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Titlebook: Environmental Remote Sensing and GIS in Iraq; Ayad M. Fadhil Al-Quraishi,Abdelazim M. Negm Book 2020 The Editor(s) (if applicable) and The

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Characterization and Classification of Soil Map Units by Using Remote Sensing and GIS in Bahar Al-Na13. Some enhancements have been made (radiation, spectral and spatial) add to unsupervised classification, as well as using earth indicators (EIs). The used EIs include soil color, texture, natural plants and topography. These EIs are used in determining the researcher movement paths to select 16 Pe
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Proximal Soil Sensing Applications in Soil Fertilityand predicted total N values for Rumetha and 0.43 for Samawa location. While NIRS- based validation models achieved highly predictive power with an R.v of 0.84 between laboratory-measured and predicted total N values for Rumetha and 0.85 for Samawa location. These results reveal an extreme decrease
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Monitoring of the Land Cover Changes in Iraqm 2003 to 2013 to monitor these changes. MODIS-NDVI scenes were used to detect the relationship between the NDVI values and both of the annual precipitation and the elevation. Croplands and annual precipitation seem to be correlated. It is a direct relationship between the accumulative annual precip
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Effects of Land Cover Change on Surface Runoff Using GIS and Remote Sensing: A Case Study Duhok Sub-ata of land cover changes were mapped from 1990 to 2016, using a temporal satellite image (Landsat) to identify land cover and land use changes. Land use and land cover were integrated with a hydrological model SCS-CN to compute the runoff volume from the catchment area. Geographic Information Syste
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Monitoring and Mapping of Land Threats in Iraq Using Remote Sensingtion process. About more than 25% of the land area of Iraq has a serious erosion problem. More than 20% of the total area, mainly in southern Iraq was seriously affected by water lodging. So, most of Iraqi agricultural lands are highly affected by one or more of the desertification processes due to
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The Aeolian Sand Dunes in Iraq: A New Insighty types of sensors: passive and active have been utilized in this chapter. The aeolian sand dunes were extracted from Landsat TM and OLI acquired in 2000 and 2016, respectively. This result shows that desertification has been increased in the study area. Moreover, we used two C-Band SAR Sentinel-1A
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