Towards Understanding Urban Patterns and Structures

Abstract

ABSTRACT:Intelligent urban design is a set of principles for desirable future urban structures. Existing urban structures can be analysed using remotely sensed images. In order to foster this analysis both in speed and objectivity automation is proposed in this work. Automatic Gestalt perception is distinguished from automatic knowledge-based analysis. Both will be required. For the Gestalt side an algebraic approach is utilized. This Gestalt algebra operates on a 6-D domain containing position, orientation, frequency, scale and assessment. It defines how to form aggregates from parts. Any Gestalt can be combined with arbitrary others, but good assessments are only achieved, if the parts are mutually in Gestalt-arrangements. There are operations for mirror-symmetry, good continuation in rows and rotational-symmetry. In this paper experiments are made only with mirror-symmetry and row-continuation. Example images of Thimphu, Bhutan and Phoenix, Arizona are obtained by use of Google Earth. The results are to a large degree in accordance with human perceptual grouping. Some illusory groupings not in accordance with human perception, as well as examples salient to humans which are not instantiated by the system, are discussed as well.

Self-organizing maps and Gestalt organization as components of an advanced system for remotely sensed data: An example with thermal hyper-spectra

“…Application to remotely sensed imagery of urban areas using SIFT key-points as primitives was investigated in [19,20]. Fig.…”

Hierarchical Grouping Using Gestalt Assessments

“…Including SIFT 128-dimensional key-point features in order to improve the performance following [1] was demonstrated in [10]. Most of our papers using these methods concentrated on remote-sensing applications [11][12] [13]. The images used were from very diverse sources such as SAR, hyper-spectral cameras, or satellite and aerial imagery.…”

“…3.1. From the picture to the primitive Gestalten Most work on hierarchical Gestalt grouping used the well-known SIFT key-points as primitives [9][10] [11] [12]. The reason might have been, that SIFT points provide exactly the desired Gestalt domain features location, scale, orientation, and assessment, and maybe also because the standard solution of Loy & Eklundh [1] also was based on these.…”

Hierarchical Grouping — The Gestalt Assessments Method

“…Including SIFT 128-dimensional key-point features in order to improve the performance following [1] was demonstrated in [10]. Most papers using these methods concentrated on remote-sensing applications [11][12] [13]. The clustering of assessed projective entities as outlined in Sect.…”