Applying a phenological object-based image analysis (phenobia) for agricultural land classification: A study case in the Brazilian Cerrado

Hugo N. Bendini*, Leila M.G. Fonseca, Anderson R. Soares, Philippe Rufin, Marcel Schwieder, Marcos A. Rodrigues, R.V. Maretto, Thales S. Korting, Pedro J. Leitao, Ieda D.A. Sanches, Patrick Hostert

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

Mapping agriculture with high accuracy is important to generate reliable information about crop production. Pixel-based methods still present problems with noise and usually require post-processing approaches to reach satisfactory results. Object-based Image Analysis (OBIA) enable the detection of homogeneous objects in remote sensing images based on spectral similarity. However, traditional OBIA does not consider the multi-temporal characteristics of land cover or land use, such as agriculture. The objective of this study is to evaluate a phenological object-based approach with dense Landsat image time series for mapping agriculture in different level of detail in the Brazilian Cerrado. We derived pixel-wise EVI fitted time series with 8-day temporal resolution and applied multi-resolution segmentation using all image bands to incorporate the influence of space and time. Then we generated phenological metrics and applied OBIA of agricultural lands in Brazil using a hierarchical classification scheme. The overall accuracies for each hierarchical level were around 90%, and the spatial consistency of the generated maps is promising.

Original languageEnglish
Title of host publication2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings
PublisherIEEE
Pages1078-1081
Number of pages4
ISBN (Electronic)9781728163741
DOIs
Publication statusPublished - 26 Sept 2020
Externally publishedYes
Event2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Virtual, Waikoloa, United States
Duration: 26 Sept 20202 Oct 2020

Conference

Conference2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020
Abbreviated titleIGARSS 2020
Country/TerritoryUnited States
CityVirtual, Waikoloa
Period26/09/202/10/20

Keywords

  • Big data
  • OBIA
  • Phenometrics
  • Time-series mining
  • ITC-CV
  • n/a OA procedure

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