Exploring the Potential of Sentinel-2 Data for Tree Crown Mapping in Oak Agro-Forestry Systems

Hugo Costa, Ines Machado, Francisco D. Moreira, Pedro Benevides, Daniel Moraes, Mario Caetano

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

Abstract

Southern Portugal is characterized by disperse tree cover of Cork and Holm oaks in an agro-forestry system known as montado. Mapping these trees has been historically very difficult as they occur in isolation or in groups with different understory vegetation, including grass and shrubland. Automatic classification for binary tree/non-tree map production has been used elsewhere, but with limited success in the context of montado. Here, the potential of Sentinel-2 data was explored to map oaks using pure and mixed pixels to train a random forest. The output depicts a gradient of tree cover that can be transformed into a crisp map. The accuracy assessment of the latter shows commission and omission errors of 17% and 18%.
Original languageEnglish
Title of host publicationIGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium
Subtitle of host publicationProceedings
PublisherIEEE
Pages5807-5810
Number of pages4
ISBN (Print)978-1-6654-0369-6
DOIs
Publication statusPublished - 11 Jul 2021
EventIGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium - Brussels, Belgium
Duration: 11 Jul 202116 Jul 2021

Conference

ConferenceIGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium
Period11/07/2116/07/21

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