Abstract:
Continuous land development and urbanization highlights the importance of improved surface water management to avoid flooding and delayed drainage. Thus, several cities a...Show MoreMetadata
Abstract:
Continuous land development and urbanization highlights the importance of improved surface water management to avoid flooding and delayed drainage. Thus, several cities around the world have used variations of the blue-green factor (BGF), a policy instrument to attain desired levels of vegetation and water surfaces in new property developments. However, estimating BGF for existing infrastructure is equally important in order to ensure proper water management of the entire city. The presented work shows a possible workflow to estimate BGF semi-automatically from remote sensing hyperspectral and lidar data in Norway. A set of urban features and areas were detected and analyzed for individual properties affecting the BGF, along with corresponding estimation accuracies. The results demonstrate the potential to extract information and calculate BGF automatically. Lastly, it is pointed out that the models used for BGF estimation need to be further investigated and developed to enhance the estimation accuracy.
Published in: 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)
Date of Conference: 24-26 September 2019
Date Added to IEEE Xplore: 05 December 2019
ISBN Information: