Towards development of a national human settlement layer using high resolution imagery: a contribution to SDG reporting

Abstract

This study investigated the automation of the building extraction using SPOT 6 satellite imagery. The proposed methodology uses variance textural information derived from 1.5m panchromatic image to detect built-up areas from non-built-up areas. Once detected, detailed segmentation is performed on built-up class to create individual building objects. Canny edges, SAVI and spectral properties of the objects were used to classify building structures from other land use features using a thresholding technique. The methodology was tested in different areas including formal, rural village and informal and new development settlement types without modifying segmentation and classification parameters. The proposed methodology successfully detected built-up from non built-up areas in all different settlement types. The detection of individual structures achieved more than 70% in formal, rural village and new development areas while less than 50% of building structures in informal settlement were detected. The proposed method can contribute towards monitoring of human settlement developments over a larger area which is vital during spatial planning, service delivery and environmental management. This work will contribute towards the development of a National Human Settlement Layer developed and maintained by SANSA.