local-to-country calibrated model
Forest monitoring
Machine learning
Additional information
IF = 4.6 (2024)
Managed by the British Library and supported by the AHRC

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Cookie settings
  • End User Agreement
  • About
  • Contact
  • Help
Repository logo COAR Notify