Investigating Sar-Optical Deep Learning Data Fusion to Map the Brazilian Cerrado Vegetation with Sentinel Data

Paulo Silva Filho*, Claudio Persello, Raian V. Maretto, Renato MacHado

*Corresponding author for this work

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

1 Downloads (Pure)

Abstract

Despite its environmental and societal importance, accurately mapping the Brazilian Cerrado's vegetation is still an open challenge. Its diverse but spectrally similar physiognomies are difficult to be identified and mapped by state-of-the-art methods from only medium-to high-resolution optical images. This work investigates the fusion of Synthetic Aperture Radar (SAR) and optical data in convolutional neural network architectures to map the Cerrado according to a 2-level class hierarchy. Additionally, the proposed model is designed to deal with uncertainties that are brought by the difference in resolution between the input images (at 10m) and the reference data (at 30m). We tested four data fusion strategies and showed that the position for the data combination is important for the network to learn better features.

Original languageEnglish
Title of host publicationIGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PublisherIEEE
Pages1365-1368
Number of pages4
ISBN (Electronic)9798350320107
DOIs
Publication statusPublished - 2023
Event43rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena Convention Center, Pasadena, United States
Duration: 16 Jul 202321 Jul 2023
Conference number: 43
https://2023.ieeeigarss.org/index.php

Publication series

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

Conference

Conference43rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Abbreviated titleIGARSS 2023
Country/TerritoryUnited States
CityPasadena
Period16/07/2321/07/23
Internet address

Keywords

  • Cerrado
  • deep learning
  • remote sensing
  • SAR-optical data fusion
  • semantic segmentation
  • 2024 OA procedure

Fingerprint

Dive into the research topics of 'Investigating Sar-Optical Deep Learning Data Fusion to Map the Brazilian Cerrado Vegetation with Sentinel Data'. Together they form a unique fingerprint.

Cite this