Annual Crop Classification Experiments in Portugal Using Sentinel-2

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

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

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Abstract

This paper presents an experimental crop classification of the 10 most abundant annual crop types in Portugal, using a study area located in Alentejo region. This region has great diversity of land uses as well as multiple crop types. Sentinel-2 2018 intra-annual time-series imagery is considered in the experiment. The Portuguese Land Parcel Identification System (LPIS) is used to extract automatic training samples. LPIS information is automatically processed with the help of auxiliary datasets to filter out crop areas more likely to have been mislabeled. Classification is obtained using random forest. Validation is performed using an independent dataset also based on LPIS. A global accuracy of 76% is obtained. The novelty of the methodology here presented shows that LPIS can be used together with auxiliary data for crop type mapping, helping to characterize the agriculture land diversity in Portugal.
Original languageEnglish
Title of host publicationIGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium
Subtitle of host publicationProceedings
PublisherIEEE
Pages5838-5841
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
Country/TerritoryBelgium
CityBrussels
Period11/07/2116/07/21

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