Semantic Navigation Mapping from Aerial Multispectral Imagery

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

2 Citations (Scopus)

Abstract

The emergence of Unmanned Aerial Vehicles (UAV) in the Precision Agriculture (PA) domain allowed decision support systems to have access to aerial images of the terrain surface. By exploiting multispectral aerial imagery, crop health analysis and terrain classification and mapping is possible. Therefore, this work proposes an open-source ROS-based (Robot Operating System) framework, capable of handling multispectral imagery and exploit it for terrain classification, building semantic maps structured by layers of vegetation, water, soil and rocks. The obtained experimental results were validated in the scope of several research projects funded by the Portuguese Rural Development Plan PDR2020, with success rates between 70% and 90%.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 28th International Symposium on Industrial Electronics, ISIE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1192-1197
Number of pages6
ISBN (Electronic)9781728136660
DOIs
Publication statusPublished - Jun 2019
Event28th IEEE International Symposium on Industrial Electronics, ISIE 2019 - Vancouver, Canada
Duration: 12 Jun 201914 Jun 2019

Publication series

NameIEEE International Symposium on Industrial Electronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Volume2019-June
ISSN (Print)2163-5137

Conference

Conference28th IEEE International Symposium on Industrial Electronics, ISIE 2019
CountryCanada
CityVancouver
Period12/06/1914/06/19

Keywords

  • Imagery Stitching
  • Multispectral Imagery
  • Precision Agriculture
  • Semantic Map
  • UAV

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