elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Impressum | Datenschutz | Kontakt | English
Schriftgröße: [-] Text [+]

Spatial and Semantic Effects of LUCAS Samples on Fully Automated Land Use/Land Cover Classification in High-resolution Sentinel-2 Data

Weigand, Matthias und Staab, Jeroen und Wurm, Michael und Taubenböck, Hannes (2020) Spatial and Semantic Effects of LUCAS Samples on Fully Automated Land Use/Land Cover Classification in High-resolution Sentinel-2 Data. International Journal of Applied Earth Observation and Geoinformation, 80, Seiten 1-9. Elsevier. doi: 10.1016/j.jag.2020.102065. ISSN 0303-2434.

[img] PDF - Verlagsversion (veröffentlichte Fassung)
2MB

Kurzfassung

In this study, we test the use of Land Use and Coverage Area frame Survey (LUCAS) in-situ reference data for classifying high-resolution Sentinel-2 imagery at a large scale. We compare several pre-processing schemes (PS) for LUCAS data and propose a new PS for a fully automated classification of satellite imagery on the national level. The image data utilizes a high-dimensional Sentinel-2-based image feature space. Key elements of LUCAS data pre-processing include two positioning approaches and three semantic selection approaches. The latter approaches differ in the applied quality measures for identifying valid reference points and by the number of LU/LC classes (7-12). In an iterative training process, the impact of the chosen PS on a Random Forest image classifier is evaluated. The results are compared to LUCAS reference points that are not pre-processed, which act as a benchmark, and the classification quality is evaluated by independent sets of validation points. The classification results show that the positional correction of LUCAS points has an especially positive effect on the overall classification accuracy. On average, this improves the accuracy by 3.7%. This improvement is lowest for the most rigid sample selection approach, PS 2 , and highest for the benchmark data set, PS 0 . The highest overall accuracy is 93.1% which is achieved by using the newly developed PS 3 ; all PS achieve overall accuracies of 80% and higher on average. While the difference in overall accuracy between the PS is likely to be influenced by the respective number of LU/LC classes, we conclude that, overall, LUCAS in-situ data is a suitable source for reference information for large scale high resolution LC mapping using Sentinel-2 imagery. Existing sample selection approaches developed for Landsat imagery can be transferred to Sentinel-2 imagery, achieving comparable semantic accuracies while increasing the spatial resolution. The resulting LC classification product that uses the newly developed PS is available for Germany via DOI: https://doi.org/10.15489/1ccmlap3mn39.

elib-URL des Eintrags:https://elib.dlr.de/134059/
Dokumentart:Zeitschriftenbeitrag
Titel:Spatial and Semantic Effects of LUCAS Samples on Fully Automated Land Use/Land Cover Classification in High-resolution Sentinel-2 Data
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Weigand, Matthiasmatthias.weigand (at) dlr.dehttps://orcid.org/0000-0002-5553-4152NICHT SPEZIFIZIERT
Staab, JeroenJeroen.Staab (at) dlr.dehttps://orcid.org/0000-0002-7342-4440NICHT SPEZIFIZIERT
Wurm, Michaelmichael.wurm (at) dlr.dehttps://orcid.org/0000-0001-5967-1894NICHT SPEZIFIZIERT
Taubenböck, Hanneshannes.taubenboeck (at) dlr.dehttps://orcid.org/0000-0003-4360-9126NICHT SPEZIFIZIERT
Datum:Juni 2020
Erschienen in:International Journal of Applied Earth Observation and Geoinformation
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:80
DOI:10.1016/j.jag.2020.102065
Seitenbereich:Seiten 1-9
Verlag:Elsevier
ISSN:0303-2434
Status:veröffentlicht
Stichwörter:Land cover classification In-situ reference data LUCAS Sentinel-2 Remote sensing
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - Fernerkundung u. Geoforschung
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum > Georisiken und zivile Sicherheit
Hinterlegt von: Weigand, Matthias
Hinterlegt am:16 Mär 2020 09:33
Letzte Änderung:23 Okt 2023 13:56

Nur für Mitarbeiter des Archivs: Kontrollseite des Eintrags

Blättern
Suchen
Hilfe & Kontakt
Informationen
electronic library verwendet EPrints 3.3.12
Gestaltung Webseite und Datenbank: Copyright © Deutsches Zentrum für Luft- und Raumfahrt (DLR). Alle Rechte vorbehalten.