An object-based temporal inversion approach to urban land use change analysis. Issue 5 (3rd May 2016)

• Record Type: Journal Article
• Authors: Toure, Sory; Stow, Douglas; Shih, Hsiao-chien; Coulter, Lloyd; Weeks, John; Engstrom, Ryan; Sandborn, Avery
• Is Part Of: Remote sensing letters. Volume 7:Issue 5(2016)
• Page Start: 503
• Page End: 512
• Publication Date: 2016-05-03
• Subjects: Remote sensing -- Periodicals; Remote sensing; Periodicals; 621.3678
• DOI: 10.1080/2150704X.2016.1157640
• Languages: English
• ISSNs: 2150-704X

Abstract

ABSTRACT: Rates of population growth and urbanization currently taking place in sub-Saharan Africa are and will be the highest in the world, providing impetus for remote-sensing-based monitoring of land cover and land use change (LCLUC). The objective of this study is to assess the utility of using segmentation and classification information derived from an object-based classification of an image at a later date ( t = 2) to aid in the segmentation and classification of an image at an earlier date ( t = 1) for the same area, in the context of a post-classification comparison for LCLUC analysis within Kumasi, Ghana. This object-based temporal inversion approach was found to increase the accuracy of the t = 1 classification and land use change classifications by 6.2% and 6.6%, respectively, compared to a traditional, non-constrained object-based image analysis (OBIA) approach.