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Mining Multitemporal In Situ Heterogeneous Monitoring Information for the Assurance of Recorded Land Cover Changes

Alonso, Kevin and Espinoza Molina, Daniela and Datcu, Mihai (2017) Mining Multitemporal In Situ Heterogeneous Monitoring Information for the Assurance of Recorded Land Cover Changes. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10 (3), pp. 877-887. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/JSTARS.2016.2599225 ISSN 1939-1404

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Official URL: http://ieeexplore.ieee.org/document/7563869/

Abstract

We present a data mining methodology to filter and validate land cover change detections obtained from multitemporal in situ surveys. As in situ data we use the measurements from the European land use and coverage area frame survey (LUCAS), which provides images with standardized metadata about land cover and land use within the whole territory of the European Union. Multitemporal LUCAS surveys present an anomaly in the amount of land cover changes that disagree with the estimated by experts. Therefore, our methodology analyses the available data in order to explain the existing irregularities in them. The initial step of our methodology is based on database query refinements. The data mining methodology continues with an image analysis process. This analysis calculates similarity measures of the multitemporal images that are used to identify the potential misclassifications. The final step involves a geographic information system based on web technologies. By defining different color codes assigned by the similarity measures, the system represents the examined points on a digital Earth globe. There, a user can easily discriminate potentially misclassified points for subsequent detailed analysis or corrections. The final output of the methodology shows remarkable results for detecting misclassified land cover changes.

Item URL in elib:https://elib.dlr.de/108086/
Document Type:Article
Title:Mining Multitemporal In Situ Heterogeneous Monitoring Information for the Assurance of Recorded Land Cover Changes
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Alonso, KevinKevin.AlonsoGonzalez (at) dlr.dehttps://orcid.org/0000-0003-2469-8290
Espinoza Molina, DanielaDaniela.EspinozaMolina (at) dlr.deUNSPECIFIED
Datcu, MihaiMihai.Datcu (at) dlr.deUNSPECIFIED
Date:March 2017
Journal or Publication Title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:10
DOI :10.1109/JSTARS.2016.2599225
Page Range:pp. 877-887
Editors:
EditorsEmail
Du, Qian (Jenny)Du@ece.msstate.edu
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1939-1404
Status:Published
Keywords:Big Data, data integration, data mining, geographic information system (GIS), in situ data, land use and coverage area frame survey (LUCAS), multitemporal change detection.
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: Alonso, Kevin
Deposited On:18 Nov 2016 15:08
Last Modified:31 Jul 2019 20:05

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