Wallerman, Jörgen
- Department of Forest Resource Management, Swedish University of Agricultural Sciences
Conference paper2023Peer reviewed
ForestMap: Mapping Forest Attributes Across the Globe - First Case Study
Fransson, Johan E. S.; Sertel, Elif; Unsalan, Cem; Salo, Jari; Holmstrom, Anton; Wallerman, Jorgen; Nilsson, Mats
Abstract
This paper presents the project ForestMap - a project aiming to develop and distribute new methods, which provide the benefits of accurate forest maps to a global audience. Using the recent developments in remote sensing, machine learning, and Artificial Intelligence (AI) the goal is to export the Scandinavian success stories to a wide range of stakeholders in the world.
Keywords
Forest; map; global; machine learning; Artificial Intelligence
Published in
IEEE International Geoscience and Remote Sensing Symposium proceedings
2023, pages: 3395-3397
Title: IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
eISBN: 979-8-3503-2010-7
Publisher: IEEE
Conference
IEEE International Geoscience and Remote Sensing Symposium (IGARSS), JUL 16-21, 2023, Pasadena, CA
Nilsson, Mats
- Department of Forest Resource Management, Swedish University of Agricultural Sciences
- Department of Forest Resource Management, Swedish University of Agricultural Sciences
SLU Authors
UKÄ Subject classification
Forest Science
Remote Sensing
Publication identifier
DOI: https://doi.org/10.1109/IGARSS52108.2023.10283354
Permanent link to this page (URI)
https://res.slu.se/id/publ/129042