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Fusion of Airborne Hyperspectral and LiDAR Remote Sensing Data to Study the Thermal Characteristics of Urban Environments

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Computational Approaches for Urban Environments

Part of the book series: Geotechnologies and the Environment ((GEOTECH,volume 13))

Abstract

This study focuses on the derivation of an urban surface material map to parameterize a 3D numerical microclimate model. For this purpose, fusion of airborne hyperspectral and light detection and ranging (LiDAR) remote sensing data is performed. In a first step, surface materials are extracted from the preprocessed input datasets using a hybrid, three-stage classification approach. The resulting map is then utilized in combination with the LiDAR object height information data to parameterize the microclimate model. To demonstrate the potential of data-driven microclimate modeling, two case studies are presented for selected test sites in the City of Houston, Texas. The results of this study highlight that the synergistic combination of hyperspectral and LiDAR data enables reliable mapping of some of the key input parameters required for urban microclimate modeling. Moreover, classification-based microclimate simulations can reveal the thermal properties of urban neighborhoods under varying conditions and, thus, facilitate the identification of hot spot areas and critical land cover configurations.

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Acknowledgements

The authors would like to thank the Hyperspectral Image Analysis group and the NSF Funded Center for Airborne Laser Mapping (NCALM) at the University of Houston for providing the “grss_dfc_2013” data set used in this study and the IEEE GRSS Image Analysis and Data Fusion Technical Committee for organizing the 2013 Data Fusion Contest. The authors also wish to thank the three anonymous reviewers whose comments helped to substantially improve an earlier version of this chapter.

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Authors and Affiliations

  1. Department of Earth Observation, University of Jena, Löbdergraben 32, D-07743, Jena, Germany

    Christian Berger, Frank Riedel, Johannes Rosentreter, Enrico Stein & Sören Hese

  2. Earth Observation Center, German Aerospace Center (DLR), Oberpfaffenhofen, D-82234, Wessling, Germany

    Christiane Schmullius

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  1. Christian Berger
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Correspondence to Christian Berger .

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Editors and Affiliations

  1. Department of Human Geography and Spatial Planning, Utrecht University, Utrecht, The Netherlands

    Marco Helbich

  2. Institute of Geography, Heidelberg University, Heidelberg, Germany

    Jamal Jokar Arsanjani

  3. Dept. of Geography and Anthropology, Louisiana State University, Baton Rouge, Louisiana, USA

    Michael Leitner

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Berger, C., Riedel, F., Rosentreter, J., Stein, E., Hese, S., Schmullius, C. (2015). Fusion of Airborne Hyperspectral and LiDAR Remote Sensing Data to Study the Thermal Characteristics of Urban Environments. In: Helbich, M., Jokar Arsanjani, J., Leitner, M. (eds) Computational Approaches for Urban Environments. Geotechnologies and the Environment, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-319-11469-9_11

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