Mangrove species mapping using Sentinel-1 and Sentinel-2 Data in North Vietnam

Tien Dat Pham, Junshi Xia, Gerald Baier, Nga Nhu Le, Naoto Yokoya

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

4 Citations (Scopus)

Abstract

This study employed Sentinel-1A C-band and Sentinel-2A multispectral data combined with the decision tree ensemble algorithms to map the spatial distribution of five mangrove communities in a coastal area in North Vietnam. The results show that the rotation forests (RoFs) model achieved better overall accuracy and kappa coefficient in mapping mangrove species than those of the canonical correlation forests (CCFs) and the random forests (RFs) models. This research demonstrates the potential of using optical and SAR data together with machine learning techniques to map mangrove species in tropical areas.

Original languageEnglish
Title of host publication2019 IEEE International Geoscience and Remote Sensing Symposium
Subtitle of host publicationproceedings
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages6102-6105
Number of pages4
ISBN (Electronic)9781538691540, 9781538691533
ISBN (Print)9781538691557
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Yokohama, Japan
Duration: 28 Jul 20192 Aug 2019

Publication series

Name
ISSN (Print)2153-6996
ISSN (Electronic)2153-7003

Conference

Conference39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
CountryJapan
CityYokohama
Period28/07/192/08/19

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