TY - JOUR
T1 - Monitoring and analysing the Emirate of Dubai’s land use/land cover changes
T2 - an integrated, low-cost remote sensing approach
AU - Elmahdy, Samy Ismail
AU - Mohamed, Mohamed Mostafa
N1 - Publisher Copyright:
© 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2018/11/2
Y1 - 2018/11/2
N2 - 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 km2 (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 km2, respectively. This study is aimed to assist urban planners and decision-makers, as well as research institutes.
AB - 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 km2 (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 km2, respectively. This study is aimed to assist urban planners and decision-makers, as well as research institutes.
KW - Dubai
KW - SAM algorithm
KW - change detection
KW - image difference
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U2 - 10.1080/17538947.2017.1379563
DO - 10.1080/17538947.2017.1379563
M3 - Article
AN - SCOPUS:85030533949
SN - 1753-8947
VL - 11
SP - 1132
EP - 1150
JO - International Journal of Digital Earth
JF - International Journal of Digital Earth
IS - 11
ER -