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Zooming into Uncertainties: Towards Fusing Multi Zoom Level Imagery for Urban Land Use Segmentation

Hoffmann, Eike Jens and Ali, Syed Mohsin and Zhu, Xiao Xiang (2021) Zooming into Uncertainties: Towards Fusing Multi Zoom Level Imagery for Urban Land Use Segmentation. In: International Geoscience and Remote Sensing Symposium (IGARSS), pp. 1-4. IGARSS 2021, Brussels, Belgium.

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Urban land use prediction is an ill-posed problem from a remote sensing perspective. Some areas are easy to predict with aerial images, e.g. residential areas or industrial areas, whereas it is nearly impossible to predict land use in dense urban centers with highly mixed land use. In this study, we use a fully convolutional, Bayesian neural network for urban land use segmentation that yields predictions and pixel-wise uncertainty values side-by-side. By adding aleatoric uncertainty to the output of our model, we can assess how much the model benefits from the provided data. We train our network using a dataset from four metropolitan areas in the U.S. on two different zoom levels. Our results show that adding aleatoric uncertainty can improve the IoU scores if a sufficient amount of informative data is provided.

Item URL in elib:https://elib.dlr.de/144212/
Document Type:Conference or Workshop Item (Speech)
Title:Zooming into Uncertainties: Towards Fusing Multi Zoom Level Imagery for Urban Land Use Segmentation
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Hoffmann, Eike JensTU Münchenhttps://orcid.org/0000-0001-7702-0403
Ali, Syed MohsinSyed.Ali (at) dlr.deUNSPECIFIED
Zhu, Xiao Xiangxiao.zhu (at) dlr.deUNSPECIFIED
Journal or Publication Title:International Geoscience and Remote Sensing Symposium (IGARSS)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 1-4
Keywords:Urban Land Use, Semantic Segmentation Model, Uncertainty, Multi-Zoom Level
Event Title:IGARSS 2021
Event Location:Brussels, Belgium
Event Type:international Conference
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Remote Sensing and Geo Research, R - Artificial Intelligence
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Hoffmann, Eike Jens
Deposited On:30 Sep 2021 12:27
Last Modified:01 Dec 2021 11:29

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