Automatic Open Space Area Extraction and Change Detection from High Resolution Urban Satellite Images

TL;DR

This paper presents an automatic method for extracting open space areas from high-resolution urban satellite images and detecting changes over time, aiding urban planning and geospatial data management.

Contribution

The paper introduces a novel automatic extraction and change detection algorithm using filters, segmentation, and grouping for high-resolution urban satellite imagery.

Findings

Effective extraction of open space areas from satellite images

Detection of changes in open space over multiple years

Potential applications in urban planning and geospatial analysis

Abstract

In this paper, we study efficient and reliable automatic extraction algorithm to find out the open space area from the high resolution urban satellite imagery, and to detect changes from the extracted open space area during the period 2003, 2006 and 2008. This automatic extraction and change detection algorithm uses some filters, segmentation and grouping that are applied on satellite images. The resultant images may be used to calculate the total available open space area and the built up area. It may also be used to compare the difference between present and past open space area using historical urban satellite images of that same projection, which is an important geo spatial data management application.