ALI KADHIM HUSSEIN, NABEEL ABBOOD KADHIM, ADIL SHNAWA JABER AND ALI ABID ABOJASSIM*
Physics Department, Faculty of Dentistry, University of Kufa, Kufa, Najaf, Iraq
*(e-mail : email@example.com; Mobile : 0964-7801103720)
(Received : April 16, 2020; Accepted : June 21, 2020)
In this study, Al-Manathera district was monitored and mapped using Landsat-8 OLI imagery from the years 2013 to 2019 as well as evaluated land use and land cover changes in the district. Maximum likehood technology was achieved to create the signature class of significant LULC category, barren land, agriculture land, orchards, water bodies and built-up area. After certifying suitable accuracy value for each classified image, a detail classification change detection analysis was performed. Image differencing statistical change detection technology, change dynamics analysis was also applied to assess the statistics of two images. According to remote sensing (RS) and geographic information system (GIS) techniques, the study was a try for monitoring the change in LULC patterns of Al-Manathera for the period 2013 to 2019. This study showed that agricultural land, built-up area, barren land and water bodies decreased by -7.91, -0.20 -1.76 and -0.08%, respectively, while orchards increased by 9.95%.
Key words : Change detection, remote sensing, ERDAS imagine and Al-Manathera