Assessing Land-Use Change Induced by the Karkhe Dam Using Satellite Images and Maximum Likelihood Classification Method
The Karkhe River is one of the most important rivers in Iran and is the third largest river in terms of the discharge volume. In its wild state. the river usually left many damage its wake. In order to reduce these detrimental out comes, the Karkhe Dam was built, which is one of the most important a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | fas |
| Published: |
Marvdasht Branch, Islamic Azad University
2016-06-01
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| Series: | مهندسی منابع آب |
| Subjects: | |
| Online Access: | https://wej.marvdasht.iau.ir/article_1829_97aad47559747638e68ca844ab1304e0.pdf |
| Summary: | The Karkhe River is one of the most important rivers in Iran and is the third largest river in terms of the discharge volume. In its wild state. the river usually left many damage its wake. In order to reduce these detrimental out comes, the Karkhe Dam was built, which is one of the most important and also the largest dams in Iran and the Middle East. This dam has instigated an economic reforminits basin, such as changes in the land-use, amount of water, vegetation and the urban areas. Some of the major changes occurred ofter the dam construction have been evaluated: The Using Landsat satellite images spanning between 1352 and 1392, maximum likelihood classification identifying 7 classes was conducted on the pre-processed images. The results showed the barren soil decrease of 0.2 percent; the residential area, vegetation and water supply have increased by 2.36, 1.4 and 2.5 percent, respectively. In spite of the logical trend of these results, the accuracy assessment was as an added measure to confirmed the previous results. The evaluation showed a high accuracy almost in all of the classification results. The overall accuracy and the Kappa coefficient estimated from the accuracy assessment are higher than 90% and 0.9, respectively, while the user and producer accuracies are more than 80%. This demonstrates the high performance of the maximum likelihood classification. |
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| ISSN: | 2008-6377 2423-7191 |