Determination of Burdur Lake`s Area Changes Using Remote Sensing Techniques
Drought monitoring in water bodies such as lakes is essential for sustainable management of water resources. In recent years, remote sensing methods and techniques have been successfully used for mapping and monitorıng water area changes. This study aimed to investigate the ten-year change between 2...
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| Format: | Article |
| Language: | English |
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Artvin Corun University
2021-01-01
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| Series: | Doğal Afetler ve Çevre Dergisi |
| Subjects: | |
| Online Access: | http://dacd.artvin.edu.tr/tr/pub/issue/60026/760805 |
| _version_ | 1797920283511750656 |
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| author | Özümcan Alara Kaya Gordana Kaplan |
| author_facet | Özümcan Alara Kaya Gordana Kaplan |
| author_sort | Özümcan Alara Kaya |
| collection | DOAJ |
| description | Drought monitoring in water bodies such as lakes is essential for sustainable management of water resources. In recent years, remote sensing methods and techniques have been successfully used for mapping and monitorıng water area changes. This study aimed to investigate the ten-year change between 2009 and 2019 in the Burdur Lake, located between Isparta and Burdur provinces in the Göller District, through remote sensing data and techniques. In the study, object-based classification was made using Landsat-7, Landsat-8, and Sentinel-2 satellite imagery. For the classification, the frequently used normalized water difference index (NDWI) combined with threshold analysis was used for water classification. All images were acquired in September. In addition to the seasonal variation analysis, Sentinel-2 images from April and May, 2017 and 2019 were used. As a result, in the last decade, Burdur lake has lost approximately 17 km2 of its water surface. Correlation analysis of the Landsat images of September for the years 2009-2019 resulted in an R2 of 0,94. The change between spring and autumn in 2017 and 2019 was determined as 2 km2. The classification accuracies range from 90% to 96%, and the highest classification accuracy was obtained with Sentinel-2 images. The results of the study show that the changes in water areas can be monitored with high accuracy through remote sensing data and techniques. |
| first_indexed | 2024-04-10T13:59:53Z |
| format | Article |
| id | doaj.art-4419acb61cf7477c85c7b7c6c9e551c2 |
| institution | Directory Open Access Journal |
| issn | 2528-9640 2528-9640 |
| language | English |
| last_indexed | 2024-04-10T13:59:53Z |
| publishDate | 2021-01-01 |
| publisher | Artvin Corun University |
| record_format | Article |
| series | Doğal Afetler ve Çevre Dergisi |
| spelling | doaj.art-4419acb61cf7477c85c7b7c6c9e551c22023-02-15T16:10:19ZengArtvin Corun UniversityDoğal Afetler ve Çevre Dergisi2528-96402528-96402021-01-0171112https://doi.org/10.21324/dacd.760805Determination of Burdur Lake`s Area Changes Using Remote Sensing TechniquesÖzümcan Alara Kaya0https://orcid.org/0000-0003-0669-6726Gordana Kaplan1https://orcid.org/0000-0001-7522-9924Eskişehir Teknik Üniversitesi, Lisansüstü Eğitim Enstitüsü, Uzaktan Algılama ve CBS A.B.D., 25555, Eskişehir.Eskişehir Teknik Üniversitesi, Yer ve Uzay Bilimleri Enstitüsü, 25555, Eskişehir.Drought monitoring in water bodies such as lakes is essential for sustainable management of water resources. In recent years, remote sensing methods and techniques have been successfully used for mapping and monitorıng water area changes. This study aimed to investigate the ten-year change between 2009 and 2019 in the Burdur Lake, located between Isparta and Burdur provinces in the Göller District, through remote sensing data and techniques. In the study, object-based classification was made using Landsat-7, Landsat-8, and Sentinel-2 satellite imagery. For the classification, the frequently used normalized water difference index (NDWI) combined with threshold analysis was used for water classification. All images were acquired in September. In addition to the seasonal variation analysis, Sentinel-2 images from April and May, 2017 and 2019 were used. As a result, in the last decade, Burdur lake has lost approximately 17 km2 of its water surface. Correlation analysis of the Landsat images of September for the years 2009-2019 resulted in an R2 of 0,94. The change between spring and autumn in 2017 and 2019 was determined as 2 km2. The classification accuracies range from 90% to 96%, and the highest classification accuracy was obtained with Sentinel-2 images. The results of the study show that the changes in water areas can be monitored with high accuracy through remote sensing data and techniques.http://dacd.artvin.edu.tr/tr/pub/issue/60026/760805area changesdroughtremote sensingburdur lake |
| spellingShingle | Özümcan Alara Kaya Gordana Kaplan Determination of Burdur Lake`s Area Changes Using Remote Sensing Techniques Doğal Afetler ve Çevre Dergisi area changes drought remote sensing burdur lake |
| title | Determination of Burdur Lake`s Area Changes Using Remote Sensing Techniques |
| title_full | Determination of Burdur Lake`s Area Changes Using Remote Sensing Techniques |
| title_fullStr | Determination of Burdur Lake`s Area Changes Using Remote Sensing Techniques |
| title_full_unstemmed | Determination of Burdur Lake`s Area Changes Using Remote Sensing Techniques |
| title_short | Determination of Burdur Lake`s Area Changes Using Remote Sensing Techniques |
| title_sort | determination of burdur lake s area changes using remote sensing techniques |
| topic | area changes drought remote sensing burdur lake |
| url | http://dacd.artvin.edu.tr/tr/pub/issue/60026/760805 |
| work_keys_str_mv | AT ozumcanalarakaya determinationofburdurlakesareachangesusingremotesensingtechniques AT gordanakaplan determinationofburdurlakesareachangesusingremotesensingtechniques |