2019_The Spatial-Temporal Analysis For The Land Cover_Land Change Detection and Prediction Using Geospatial Approach In South Ghor Regions, Jordan
| Format: | General Document |
|---|
| _version_ | 1860797999186182144 |
|---|---|
| building | INTELEK Repository |
| collection | Online Access |
| collectionurl | https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection3 |
| copyright | Copyright©PWB2025 |
| date | 2019-11-12 12:26 |
| format | General Document |
| id | 15357 |
| institution | UniSZA |
| originalfilename | THE SPATIAL-TEMPORAL ANALYSIS FOR THE LAND COVER_LAND CHANGE DETECTION AND PREDICTION USING GEOSPATIAL APPROACH IN SOUTH GHOR REGIONS, JORDAN |
| person | PDFsam Basic v4.2.10 Mousa Hammad Suleiman Abu Ghurah |
| recordtype | oai_dc |
| resourceurl | https://intelek.unisza.edu.my/intelek/pages/view.php?ref=15357 |
| sourcemedia | Server storage Scanned document |
| spelling | 15357 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=15357 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection3 General Document Library Staff (Top Management) Library Staff (Management) Library Staff (Support) Terengganu English UniSZA East Coast Environmental Research Institute application/pdf 1.5 PDFsam Basic v4.2.10 Jordan Server storage Scanned document Universiti Sultan Zainal Abidin UniSZA Private Access Universiti Sultan Zainal Abidin SAMBox 2.3.4; modified using iTextSharp™ 5.5.10 ©2000-2016 iText Group NV (AGPL-version) 2019-11-12 12:26 THE SPATIAL-TEMPORAL ANALYSIS FOR THE LAND COVER_LAND CHANGE DETECTION AND PREDICTION USING GEOSPATIAL APPROACH IN SOUTH GHOR REGIONS, JORDAN 292 2019_The Spatial-Temporal Analysis For The Land Cover_Land Change Detection and Prediction Using Geospatial Approach In South Ghor Regions, Jordan Copyright©PWB2025 Spatial analysis (Statistics) Geospatial data—Environmental aspects Mousa Hammad Suleiman Abu Ghurah Spatial-Temporal Analysis Land Cover_Land Geospatial South Ghor Regions Problem Statement: Land Cover/Land Use (LCLU) changes studies have become a principal part of current policies for natural resources management in Jordan. Previous studies of LCLU in Jordan have not included a detailed and complete analysis of the intensity of LCLU change, the spatial characteristics of LCLU transitions, and the landscape index. The main objectives of this study were to identify the changes of LCLU and to determine strategies for sustainable land management in South Ghor, Jordon. Methodology: Remote Sensing (RS) data, such as satellite images and Geographic Information System (GIS) technology, were used for the supervised classification of Maximum Likelihood Algorithm (MLA) and the changes detection to classify LCLU changes using four satellite images taken in 1972, 1989, 1999 and 2016. The LCLU classification falls into four categories, namely agricultural land, pastures and bare land, urban area and water bodies. The Principal Component Analysis (PCA) was applied to evaluate and verify LCLU significant forces variables. Results: The validation result recorded the accuracy of overall classification of 95.62%, 96.87%, 95.00%, and 94.37%, and overall Kappa Statistics values of 0.94, 0.96, 0.93 and 0.90, respectively. The results showed an increase in urban areas and agricultural land development, and a decrease in pastures and bare land and water bodies from 1972 until 2016. Besides that, PCA reveals that there were two factors found in the region that are responsible for 57.32% of the total LCLU changes. Predictions about LCLU changes in 2033 suggest that urban and agricultural areas will increase from 4.81% and 12.73% in 2016 to 7.24% and 13.82% in 2033, respectively. In contrast, the percentage of water bodies and pastures land areas will decrease from 37.70% and 44.76% in 2016 to 36.18% and 42.75% by 2033, respectively. There were several factors taken into consideration in proposing a model as a driving force of LCLU changes. Conclusion: The study concluded that there are many significant factors that have brought changes to LCLU categories in South Ghor areas such as population growth and socio-economic factors. These factors are essential in developing a model of action plan based on the changes of LCLU in Jordan. This study is significant for better policy making, ecosystem services, natural resource and suitable land planning, as well as sustainable development and useful land management plans for South Ghor and similar regions. Land cover—Jordan—South Ghor Region—Remote sensing Land use—Jordan—South Ghor Region—Changes Remote sensing—Jordan—Applications in land use Land use—Mathematical models Geographic information systems—Applications in environmental studies Environmental monitoring—Jordan—South Ghor Region Landscape changes—Jordan—South Ghor Region Sustainable land management—Jordan Dissertations, Academic Thesis |
