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Land Cover Change Detection in Satellite Image Time Series Using an Active Learning Method

Grivei, Alexandru and Radoi, Anamaria and Datcu, Mihai (2017) Land Cover Change Detection in Satellite Image Time Series Using an Active Learning Method. In: Analysis of Multitemporal Remote Sensing Images (MultiTemp), pp. 1-4. 9th International Workshop (Multitemp), 27.-29. Juni 2017, Brügge, Belgien. DOI: 10.1109/Multi-Temp.2017.8035213

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Official URL: http://ieeexplore.ieee.org/document/8035213/


Some of the first Earth Observation (EO) missions date back to the 1970s. Over the time, large datasets of Satellite Image Time Series (SITS) have been used to identify and monitorland cover evolutions. The processing complexity increases proportionally to the time span of the Earth Observation (EO) series. Because of the SITS dataset complexity and variety of contained evolution patterns, most unsupervised classification methods fail to detect and isolate the user’s evolution pattern of interest. This is usually caused by the discrepancy between automatically extracted low-level features and high-level meaning assigned by the user who searches for a specific evolution. In an effort to find a solution for this difficult task, this paper presents a SVM based active learning method for the extraction of specific evolution classes from SITS. Several experiments were conducted on a dataset composed of Landsat 4 TM (Thematic Mapper) and Landsat 5 TM acquisitions over Bucharest, Romania, in the time interval of 1984-1993.

Item URL in elib:https://elib.dlr.de/118558/
Document Type:Conference or Workshop Item (Speech)
Title:Land Cover Change Detection in Satellite Image Time Series Using an Active Learning Method
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Grivei, AlexandruUniversity Politehnica of Bucharest, RomaniaUNSPECIFIED
Radoi, AnamariaUniversity Politehnica of Bucharest, RomaniaUNSPECIFIED
Datcu, Mihaimihai.datcu (at) dlr.deUNSPECIFIED
Date:June 2017
Journal or Publication Title:Analysis of Multitemporal Remote Sensing Images (MultiTemp)
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
DOI :10.1109/Multi-Temp.2017.8035213
Page Range:pp. 1-4
Keywords:Land cover change detection, Satellite Image Time Series (SITS), active learning method
Event Title:9th International Workshop (Multitemp)
Event Location:Brügge, Belgien
Event Type:international Conference
Event Dates:27.-29. Juni 2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Zielske, Mandy
Deposited On:01 Feb 2018 18:35
Last Modified:01 Feb 2018 18:35

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