Abstract
Abstract. In this work we focused on the classification of Urban Settlement Types (USTs) based on two datasets from the TerraSAR-X satellite acquired at ascending and descending look directions. These data sets comprise the intensity, amplitude and coherence images from the ascending and descending datasets. In accordance to most official UST maps, the urban blocks of our study site were considered as the elements to be classified. The considered USTs classes in this paper are: Vegetated Areas, Single-Family Houses and Commercial and Residential Buildings. Three different groups of image attributes were utilized, namely: Relative Areas, Histogram of Oriented Gradients and geometrical and contextual attributes extracted from the nodes of a Max-Tree Morphological Profile. These image attributes were submitted to three powerful soft multi-class classification algorithms. In this way, each classifier output a membership value to each of the classes. This membership values were then treated as the potentials of the unary factors of a Conditional Random Fields (CRFs) model. The pairwise factors of the CRFs model were parameterised with a Potts function. The reclassification performed with the CRFs model enabled a slight increase of the classification’s accuracy from 76% to 79% out of 1926 urban blocks.
Highlights
1.1 Urban Structure TypesEfficient urban planning and monitoring actions heavily rely on the spatial distribution of the city’s different settlements types
This map was kindly provided to us by the prefecture of this city and it considers the urban blocks as the elementary mapping units, which enabled a one-to-one comparison between the map and the classifications
This paper shows our first efforts to classify general Urban Structure Types (USTs) classes based on simple statistical and geometrical image attributes
Summary
Efficient urban planning and monitoring actions heavily rely on the spatial distribution of the city’s different settlements types. Traffic management, water and energy consumption are just a few socio-economic and environmental planning categories that should be tailored according to the spatial distribution of the city’s different types of settlements. In Germany, the term Urban Structure Types (USTs) (Stadtstrukturtypen) was conceived in the nineties to categorize these different urban settlements. Since this concept has been used as the main spatial indicator used in urban planning and monitoring actions in this country and others. USTs are characterized by: (1) the geometry, density and spatial configuration of buildings; (2) their social, cultural and economic usages (e.g. residential, commercial, industrial, amusement etc.) and (3) their environmental properties like the presence and type of vegetation and water bodies (Pauleit and Duhme (2000) and Heiden et al (2012))
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