Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 185-188, 2015
https://doi.org/10.5194/isprsarchives-XL-1-W5-185-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
11 Dec 2015
SEMANTIC INDEXING OF TERRASAR-X AND IN SITU DATA FOR URBAN ANALYTICS
D. Espinoza Molina, K. Alonso, and M. Datcu German Aerospace Center (DLR), Earth Observation Center, Remote Sensing Institute, Oberpfaffenhofen, 82234 Weßling, Germany
Keywords: Earth-Observation images, data mining, semantic definition, land use land cover, analytics Abstract. This paper presents the semantic indexing of TerraSAR-X images and in situ data. Image processing together with machine learning methods, relevance feedback techniques, and human expertise are used to annotate the image content into a land use land cover catalogue. All the generated information is stored into a geo-database supporting the link between different types of information and the computation of queries and analytics. We used 11 TerraSAR-X scenes over Germany and LUCAS as in situ data. The semantic index is composed of about 73 land use land cover categories found in TerraSAR-X test dataset and 84 categories found in LUCAS dataset.
Conference paper (PDF, 1080 KB)


Citation: Espinoza Molina, D., Alonso, K., and Datcu, M.: SEMANTIC INDEXING OF TERRASAR-X AND IN SITU DATA FOR URBAN ANALYTICS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 185-188, https://doi.org/10.5194/isprsarchives-XL-1-W5-185-2015, 2015.

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