Next Article in Journal
OSMWatchman: Learning How to Detect Vandalized Contributions in OSM Using a Random Forest Classifier
Previous Article in Journal
Tools for BIM-GIS Integration (IFC Georeferencing and Conversions): Results from the GeoBIM Benchmark 2019
Previous Article in Special Issue
POI Mining for Land Use Classification: A Case Study
Article

Semantic Integration of Raster Data for Earth Observation: An RDF Dataset of Territorial Unit Versions with their Land Cover

IRIT, Université de Toulouse, CNRS, 31062 Toulouse CEDEX 9, France
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(9), 503; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090503
Received: 19 June 2020 / Revised: 4 August 2020 / Accepted: 19 August 2020 / Published: 21 August 2020
(This article belongs to the Special Issue Geographic Information Extraction and Retrieval)
Semantic technologies are at the core of Earth Observation (EO) data integration, by providing an infrastructure based on RDF representation and ontologies. Because many EO data come in raster files, this paper addresses the integration of data calculated from rasters as a way of qualifying geographic units through their spatio-temporal features. We propose (i) a modular ontology that contributes to the semantic and homogeneous description of spatio-temporal data to qualify predefined areas; (ii) a Semantic Extraction, Transformation, and Load (ETL) process, allowing us to extract data from rasters and to link them to the corresponding spatio-temporal units and features; and (iii) a resulting dataset that is published as an RDF triplestore, exposed through a SPARQL endpoint, and exploited by a semantic interface. We illustrate the integration process with raster files providing the land cover of a specific French winery geographic area, its administrative units, and their land registers over different periods. The results have been evaluated with regards to three use-cases exploiting these EO data: integration of time series observations; EO process guidance; and data cross-comparison. View Full-Text
Keywords: Earth Observation; semantic integration; land cover; RDF Earth Observation; semantic integration; land cover; RDF
Show Figures

Figure 1

MDPI and ACS Style

Tran, B.-H.; Aussenac-Gilles, N.; Comparot, C.; Trojahn, C. Semantic Integration of Raster Data for Earth Observation: An RDF Dataset of Territorial Unit Versions with their Land Cover. ISPRS Int. J. Geo-Inf. 2020, 9, 503. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090503

AMA Style

Tran B-H, Aussenac-Gilles N, Comparot C, Trojahn C. Semantic Integration of Raster Data for Earth Observation: An RDF Dataset of Territorial Unit Versions with their Land Cover. ISPRS International Journal of Geo-Information. 2020; 9(9):503. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090503

Chicago/Turabian Style

Tran, Ba-Huy; Aussenac-Gilles, Nathalie; Comparot, Catherine; Trojahn, Cassia. 2020. "Semantic Integration of Raster Data for Earth Observation: An RDF Dataset of Territorial Unit Versions with their Land Cover" ISPRS Int. J. Geo-Inf. 9, no. 9: 503. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090503

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop