Extracting Urban Morphology for Atmospheric Modeling from Multispectral and SAR Satellite Imagery

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dc.contributor University of Helsinki, Institute for Atmospheric and Earth System Research (INAR) en
dc.contributor.author Wittke, Samantha
dc.contributor.author Karila, Kirsi
dc.contributor.author Puttonen, Eetu
dc.contributor.author Hellsten, Antti
dc.contributor.author Auvinen, Mikko Jussi Santeri
dc.contributor.author Karjalainen, Mika
dc.contributor.editor Heipke, C.
dc.contributor.editor Jacobsen, K.
dc.contributor.editor Stilla, U.
dc.contributor.editor Rottensteiner, F.
dc.contributor.editor Yilmaz, A.
dc.contributor.editor Ying Yang, M.
dc.contributor.editor Skaloud, J.
dc.contributor.editor Colomina, I.
dc.date.accessioned 2018-02-05T15:09:01Z
dc.date.available 2018-02-05T15:09:01Z
dc.date.issued 2017-05-31
dc.identifier.citation Wittke , S , Karila , K , Puttonen , E , Hellsten , A , Auvinen , M J S & Karjalainen , M 2017 , Extracting Urban Morphology for Atmospheric Modeling from Multispectral and SAR Satellite Imagery . in C Heipke , K Jacobsen , U Stilla , F Rottensteiner , A Yilmaz , M Ying Yang , J Skaloud & I Colomina (eds) , ISPRS Hannover Workshop: HRIGI 17 – CMRT 17 – ISA 17 – EuroCOW 17 : 6–9 June 2017, Hannover, Germany . The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences , vol. XLII-1/W1 , ISPRS , pp. 425-431 , ISPR Hannover Workshop , Hannover , Germany , 06/06/2017 . https://doi.org/10.5194/isprs-archives-XLII-1-W1-425-2017 en
dc.identifier.citation conference en
dc.identifier.other PURE: 96544357
dc.identifier.other PURE UUID: 590e9e7c-f7f3-484e-b29f-d4064baf26f0
dc.identifier.other Scopus: 85021074398
dc.identifier.other WOS: 000430221300063
dc.identifier.other ORCID: /0000-0002-6927-825X/work/41401994
dc.identifier.uri http://hdl.handle.net/10138/232068
dc.description.abstract This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1) Digital Elevation Model (DEM) and 2) land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP). en
dc.format.extent 7
dc.language.iso eng
dc.publisher ISPRS
dc.relation.ispartof ISPRS Hannover Workshop: HRIGI 17 – CMRT 17 – ISA 17 – EuroCOW 17 6–9 June 2017, Hannover, Germany
dc.relation.ispartofseries The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
dc.rights en
dc.subject 1171 Geosciences en
dc.title Extracting Urban Morphology for Atmospheric Modeling from Multispectral and SAR Satellite Imagery en
dc.type Conference contribution
dc.identifier.doi https://doi.org/10.5194/isprs-archives-XLII-1-W1-425-2017
dc.type.uri info:eu-repo/semantics/other
dc.contributor.pbl
dc.contributor.pbl
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