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

Nathalie Aussenac-Gilles¹  Catherine Comparot¹  Ba-Huy Tran¹  Cassia Trojahn¹ 

[1] IRIT, Université de Toulouse, CNRS, CEDEX 9, 31062 Toulouse, France;

关键词: Earth Observation;    semantic integration;    land cover;    RDF;   

DOI  :  10.3390/ijgi9090503

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown