Monitoring and analysing the Emirate of Dubai's land use/land cover changes: an integrated, low-cost remote sensing approach

• Published in: International journal of digital earth Vol. 11; no. 11; pp. 1132 - 1150
• Main Authors: Elmahdy, Samy Ismail, Mohamed, Mohamed Mostafa
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 02.11.2018; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Accuracy; algorithms; change detection; Classification; decision making; Dubai; Image classification; image difference; Image enhancement; Land cover; Land use; Low cost; Monitoring; Remote sensing; Research facilities; research institutions; SAM algorithm; sieving; Spatial discrimination; Spatial resolution; Training; United Arab Emirates; Urban planning; vegetation; Dubai United Arab Emirates; United Arab Emirates
• ISSN: 1753-8947; 1753-8955; 1753-8955
• DOI: 10.1080/17538947.2017.1379563

This study presents a modified low-cost approach, which integrates the spectral angle mapper and image difference algorithms in order to enhance classification maps for the purpose of monitoring and analysing land use/land cover change between 2000 and 2015 for the Emirate of Dubai. The approach was modified by collecting 320 training samples from QuickBird images with a spatial resolution of 0.6 m, as well as carrying out field observations, followed by the application of a 3 × 3 Soble filter, sieving classes, majority/minority analysis, and clump classes of the obtained classification maps. The accuracy assessment showed that the targeted 2000, 2005, 2010 and 2015 classification maps have 88.1252%, 89.0699%, 90.1225% and 96.0965% accuracy, respectively. The results showed that the built-up area increased by 233.721 km 2 (5.81%) between 2000 and 2005 and continues to increase even up and till the present time. The assessment of changes in the periods 2000-2005 and 2010-2015 confirmed that net vegetation area losses were more pronounced from 2000 to 2005 than from 2010 to 2015, dropping from 47,618 to 40,820 km 2 , respectively. This study is aimed to assist urban planners and decision-makers, as well as research institutes.