TY - JOUR ID - TI - Mapping LCLU Using Python Scripting AU - Noor E. Sadiqe AU - Khalid I. Hasoon AU - Oday Z. Jasim PY - 2019 VL - 37 IS - 4part (A) Engineering SP - 140 EP - 147 JO - Engineering and Technology Journal مجلة الهندسة والتكنولوجيا SN - 16816900 24120758 AB - Land cover land use changes constantly with the time atlocal, regional, and global scales, therefore, remote sensing provideswide, and broad information for quantifying the location, extent, andvariability of change; the reason and processes of change; and theresponses to and consequences of change. And considering to theimportance of mapping of (LCLU). For that reason this study will focuson the problems arising from the traditional classification (LCLU) thatbased on spatial resolution only which leads to prediction a thematicmap with noisy classes, and using a new method that depend on spectraland spatial resolution to produce an acceptable classification andproducing a thematic map with an acceptable database by usingartificial neural network (ANN) and python in additional to otherprogram. In this study the methods of classification were studied throughusing two images for the same study area , rapid eye image which hasthree spectral bands with high spatial resolution(5m) and Landsat 8image (high spectral resolution with eight bands), also several programslike ENVI version 5.1, Arc GIS version 10.3, Python 3, and GPS. Theresult for this research was sensuousness as geometrics accuracyaccepted in map production

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