ForestMap: Mapping Forest Attributes Across the Globe - First Case Study

Johan E.S. Fransson*, Elif Sertel, Cem Unsalan, Jari Salo, Anton Holmstrom, Jorgen Wallerman, Mats Nilsson

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationIGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3395-3397
Number of pages3
ISBN (Electronic)9798350320107
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena, United States
Duration: 16 Jul 202321 Jul 2023

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2023-July

Conference

Conference2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Country/TerritoryUnited States
CityPasadena
Period16/07/2321/07/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Artificial Intelligence
  • Forest
  • global
  • machine learning
  • map

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