Abschlussarbeiten
Computational Delineation of Built-up Area at Urban block Level from Topographic Maps – A Contribution to Retrospective Monitoring of Urban Dynamics
Art der Abschlussarbeit
Dissertation
Autoren
- Muhs, Sebastian
Betreuer
- Prof. Dr.-Ing.habil. Dipl.-Phys. Dirk Burghardt
Weitere Betreuer
Dr. Gotthard Meinel; Leibniz-Institut für ökologische Raumentwicklung, Dresden; Prof. Dr. Nguyen Xuan Thinh, TU Dortmund
Abstract
Among many others, one general goal of the UN sustainability strategies aims at reducing the anthropogenic land change due to land take for settlements and transport infrastructure. To monitor the success of this goal and to comprehensively study and better understand these urban dynamic processes – such as densification, growth and sprawl, or shrinkage –, quantitative measurements were introduced to assist the assessment. For the analysis of urban dynamics, the built-up area is an important measure that can be considered at different scales, one common scale being the aggregated level of urban blocks that represent a group of developed parcels bounded by topographic borders such as street lines. Regardless of the scale of quantitative analysis, however, digital spatio-temporal data are essential. While comprehensive databases exist for contemporary data, they usually lack a historic dimension. To derive these historic data about the built-up area, potential surveying methods and sources may vary. Considering the long-term characteristic of urban land change, however, topographic maps often are the only source for small-scale, spatially explicit land cover information to build a comprehensive, spatio-temporal database of built-up area, which has been demonstrated by numerous studies. However, the manual constitution of historic geographic data based on historic maps – commonly referred to as map digitization or vectorization – is a time consuming and laborious process that limits the spatial and temporal scope and, therefore, opposes comprehensive studies. Therefore, this thesis proposes an approach to automatically extract information about the built-up area at urban block level from historic topographic maps. For a number of reasons, this is a challenging task. First, topographic maps show a high degree of informational density and complexity due to their layer concept. These layers of geographic objects generally overlap leading to the (multi-)fragmentation or fusion of distinct geographic map objects. While this may not pose a challenge to a human interpreter, it does for the formalization of the computational object recognition. Second, material aging of the document as well as a poor scanning or image compression process may result in a reduced graphical quality. Third, object representations including the use of color, if present at all, show an immense diversity over space and time. To overcome these challenges in regard to cartographical image analysis, a modular process has been designed pursuing a two-step strategy: a decomposition of salient map layers is succeeded by a re-composition of the structuring map objects to delineate the built-up area at urban block level. Several experiments prove this process to achieve acceptable results with correctness values ranging from 0.97 to 0.93 for three German study maps. Behind the background of a global trend to digitize knowledge that can also be observed with historic topographic maps, the designed process represents a promising approach to efficiently prepare these historic data for integration into a spatio-temporal database of built-up area with minimal user intervention.
Schlagwörter
Topographic Maps, Image Analysis, Built-up Area, computational
Berichtsjahr
2018