The Effect of War on Land Use Dynamics in Mosul Iraq Using Remote Sensing and GIS Techniques

Jumaah, Huda Jamal; Kalantar, Bahareh; Ojogbane, Sani Success; Ajaj, Qayssar Mahmood; Jumaah, Sarah Jamal

doi:10.1109/igarss47720.2021.9553165

Cited by 8 publications

(7 citation statements)

References 16 publications

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“…GIS includes useful tools and applications that facilitate the process of analysis and evaluation in addition to creating models [15][16][17][18][19][20] and detecting changes [7,11]. The classification process by SVM included creating training samples and then classifying the raster using the Esri classifier definition file (ecd.).…”

Section: Methodsmentioning

confidence: 99%

“…The final step involved calculating water levels based on lake depth and extracted areas. The equation of SVM can be written as [11]:…”

Section: Methodsmentioning

confidence: 99%

“…where a vector (xi) is of each r training case, it represents a spectral response composed of a description of the class item (y i ). ∝ i (i = 1, ..., r) are multipliers of Lagrange, k(x, x i ) is the task of the kernel while b refers to hyperplane space from starting point [11]. Moreover, NDWI was used to compare changes based on Sentinel-2 Images from 2017 to 2022.…”

Section: Methodsmentioning

confidence: 99%

“…For land cover detections, pixel-based classification algorithms have been developed [10]. The distinguished one involves Maximum Likelihood Classification, Support Vector Machine (SVM), and Decision Tree [11]. The classification type and training data attributes influence classification performance; these conditions must be carefully considered [12].…”

Section: Introductionmentioning

confidence: 99%

“…The classification type and training data attributes influence classification performance; these conditions must be carefully considered [12]. SVM classification reliability of hyper-spectral images has been approved in many papers [11,13].…”

Section: Introductionmentioning

confidence: 99%

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Surface Water Changes and Water Depletion of Lake Hamrin, Eastern Iraq, Using Sentinel-2 Images and Geographic Information Systems

Jumaah¹,

Ameen²,

Kalantar³

2023

Adv Environ Eng Res

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Iraq’s lakes and rivers are currently exposed to drought because of climatic and political conditions. This study uses satellite images and geographic information systems to display the water depletion and the change in the surface water area of Hamrin Lake. Sentinel-2 imagery of 2018 and 2022 was used to analyze the surface water area changes and water depletion. A comparison was made by studying the changes that happened between 2018 and 2022 respectively. Moreover, a supervised classification technique was implemented using the Support Vector Machine algorithm (SVM). Besides the shrinkage of Hamrin Lake was determined based on 2017 to 2022 Sentinel-2 images and the Normal Difference Water Index (NDWI). Findings showed an extreme change occurred in the surface water area of the lake, which had decreased by 73% in study years and changed to land in 2022. Based on the resultant maps clear alteration is notable in the shape of the lake from north to southeast where the maximum retraction occurred. The surface water area was 144 km<sup>2</sup> in 2018 which decreased to 39 km<sup>2</sup> in 2022 and was concentrated in the western part of the lake. Besides, the lake's capacity has become 234 million cubic meters, and the amount of water in it is very little while its capacity is more than two billion cubic meters. This sharp drop in the water level in the lake indicates that what is flowing to the lake is less than what is released from it, especially due to the lack of rain. In addition to the drought, the neighboring countries have taken measures to change courses, cut off some rivers, and build dams, all of which are additional influential factors that impose quick intervention and action to prevent the lake from drying out completely.

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