A QUICK SEASONAL DETECTION AND ASSESSMENT OF INTERNATIONAL SHADEGAN WETLAND WATER BODY EXTENT USING GOOGLE EARTH ENGINE CLOUD PLATFORM
Understanding the variation of Water Extent (WE) can provide insights into Wetland conservation and management. In this study, and-inter inner-annual variations of WE were analyzed during 2019–2021 to understand the spatiotemporal changes of the International Shadegan Wetland, Iran. We utilized a th...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2023-01-01
|
| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/X-4-W1-2022/699/2023/isprs-annals-X-4-W1-2022-699-2023.pdf |
| _version_ | 1797952192386170880 |
|---|---|
| author | S. M. Seyed Mousavi M. Akhoondzadeh |
| author_facet | S. M. Seyed Mousavi M. Akhoondzadeh |
| author_sort | S. M. Seyed Mousavi |
| collection | DOAJ |
| description | Understanding the variation of Water Extent (WE) can provide insights into Wetland conservation and management. In this study, and-inter inner-annual variations of WE were analyzed during 2019–2021 to understand the spatiotemporal changes of the International Shadegan Wetland, Iran. We utilized a thresholding process on Modified Normalized Difference Water Index (MNDWI) to extract the WE quickly and accurately using the Google Earth Engine (GEE) platform. The water surface analysis showed that: (1) WE had a downward trend from 2019 to 2021, with the overall average WE being 1405.23 km<sup>2</sup>; (2) the water area reached its peak due to the water supply to International Shadegan Wetland through the Jarahi River and upstream reservoirs at the end of 2019 and the beginning of 2020, and the largest water body appeared in Winter 2019, reaching 1953.31 km<sup>2</sup>. In contrast, the smallest water body appeared in Autumn 2021, reaching 563.56 km<sup>2</sup>; (3) The WE of the wetland showed predictable seasonal characteristics. The water area in Winter was the largest, with an average value of 1829.1 km<sup>2</sup>, while it was the smallest in Summer, with an average value of 1100.3 km<sup>2</sup>; (4) The average water area in 2019 was 1490.5 km<sup>2</sup> whereas in 2020 and 2021 decreased by 9% and 25%, respectively, and reached 968.6 km<sup>2</sup> and 811.9 km<sup>2</sup>. Finally, to evaluate the proposed model, its results were compared with the Random Forest (RF) classification results. Accordingly, Histogram Analysis (HA) classification achieved 94.6% of the average overall accuracy and the average Kappa coefficient of 0.93, but the RF method obtained 95.38% of the average overall accuracy and an average Kappa coefficient of 0.94. |
| first_indexed | 2024-04-10T22:43:34Z |
| format | Article |
| id | doaj.art-2127209482e54c4e8cf8eb0f4ef761f4 |
| institution | Directory Open Access Journal |
| issn | 2194-9042 2194-9050 |
| language | English |
| last_indexed | 2024-04-10T22:43:34Z |
| publishDate | 2023-01-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-2127209482e54c4e8cf8eb0f4ef761f42023-01-15T21:34:16ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502023-01-01X-4-W1-202269970610.5194/isprs-annals-X-4-W1-2022-699-2023A QUICK SEASONAL DETECTION AND ASSESSMENT OF INTERNATIONAL SHADEGAN WETLAND WATER BODY EXTENT USING GOOGLE EARTH ENGINE CLOUD PLATFORMS. M. Seyed Mousavi0M. Akhoondzadeh1School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, IranSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, IranUnderstanding the variation of Water Extent (WE) can provide insights into Wetland conservation and management. In this study, and-inter inner-annual variations of WE were analyzed during 2019–2021 to understand the spatiotemporal changes of the International Shadegan Wetland, Iran. We utilized a thresholding process on Modified Normalized Difference Water Index (MNDWI) to extract the WE quickly and accurately using the Google Earth Engine (GEE) platform. The water surface analysis showed that: (1) WE had a downward trend from 2019 to 2021, with the overall average WE being 1405.23 km<sup>2</sup>; (2) the water area reached its peak due to the water supply to International Shadegan Wetland through the Jarahi River and upstream reservoirs at the end of 2019 and the beginning of 2020, and the largest water body appeared in Winter 2019, reaching 1953.31 km<sup>2</sup>. In contrast, the smallest water body appeared in Autumn 2021, reaching 563.56 km<sup>2</sup>; (3) The WE of the wetland showed predictable seasonal characteristics. The water area in Winter was the largest, with an average value of 1829.1 km<sup>2</sup>, while it was the smallest in Summer, with an average value of 1100.3 km<sup>2</sup>; (4) The average water area in 2019 was 1490.5 km<sup>2</sup> whereas in 2020 and 2021 decreased by 9% and 25%, respectively, and reached 968.6 km<sup>2</sup> and 811.9 km<sup>2</sup>. Finally, to evaluate the proposed model, its results were compared with the Random Forest (RF) classification results. Accordingly, Histogram Analysis (HA) classification achieved 94.6% of the average overall accuracy and the average Kappa coefficient of 0.93, but the RF method obtained 95.38% of the average overall accuracy and an average Kappa coefficient of 0.94.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/X-4-W1-2022/699/2023/isprs-annals-X-4-W1-2022-699-2023.pdf |
| spellingShingle | S. M. Seyed Mousavi M. Akhoondzadeh A QUICK SEASONAL DETECTION AND ASSESSMENT OF INTERNATIONAL SHADEGAN WETLAND WATER BODY EXTENT USING GOOGLE EARTH ENGINE CLOUD PLATFORM ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | A QUICK SEASONAL DETECTION AND ASSESSMENT OF INTERNATIONAL SHADEGAN WETLAND WATER BODY EXTENT USING GOOGLE EARTH ENGINE CLOUD PLATFORM |
| title_full | A QUICK SEASONAL DETECTION AND ASSESSMENT OF INTERNATIONAL SHADEGAN WETLAND WATER BODY EXTENT USING GOOGLE EARTH ENGINE CLOUD PLATFORM |
| title_fullStr | A QUICK SEASONAL DETECTION AND ASSESSMENT OF INTERNATIONAL SHADEGAN WETLAND WATER BODY EXTENT USING GOOGLE EARTH ENGINE CLOUD PLATFORM |
| title_full_unstemmed | A QUICK SEASONAL DETECTION AND ASSESSMENT OF INTERNATIONAL SHADEGAN WETLAND WATER BODY EXTENT USING GOOGLE EARTH ENGINE CLOUD PLATFORM |
| title_short | A QUICK SEASONAL DETECTION AND ASSESSMENT OF INTERNATIONAL SHADEGAN WETLAND WATER BODY EXTENT USING GOOGLE EARTH ENGINE CLOUD PLATFORM |
| title_sort | quick seasonal detection and assessment of international shadegan wetland water body extent using google earth engine cloud platform |
| url | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/X-4-W1-2022/699/2023/isprs-annals-X-4-W1-2022-699-2023.pdf |
| work_keys_str_mv | AT smseyedmousavi aquickseasonaldetectionandassessmentofinternationalshadeganwetlandwaterbodyextentusinggoogleearthenginecloudplatform AT makhoondzadeh aquickseasonaldetectionandassessmentofinternationalshadeganwetlandwaterbodyextentusinggoogleearthenginecloudplatform AT smseyedmousavi quickseasonaldetectionandassessmentofinternationalshadeganwetlandwaterbodyextentusinggoogleearthenginecloudplatform AT makhoondzadeh quickseasonaldetectionandassessmentofinternationalshadeganwetlandwaterbodyextentusinggoogleearthenginecloudplatform |