Land cover mapping at national scale with Sentinel-2 and LUCAS: a case study in Portugal

Pedro José Benevides, Nuno Silva, Hugo Costa, Francisco D. Moreira, Daniel Moraes, Mauro Castelli, Mário Caetano

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Abstract

Experiments were carried out to investigate the use of Land Use and Coverage Area frame Survey (LUCAS) dataset and Sentinel-2 imagery to produce a land cover map in Portugal through automated supervised classification. LUCAS is a free land cover land use (LCLU) dataset based in Europe, while Sentinel-2 satellites provide also free images with short revisit frequency. The goal was to evaluate if LUCAS dataset from 2018 can be used as a single reference dataset for land cover classification at national level. The Random Forest (RF) algorithm was used. Some processing steps were undertaken to use LUCAS as reference dataset. The original LUCAS LCLU nomenclature was modified into a new nomenclature composed of 12 and 6 level-2 and level-1 map classes, respectively. Filtering was performed on LUCAS metadata, reducing the initial number of LUCAS points over Portugal from 7168 to 4910. Monthly composites of Sentinel-2 images acquired between October 2017 and September 2018 were used. To reduce the imbalance in LUCAS training points, an oversampling technique based on Synthetic Minority Over-Sampling Technique (SMOTE) was used. An independent validation dataset was produced with 600 points. RF shows an overall accuracy (OA) of 57% for level-2 and 72% for level-1 nomenclatures. When using the oversampling technique, the OA accuracy increases by 3% for level2 and 2% for level-1. The preliminary results of this experiment show that LUCAS dataset used in supervised machine learning classification has potential to produce a reliable land cover map at national scale.
Original languageEnglish
Title of host publicationRemote Sensing for Agriculture, Ecosystems, and Hydrology XXIII
EditorsChristopher M. U. Neale, Antonino Maltese
PublisherSPIE-International Society for Optical Engineering
Number of pages10
Volume11856
ISBN (Electronic)9781510645578
ISBN (Print)9781510645561
DOIs
Publication statusPublished - 12 Sep 2021
EventRemote Sensing for Agriculture, Ecosystems, and Hydrology XXIII - Online Only, Spain
Duration: 13 Sep 202118 Sep 2021

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
PublisherSPIE
Volume11856
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceRemote Sensing for Agriculture, Ecosystems, and Hydrology XXIII
Period13/09/2118/09/21

Keywords

  • Land Cover
  • LUCAS survey
  • National mapping
  • Oversampling
  • Random Forest
  • Sentinel-2

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