Topology, homogeneity and scale factors for object detection: application of eCognition software for urban mapping using multispectral satellite image

TL;DR

This paper demonstrates the application of object-based image analysis using eCognition software for urban mapping of Brussels with multispectral satellite imagery, achieving effective segmentation and classification for city planning.

Contribution

It introduces a semi-automated OBIA approach with eCognition for urban land cover mapping using high-resolution satellite images, showcasing its applicability in dense urban areas.

Findings

Effective image segmentation and classification achieved

Demonstrated applicability for urban planning and growth analysis

Suitable for densely populated megacities

Abstract

The research scope of this paper is to apply spatial object based image analysis (OBIA) method for processing panchromatic multispectral image covering study area of Brussels for urban mapping. The aim is to map different land cover types and more specifically, built-up areas from the very high resolution (VHR) satellite image using OBIA approach. A case study covers urban landscapes in the eastern areas of the city of Brussels, Belgium. Technically, this research was performed in eCognition raster processing software demonstrating excellent results of image segmentation and classification. The tools embedded in eCognition enabled to perform image segmentation and objects classification processes in a semi-automated regime, which is useful for the city planning, spatial analysis and urban growth analysis. The combination of the OBIA method together with technical tools of the eCognition demonstrated applicability of this method for urban mapping in densely populated areas, e.g. in megapolis and capital cities. The methodology included multiresolution segmentation and classification of the created objects.