Fusion of Airborne Hyperspectral and LiDAR Remote Sensing Data to Study the Thermal Characteristics of Urban Environments - Computational Approaches for Urban Environments - page 279

However, further investigations are still required in order to get a more complete
picture of the data and methods under consideration. Among other issues, future
studies should comprehensively test the generalization capabilities of the developed
mapping procedure (different study areas and/or input data) and rigorously validate
the performance of data-driven microclimate modeling. In the long run, this would
effectively help promoting hyperspectral and LiDAR remote sensing technologies
for urban planning applications.
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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