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Change Detection for Application in Urban Geography based on Very High Resolution Remote Sensing

Leichtle, Tobias (2020) Change Detection for Application in Urban Geography based on Very High Resolution Remote Sensing. Dissertation, Humboldt-Universität zu Berlin.

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Official URL: http://edoc.hu-berlin.de/18452/21797


Cities are hot spots of global change. Thus, highly detailed and up-to-date information is required, which can be delineated based on various earth observation sensors. This thesis aims at the development of a change detection approach based on very high resolution (VHR) optical remote sensing data and consequent exemplary application of the assessment of the ghost city phenomenon in the context of urban geography. The unsupervised object-based change detection method captures the construction of individual buildings with accuracy of 0.8 to 0.9 according to kappa statistics in the city of Dongying, China. The methodology utilizes object-based difference features based on existing building geometries for the delimitation of changed and unchanged buildings. It is capable of handling VHR data from different sensors with deviating viewing geometries which allows the utilization of all present and future available sources of VHR data at small spatial scale. The transferability of the approach is investigated with particular focus on the nature and effects of class distribution. For this purpose, a diagnostic framework is developed and consequently applied in two cities of different characteristics. Results showed that situations of imbalanced class distribution generally provide less reliable identification of changes compared to balanced situations. The assessment of the ghost city phenomenon is conducted as an exemplary application of urban geography in the city of Dongying, China. The conceptual framework replicates undercapacity with respect to the residential population as one of the key characteristics of a ghost city. A 4d functional city model is established based on VHR imagery for population capacity estimation of residential buildings and subsequently related to actual permanent residential population from census counts. A significant mismatch and thus, high likelihood for the emergence and presence of the ghost city phenomenon was found in Dongying.

Item URL in elib:https://elib.dlr.de/133819/
Document Type:Thesis (Dissertation)
Title:Change Detection for Application in Urban Geography based on Very High Resolution Remote Sensing
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Leichtle, Tobiastobias.leichtle (at) dlr.deUNSPECIFIED
Date:January 2020
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Number of Pages:151
Keywords:remote sensing, urbanization, change detection, urban geography, ghost city, China
Institution:Humboldt-Universität zu Berlin
Department:Geographisches Institut
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
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Deposited By: Leichtle, Tobias
Deposited On:23 Jan 2020 12:44
Last Modified:23 Jan 2020 12:44

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