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DOI: 10.5445/IR/1000087844
Veröffentlicht am 26.11.2018
DOI: 10.5194/isprs-archives-XLII-1-217-2018

Classification and representation of commonly used roofing material using multisensorial aerial data

Ilehag, R.; Bulatov, D.; Helmholz, P.; Belton, D.

As more cities are starting to experience the urban heat islands effect, knowledge about the energy emitted from building roofs is of primary importance. Since this energy depends both on roof orientations and materials, we tackled both issues by analysing sensor data from multispectral, thermal infrared, high-resolution RGB, and airborne laser datasets (each with different spatial resolutions) of a council in Perth, Australia. To localise the roofs, we acquired building outlines that had to be updated using the normalised digital surface model, the NDVI and the planarity. Then, we computed a semantic 3D model of the study area, with roof detail analysis being a particular focus. The main objective of this study, however, was to classify three commonly used roofing materials: Cement tiles, Colorbond and Zincalume by combining the multispectral and thermal infrared image bands while the high-resolution RGB dataset was used to provide additional information about the roof texture. Three types of image segmentation approaches were evaluated to assess any differences while performing the material classification; pixel-wise, superpixel-w ... mehr

Zugehörige Institution(en) am KIT Institut für Photogrammetrie und Fernerkundung (IPF)
Publikationstyp Zeitschriftenaufsatz
Jahr 2018
Sprache Englisch
Identifikator ISSN: 1682-1750
URN: urn:nbn:de:swb:90-878442
KITopen ID: 1000087844
Erschienen in The international archives of photogrammetry, remote sensing and spatial information sciences
Band 42
Heft 1
Seiten 217-224
Bemerkung zur Veröffentlichung 2018 ISPRS Technical Commission I Midterm Symposium on Innovative Sensing - From Sensors to Methods and Applications; Karlsruhe; Germany; 10 October 2018 through 12 October 2018. Ed.: M. Weinmann
Schlagworte Multispectral, Thermal, High-resolution RGB, LiDAR, Building outlines, Classification, Image segmentation
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