| spellingShingle | 2019_The Spatial-Temporal Analysis For The Land Cover_Land Change Detection and Prediction Using Geospatial Approach In South Ghor Regions, Jordan |
| state | Terengganu |
| subject | Spatial analysis (Statistics) Geospatial data—Environmental aspects Land cover—Jordan—South Ghor Region—Remote sensing Land use—Jordan—South Ghor Region—Changes Remote sensing—Jordan—Applications in land use Land use—Mathematical models Geographic information systems—Applications in environmental studies Environmental monitoring—Jordan—South Ghor Region Landscape changes—Jordan—South Ghor Region Sustainable land management—Jordan Dissertations, Academic |
| summary | Problem Statement: Land Cover/Land Use (LCLU) changes studies have become a principal part of current policies for natural resources management in Jordan. Previous studies of LCLU in Jordan have not included a detailed and complete analysis of the intensity of LCLU change, the spatial characteristics of LCLU transitions, and the landscape index. The main objectives of this study were to identify the changes of LCLU and to determine strategies for sustainable land management in South Ghor, Jordon. Methodology: Remote Sensing (RS) data, such as satellite images and Geographic Information System (GIS) technology, were used for the supervised classification of Maximum Likelihood Algorithm (MLA) and the changes detection to classify LCLU changes using four satellite images taken in 1972, 1989, 1999 and 2016. The LCLU classification falls into four categories, namely agricultural land, pastures and bare land, urban area and water bodies. The Principal Component Analysis (PCA) was applied to evaluate and verify LCLU significant forces variables. Results: The validation result recorded the accuracy of overall classification of 95.62%, 96.87%, 95.00%, and 94.37%, and overall Kappa Statistics values of 0.94, 0.96, 0.93 and 0.90, respectively. The results showed an increase in urban areas and agricultural land development, and a decrease in pastures and bare land and water bodies from 1972 until 2016. Besides that, PCA reveals that there were two factors found in the region that are responsible for 57.32% of the total LCLU changes. Predictions about LCLU changes in 2033 suggest that urban and agricultural areas will increase from 4.81% and 12.73% in 2016 to 7.24% and 13.82% in 2033, respectively. In contrast, the percentage of water bodies and pastures land areas will decrease from 37.70% and 44.76% in 2016 to 36.18% and 42.75% by 2033, respectively. There were several factors taken into consideration in proposing a model as a driving force of LCLU changes. Conclusion: The study concluded that there are many significant factors that have brought changes to LCLU categories in South Ghor areas such as population growth and socio-economic factors. These factors are essential in developing a model of action plan based on the changes of LCLU in Jordan. This study is significant for better policy making, ecosystem services, natural resource and suitable land planning, as well as sustainable development and useful land management plans for South Ghor and similar regions. |
| title | 2019_The Spatial-Temporal Analysis For The Land Cover_Land Change Detection and Prediction Using Geospatial Approach In South Ghor Regions, Jordan |
| title_full | 2019_The Spatial-Temporal Analysis For The Land Cover_Land Change Detection and Prediction Using Geospatial Approach In South Ghor Regions, Jordan |
| title_fullStr | 2019_The Spatial-Temporal Analysis For The Land Cover_Land Change Detection and Prediction Using Geospatial Approach In South Ghor Regions, Jordan |
| title_full_unstemmed | 2019_The Spatial-Temporal Analysis For The Land Cover_Land Change Detection and Prediction Using Geospatial Approach In South Ghor Regions, Jordan |
| title_short | 2019_The Spatial-Temporal Analysis For The Land Cover_Land Change Detection and Prediction Using Geospatial Approach In South Ghor Regions, Jordan |
| title_sort | 2019_the spatial-temporal analysis for the land cover_land change detection and prediction using geospatial approach in south ghor regions, jordan |