تغيرات الغطاء الأرضي في حوض وادي بنا و انعكاساتها البيئية
باستخدام الجيوماتكس
دراسة في جغرافية البيئة
أطروحة مقدمة إلى كلية الآداب في جامعة عدن باليمن
وهي جزء من متطلبات الحصول على درجة الدكتوراه فلسفة
في الجغرافيا
من الباحثة
تهاني عباس أحمد عقلان
بإشراف
الأستاذ المشارك الدكتور
فهمي علي سعيد البنأ
2023م - 1445هـ
Land Cover Changes in Wadi Bana Basin and its Environmental Implications Using Geomatics (A study in Environmental Geography)
A thesis submitted to the Council of the College of Arts at University of Aden as part of the requirements for obtaining a PhD in Geography
By:
Tahani Abbas Ahmed Aqlan
SUPERVISOR:
Pro. Fahmi Ali Saeed Alban,a
2023 - 1445
Abstract
Studying land cover change and predicting these changes using temporal-spatial data is important for environmental monitoring and better management planning. The main objective of this study is to track and discover the change of land cover, its causes and the extent of its impact on the natural environment for the period 1989- 2022. The methodology of the study relied on the use of geomatics techniques in determining the classes of land cover and predicting their future changes in the Upper Wadi Bana Basin, whose borders lies between longitude 44 15 8" to 44 33 18"E, and latitude 14 00 29" to 14 18 52"N, Northeast of Ibb Governorate, within the central highlands of the Republic of Yemen.
The study was divided into six chapters, the first of which is the theoretical framework and includes the introduction, objectives, curricula, methodology, previous studies, and others. As for the second chapter, it included the employment of geomatics in the study of land cover and its changes, while the third chapter dealt with the natural and human characteristics of the study area, while the fourth chapter dealt with digital processing and interpretation satellite images of the land cover, The fifth chapter included the classification of the land cover of the study area, Finally, the sixth chapter included the detection of land cover changes, future predictions, and their environmental repercussions in the study area, the study also came up with many results and recommendations related to the study problem and its objectives.
Landsat-5 TM of year 1989, Landsat-7 ETM+ of year 2002 and Landsat-9 OLI-2 of year 2022 by Earth Explorer were downloaded and preprocessed with ERDAS IMAGINE software, ArcGIS pro. Used Support Vector Machine algorithm (SVM) were used for classifying land cover, which has proven to be one of the best algorithms for finding classes of land cover. And following the updated Anderson classification (National Land Cover Data Classification System (NLCD)) with the work of the classification error matrix to verify the accuracy of the classification for the year 2022. Kappa coefficient reached to evaluate the classification accuracy of the error matrix (88%). Where the values of the Kappa coefficient of classification indicate a strong agreement between the classified and reference data, then the categorical change detection algorithm and the pixel value change detection algorithm in ArcGIS pro software were used to find the type and change area for each category. Used TerrSet and automata software were used Cellular (Markov) modeling for land cover prediction Modeling the transition potential and thus predicting future changes of the land cover. was calculated using the CA-Markov model, and the overall accuracy of Kappa (86.7%) was obtained by comparing the actual data for the year 2022 with the land cover simulation with data from the same year, and thus the prediction was made for the year 2050. The study concluded that there are five main classes of land cover represented by water, developed, barren, agricultural (permanent and seasonal) and finally the mixed land class. The area of each category was also found, and agricultural land constituted the highest percentage (69%) of the area of the study area, followed by barren lands (22.6%).As for the second result, it is the emergence of the highest value of changes in the year 2022 in the category of agricultural land by (7.6) km2 by (1.2%) than it was in the year 1989, where part of it turned into barren or urban lands. As for the third result, it is for the future prediction of the state of the land cover, as it showed that there will be a state of deterioration in the areas of some covers, the most important of which are agricultural lands by (4%) compared to the year (2022), and the expansion of urban areas by (4.7%) and arid (7.6%). According to the results of the study, the main causes of land cover changes are represented by human factors, and then comes the influence of natural factors, which requires a comprehensive study using additional data and models to give planners and decision makers clear information about land cover changes and its environmental impacts.
Keywords: Land Cover Changes, Geomatics, Satellite Images, Environmental Repercussions, Wadi Bana, Future Predictions.
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