Automatic Extraction of Open Space Area from High Resolution Urban Satellite Imagery

TL;DR

This paper presents an automatic method for extracting open space areas from high-resolution urban satellite images using filters, segmentation, and grouping, enabling efficient urban space analysis and historical comparison.

Contribution

It introduces a novel automatic extraction algorithm combining filtering, segmentation, and grouping for urban satellite imagery analysis.

Findings

Effective extraction of open space areas demonstrated.

Algorithm enables comparison of urban open spaces over time.

Potential for integration into GIS systems for urban planning.

Abstract

In the 21st century, Aerial and satellite images are information rich. They are also complex to analyze. For GIS systems, many features require fast and reliable extraction of open space area from high resolution satellite imagery. In this paper we will study efficient and reliable automatic extraction algorithm to find out the open space area from the high resolution urban satellite imagery. This automatic extraction algorithm uses some filters and segmentations and grouping is applying on satellite images. And the result images may use to calculate the total available open space area and the built up area. It may also use to compare the difference between present and past open space area using historical urban satellite images of that same projection