Abstract
Deriving land cover information from satellite data is one of the most common applications employed to monitor, evaluate, and manage the environment. This study aims to detect the land cover/land use changes and calculate the areas of different land cover types in Baghdad, Iraq, for the period from 2015 to 2020, using Landsat 8 images. The supervised Maximum Likelihood Classification (MLC) method was applied to classify the images. Four land cover types were obtained, namely urban, vegetation, water, and barren soil. Changes in the four land cover classes during the study period were observed. The extent of the urban, vegetation, and water areas was increased by about 7.5%, 9.5%, and 1.5%, respectively, whereas the barren soil area was decreased by about 18.5%. This study shows that the MLC classifier is a very effective method to map land cover classes.
Highlights
Over the past years, remote sensing data have been considered as a vital source to map the land use/ land cover (LULC), manage the natural resources, and monitor the environment.Iraqi Journal of Science, 2021, Vol 62, No 10, pp: 3772-3778Various satellite data sources were used in previous land cover classification studies to achieve historical trends of the changes in land cover [1]
The Maximum Likelihood Classification (MLC) classification method was applied and the land cover was classified into four classes, namely vegetation, water, urban area, and barren soil
This study showed that MLC classifier is a very effective method to map the land cover classes
Summary
Remote sensing data have been considered as a vital source to map the land use/ land cover (LULC), manage the natural resources, and monitor the environment.Iraqi Journal of Science, 2021, Vol 62, No 10, pp: 3772-3778Various satellite data sources were used in previous land cover classification studies to achieve historical trends of the changes in land cover [1]. Supervised classification learning algorithms are used, for example, to classify pixels based on their spectral properties (reflectance values or Digital Number) with the selection of training data for each class, which are manually defined by the interpreter [6]; [7] This approach is commonly used in the land classification using remote sensing. The expected population increase in Iraq during the coming years and the increase in the average human life will possibly lead to the phenomenon of overcrowding in the major cities in the country This is especially true in Baghdad, the capital, which has been clearly subjected to increased numbers of workforce newly-opened factories, workshops, etc. We calculate the areas of the different land cover types using Landsat 8 images and supervised MLC
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
