Determining Atikhisar Reservoir’s Bathymetry from Landsat-5 TM Satellite Images Using the Stumpf Algorithm
Determining the bathymetry of shallow waters is important for managing coastal areas, river basins, and water resources. However, economic and practical difficulties in collecting bathymetric data cause disruptions in bathymetric studies. To overcome these challenges, a recent focus has involved the...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Istanbul University Press
2022-12-01
|
| Series: | Coğrafya Dergisi |
| Subjects: | |
| Online Access: | https://cdn.istanbul.edu.tr/file/JTA6CLJ8T5/86DC603031FC406A95204402B22543C4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849314911940771840 |
|---|---|
| author | Derya Öztürk |
| author_facet | Derya Öztürk |
| author_sort | Derya Öztürk |
| collection | DOAJ |
| description | Determining the bathymetry of shallow waters is important for managing coastal areas, river basins, and water resources. However, economic and practical difficulties in collecting bathymetric data cause disruptions in bathymetric studies. To overcome these challenges, a recent focus has involved the use of remote sensing technology as an alternative approach to the bathymetric mapping of shallow waters. This study uses Landsat-5 TM satellite imagery, which is free and open data, to determine the digital bathymetric model (DBM) of Atikhisar Reservoir. The study also uses the Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) to determine the reservoir’s surface area and the Stumpf algorithm to perform the bathymetric mapping. Satellite image-based DBMs were obtained using the linear regression equations created from the blue/green log-ratio values from the Landsat-5 TM satellite image and the values obtained from a 1/5000 scale digital bathymetric map for five different training reference point sets. The root mean square error (RMSE) values were calculated by comparing the DBMs with the test data. The model with the best results showed the regression determination coefficient (R2 ) to be 0.701 and the RMSE to be 2.1 m. These results reveal the potential of low-cost bathymetric map production for preliminary investigation and general evaluation in reservoirs with easy data processing from Landsat images. |
| format | Article |
| id | doaj-art-a325045a72924f8da06d3f232180ab92 |
| institution | Kabale University |
| issn | 1305-2128 |
| language | English |
| publishDate | 2022-12-01 |
| publisher | Istanbul University Press |
| record_format | Article |
| series | Coğrafya Dergisi |
| spelling | doaj-art-a325045a72924f8da06d3f232180ab922025-08-20T03:52:16ZengIstanbul University PressCoğrafya Dergisi1305-21282022-12-01459711010.26650/JGEOG2022-1099122123456Determining Atikhisar Reservoir’s Bathymetry from Landsat-5 TM Satellite Images Using the Stumpf AlgorithmDerya Öztürk0https://orcid.org/0000-0002-0684-3127Ondokuz Mayıs Üniversitesi, Samsun, TurkiyeDetermining the bathymetry of shallow waters is important for managing coastal areas, river basins, and water resources. However, economic and practical difficulties in collecting bathymetric data cause disruptions in bathymetric studies. To overcome these challenges, a recent focus has involved the use of remote sensing technology as an alternative approach to the bathymetric mapping of shallow waters. This study uses Landsat-5 TM satellite imagery, which is free and open data, to determine the digital bathymetric model (DBM) of Atikhisar Reservoir. The study also uses the Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) to determine the reservoir’s surface area and the Stumpf algorithm to perform the bathymetric mapping. Satellite image-based DBMs were obtained using the linear regression equations created from the blue/green log-ratio values from the Landsat-5 TM satellite image and the values obtained from a 1/5000 scale digital bathymetric map for five different training reference point sets. The root mean square error (RMSE) values were calculated by comparing the DBMs with the test data. The model with the best results showed the regression determination coefficient (R2 ) to be 0.701 and the RMSE to be 2.1 m. These results reveal the potential of low-cost bathymetric map production for preliminary investigation and general evaluation in reservoirs with easy data processing from Landsat images.https://cdn.istanbul.edu.tr/file/JTA6CLJ8T5/86DC603031FC406A95204402B22543C4bathymetrystumpf algorithmremote sensing |
| spellingShingle | Derya Öztürk Determining Atikhisar Reservoir’s Bathymetry from Landsat-5 TM Satellite Images Using the Stumpf Algorithm Coğrafya Dergisi bathymetry stumpf algorithm remote sensing |
| title | Determining Atikhisar Reservoir’s Bathymetry from Landsat-5 TM Satellite Images Using the Stumpf Algorithm |
| title_full | Determining Atikhisar Reservoir’s Bathymetry from Landsat-5 TM Satellite Images Using the Stumpf Algorithm |
| title_fullStr | Determining Atikhisar Reservoir’s Bathymetry from Landsat-5 TM Satellite Images Using the Stumpf Algorithm |
| title_full_unstemmed | Determining Atikhisar Reservoir’s Bathymetry from Landsat-5 TM Satellite Images Using the Stumpf Algorithm |
| title_short | Determining Atikhisar Reservoir’s Bathymetry from Landsat-5 TM Satellite Images Using the Stumpf Algorithm |
| title_sort | determining atikhisar reservoir s bathymetry from landsat 5 tm satellite images using the stumpf algorithm |
| topic | bathymetry stumpf algorithm remote sensing |
| url | https://cdn.istanbul.edu.tr/file/JTA6CLJ8T5/86DC603031FC406A95204402B22543C4 |
| work_keys_str_mv | AT deryaozturk determiningatikhisarreservoirsbathymetryfromlandsat5tmsatelliteimagesusingthestumpfalgorithm |