الرئيسية / الفعاليات العلمية / اكتشاف التغيير والنمذجة والمحاكاة لغطاء الارض واستخدام الارض باستخدام صور الأقمار الصناعية متعددة الأطياف للتنمية المستدامة في مدينة النجف ، العراق

اكتشاف التغيير والنمذجة والمحاكاة لغطاء الارض واستخدام الارض باستخدام صور الأقمار الصناعية متعددة الأطياف للتنمية المستدامة في مدينة النجف ، العراق

Kawther Hussein Mohammed1

, Ahmed Asal Kzar
Physics Department, Faculty of Science, Kufa University, Najaf, Iraq.

Received Date: 29 June 2021
Revised Date: 03 August 2021
Accepted Date: 14 August 2021

Abstract – Sustainability development is the most important
and dangerous issue globally, in the present and future. In
this study, remote sensing technology represented by
multispectral Landsat images is used to find change
detection in classes of land cover and land use that are
considered part of the sustainable development goals in this
city. The adopted duration time are 2000, 2005, 2009, 2015,
and 2020 with five multispectral Landsat images. ERDAS
Imagine 2015 is the main program used in this study, where
the maximum likelihood method is used for the supervised
classification. The results are classified images with
accuracies 92.13%, 90.91%, 89.74%, 88.39%, and 85.22%,
whereas Kappa coefficient 0.8668, 0.8486, 0.8413, 0.8296,
and 0.7805 respectively. The change detection of the area for
each class during these years has been realized. The results
are an increase in the water bodies area by 6.546%,
agricultural lands by 2.8%, And urban land area by 7.719%.
In contrast, there is a decrease in the bare lands by
-17.068%. The results were followed by modeling from the
adopted period, then a simulation for all classes of LCLU for
period years (2025- 2050). The outcomes of this study gave
useful information for sustainability development through
providing a benefit to government institutions related to
urban planning, water resources, environment, and
agriculture in Al-Najaf city, Iraq. The outcomes of this study
are considered as part of achievements that related to the 17
goals of 2015 Paris agreement that should be verified in
2030.
Keywords: Sustainability development; Remote Sensing;
Multispectral; change detection; image Classification.

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