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Implementation of remote sensing for vegetation studying using vegetation indices and automatic feature space plot
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Study of vegetation cover distribution using DVI, PVI, WDVI indices with 2D-space plot
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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Monitoring the Vegetation and Water Content of Al-Hammar Marsh Using Remote Sensing Techniques
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The object of the presented study was to monitor the changes that had happened in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To fulfill this goal, different satellite images had been used in different times, MSS 1973, TM 1990, ETM+ 2000, 2002, and MODIS 2009, 2010. A new technique of the unsupervised classification called (Color Extracting Technique) was used to classify the satellite images. MATLAP programming used the technique and separated Al-Hammar Marsh from other water features (rivers, irrigated lands, etc.) when calculated the changes in the water content of the study region. ArcGIS 9.3 (arcMAP, arcToolbox) were used to achieve this work and calculate area of each class.

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Publication Date
Sun Mar 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Using Remote Sensing and GIS in Measuring Vegetation Cover Change from Satellite Imagery in Mosul City, North of Iraq
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Abstract<p>The aim of the study is the assessment of changes in the land cover within Mosul City in the north of Iraq using Geographic Information Systems (GIS) and remote sensing techniques during the period (2014-2018). Satellite images of the Landsat 8 on this period have been selected to classify images in order to measure normalized difference vegetation index (NDVI) to assess land cover changes within Mosul City. The results indicated that the vegetative distribution ratio in 2014 is 4.98% of the total area under study, decreased to 4.77% in 2015 and then decreased to 4.54 <italic>%</italic> in 2016, after then decreased to 3,59% in 2017,then increased to 4.39% in 2018. Land cove</p> ... Show More
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Scopus (13)
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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Monitoring Vegetation Area in Baghdad Using Normalized Difference Vegetation Index
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       Vegetation monitoring is considered an important application in remote sensing task due to variation of vegetation types and their distribution. The vegetation concentration around the Earth is increase in 5% in 2000 according to NASA monitoring. This increase is due to the Indian vegetable programs. In this research, the vegetation monitoring in Baghdad city was done using Normalized Difference Vegetation Index (NDVI) for temporal Landsat satellite images (Landsat 5 TM& Landsat 8 OIL). These images had been used and utilize in different times during the period from 2000, 2010, 2015 & 2017. The outcomes of the study demonstrate that a change in the vegetation Cover (VC) in Baghdad city. (NDVI) generally shows a

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Publication Date
Sat Dec 01 2012
Journal Name
Iraqi Journal Of Science,
Monitoring Vegetation Growth of Spectrally Landsat Satellite Imagery ETM+ 7 & TM 5 for Western Region of Iraq by Using Remote Sensing Techniques.
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Landsat-5 Thematic Mapper (TM) has been imaging the Earth since March 1984 and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) was added to the series of Landsat instruments in April 1999. In this paper the two sensors are used to monitoring the agriculture condition and detection the changing in the area of plant covers, the stability and calibration of the ETM+ has been monitored extensively since launch although it is not monitored for many years, TM now has a similar system in place to monitor stability and calibration. By referring to statistical values for the classification process, the results indicated that the state of vegetation in 1990 was in the proportion of 42.8%, while this percentage rose to 52.5% for the same study area in

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Publication Date
Sat Apr 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
The Relationship Between the Above-Ground Biomass and the Vegetation Cover Indices at Different Salinity Levels
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Abstract<p>The current study was carried out to find out the relationship between the Above-Ground Biomass and the spectral vegetative indices (Normalized Difference Vegetation Index, Soil Adjusted Vegetation Index, Difference Vegetation Index) (NDVI, SAVI, DVI) for soils with different salinity levels. Al Salamiyat Project was chosen as a study area located at an altitude of 34 m above sea level and within the geographical coordinates (E 44°.09´13.65´´ N 33°.25´ 07.87´´ and E 44°.17´ 46.03´´ N 33°.2l´40.72´´), with a total area of 14265 Dunum. Surface and subsurface soil samples were chosen from the study area and according to the previously defined salinity units, except for th</p> ... Show More
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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Studying the Effects of Contamination on Soil Properties Using Remote Sensing
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The problem of soil contamination is increased recently due to increasing the industrial wastes such as petroleum hydrocarbon, organic solvents, and heavy metals as well as maximizing the use of agricultural fertilizers. During this period, wide development of data collection methods, using remote sensing techniques in the field of soil and environment applications appear and state the suitable technique for remediation. This study deals with the application of remote sensing techniques in geoenvironmental engineering through a field spectral reflectance measurements at nine spots of naturally hydrocarbons contaminated soil in Al-Daura Refinery Company site which is located to the south west of Baghdad using radiometer device to get stan

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Improved Automatic Registration Adjustment of Multi-source Remote Sensing Datasets
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Registration techniques are still considered challenging tasks to remote sensing users, especially after enormous increase in the volume of remotely sensed data being acquired by an ever-growing number of earth observation sensors. This surge in use mandates the development of accurate and robust registration procedures that can handle these data with varying geometric and radiometric properties. This paper aims to develop the traditional registration scenarios to reduce discrepancies between registered datasets in two dimensions (2D) space for remote sensing images. This is achieved by designing a computer program written in Visual Basic language following two main stages: The first stage is a traditional registration p

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Improved Automatic Registration Adjustment of Multi-source Remote Sensing Datasets
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Registration techniques are still considered challenging tasks to remote sensing users, especially after enormous increase in the volume of remotely sensed data being acquired by an ever-growing number of earth observation sensors. This surge in use mandates the development of accurate and robust registration procedures that can handle these data with varying geometric and radiometric properties. This paper aims to develop the traditional registration scenarios to reduce discrepancies between registered datasets in two dimensions (2D) space for remote sensing images. This is achieved by designing a computer program written in Visual Basic language following two main stages: The first stage is a traditional registration process by de

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Publication Date
Tue Dec 01 2020
Journal Name
Eurasian Journal Of Biosciences
Utilizing remote sensing for studying Al-Saadya Marsh in the period 1987-2017
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The marshes are one of the important environmental features affecting human and animal systems, so the studying of changes they undergo is one of the important topics. This study is concerned with the changes occurring in the Al Saadya marsh for the period from 1987 to 2017 exclusively in the winter season (the marshes’ revival season in Iraq revive). In order to inspect the changes in this marsh, we choose 7 years to cover the study period as a criterion years, namely 1987, 1990, 1995, 2000, 2007, 2014 and 2017. The “Maximum Likelihood” classifier was used to separate the stacked land cover features, where the minimum overall accuracy ratio that recorded for all years of study was 96%. The results revealed that Al-Saadya marsh went t

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