Potential application of remote sensing in monitoring informal settlements in South Africa where complimentary data does not exist

Karishma Busgeeth; Frans van den Bergh; Jarrell Whisken; André Brits

doi:10.1117/12.813211

7 November 2008 Potential application of remote sensing in monitoring informal settlements in South Africa where complimentary data does not exist

Karishma Busgeeth, Frans van den Bergh, Jarrell Whisken, André Brits

Author Affiliations +

Proceedings Volume 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images; 71470B (2008) https://doi.org/10.1117/12.813211
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

Abstract

Remotely sensed images are used for many purposes in today's world. In this paper, we explore the potential application of high resolution satellite images in extracting features and classifying urban settlements. The test area is Soweto, an urban area in the Greater Johannesburg Metropolitan area, in Gauteng, South Africa. We propose a new settlement typology for efficient classification of formal and informal settlements via QuickBird satellite images. Following on, an automated classification procedure based on the local binary pattern texture features is introduced. Using a convenience sample of 25 images, we show the feasibility of the new typology by applying it to both a manual classification procedure and an automated one. The manual classification procedure was conducted by a group of five experts who interpreted the images and classified them according to formal and informal settlements. Analysis of the results revealed an overall mean classification accuracy of 99.2% with a standard deviation of 1.79%. The automated method involved extracting tiles at random positions within the 25-sample dataset. The features extracted from these tiles were classified using a support vector machine. Classification accuracy on new samples was 56.27%, but cross-validation on the training data reached classification accuracies of 98%.

Citation Download Citation

Karishma Busgeeth, Frans van den Bergh, Jarrell Whisken, and André Brits "Potential application of remote sensing in monitoring informal settlements in South Africa where complimentary data does not exist", Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470B (7 November 2008); https://doi.org/10.1117/12.813211

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available