Water Surface Temperature and Suspended Sediment Concentration (SSC) Retrieval from Landsat Imagery, Northwest Territories, Canada
This paper presents water surface temperature retrieval using Landsat thermal band and meteorological ancillary data. The algorithms were tested using Landsat-5/7/8 imagery acquired at different study sites along the Slave River and Mackenzie River of the Northwest Territories (NWT), Canada. By comp...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2019-07-01
|
| Series: | Canadian Journal of Remote Sensing |
| Online Access: | http://dx.doi.org/10.1080/07038992.2019.1643706 |
| _version_ | 1797661140974567424 |
|---|---|
| author | Joseph Chamberland John Bennett Bing Yue |
| author_facet | Joseph Chamberland John Bennett Bing Yue |
| author_sort | Joseph Chamberland |
| collection | DOAJ |
| description | This paper presents water surface temperature retrieval using Landsat thermal band and meteorological ancillary data. The algorithms were tested using Landsat-5/7/8 imagery acquired at different study sites along the Slave River and Mackenzie River of the Northwest Territories (NWT), Canada. By comparing the retrieved temperatures with in situ water temperatures, in-depth validation of one reliable retrieved technique was successfully demonstrated. The method yielded a mean absolute error (MAE) in the range of 1.00–1.38 °C, over 7 validation locations in a 2-year observation period. This paper also presents a method to estimate suspended sediment concentration (SSC) in the Slave River region using Landsat-8 imagery. The numerical relationships between in situ SSC measurements and water-leaving reflectance in visible and near-infrared (NIR) bands were investigated through regression fitting. The SSC estimation results using the retrieved models were analyzed and validated, the NIR model was found to generate the smallest estimation errors with a MAE of 7.98 mg/L using leave-one-out (LOO) uncertainty assessment. An operational web-based tool for water surface temperature and SSC mapping based on the algorithms validated during this study has been developed to address additional monitoring requirements of the NWT communities. The design and implementation of this tool is also described. |
| first_indexed | 2024-03-11T18:41:12Z |
| format | Article |
| id | doaj.art-c2f8a505553d4570971f04d2f09300f1 |
| institution | Directory Open Access Journal |
| issn | 1712-7971 |
| language | English |
| last_indexed | 2024-03-11T18:41:12Z |
| publishDate | 2019-07-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Canadian Journal of Remote Sensing |
| spelling | doaj.art-c2f8a505553d4570971f04d2f09300f12023-10-12T13:36:22ZengTaylor & Francis GroupCanadian Journal of Remote Sensing1712-79712019-07-01453-444345610.1080/07038992.2019.16437061643706Water Surface Temperature and Suspended Sediment Concentration (SSC) Retrieval from Landsat Imagery, Northwest Territories, CanadaJoseph Chamberland0John Bennett1Bing Yue2C-COREC-COREC-COREThis paper presents water surface temperature retrieval using Landsat thermal band and meteorological ancillary data. The algorithms were tested using Landsat-5/7/8 imagery acquired at different study sites along the Slave River and Mackenzie River of the Northwest Territories (NWT), Canada. By comparing the retrieved temperatures with in situ water temperatures, in-depth validation of one reliable retrieved technique was successfully demonstrated. The method yielded a mean absolute error (MAE) in the range of 1.00–1.38 °C, over 7 validation locations in a 2-year observation period. This paper also presents a method to estimate suspended sediment concentration (SSC) in the Slave River region using Landsat-8 imagery. The numerical relationships between in situ SSC measurements and water-leaving reflectance in visible and near-infrared (NIR) bands were investigated through regression fitting. The SSC estimation results using the retrieved models were analyzed and validated, the NIR model was found to generate the smallest estimation errors with a MAE of 7.98 mg/L using leave-one-out (LOO) uncertainty assessment. An operational web-based tool for water surface temperature and SSC mapping based on the algorithms validated during this study has been developed to address additional monitoring requirements of the NWT communities. The design and implementation of this tool is also described.http://dx.doi.org/10.1080/07038992.2019.1643706 |
| spellingShingle | Joseph Chamberland John Bennett Bing Yue Water Surface Temperature and Suspended Sediment Concentration (SSC) Retrieval from Landsat Imagery, Northwest Territories, Canada Canadian Journal of Remote Sensing |
| title | Water Surface Temperature and Suspended Sediment Concentration (SSC) Retrieval from Landsat Imagery, Northwest Territories, Canada |
| title_full | Water Surface Temperature and Suspended Sediment Concentration (SSC) Retrieval from Landsat Imagery, Northwest Territories, Canada |
| title_fullStr | Water Surface Temperature and Suspended Sediment Concentration (SSC) Retrieval from Landsat Imagery, Northwest Territories, Canada |
| title_full_unstemmed | Water Surface Temperature and Suspended Sediment Concentration (SSC) Retrieval from Landsat Imagery, Northwest Territories, Canada |
| title_short | Water Surface Temperature and Suspended Sediment Concentration (SSC) Retrieval from Landsat Imagery, Northwest Territories, Canada |
| title_sort | water surface temperature and suspended sediment concentration ssc retrieval from landsat imagery northwest territories canada |
| url | http://dx.doi.org/10.1080/07038992.2019.1643706 |
| work_keys_str_mv | AT josephchamberland watersurfacetemperatureandsuspendedsedimentconcentrationsscretrievalfromlandsatimagerynorthwestterritoriescanada AT johnbennett watersurfacetemperatureandsuspendedsedimentconcentrationsscretrievalfromlandsatimagerynorthwestterritoriescanada AT bingyue watersurfacetemperatureandsuspendedsedimentconcentrationsscretrievalfromlandsatimagerynorthwestterritoriescanada |