Estimation of the chlorophyll-a concentration on the surface of Sechura Bay using Landsat 8 image data
The purpose of this study is to implement the OC2 and OC3 algorithms to estimate the concentration of surface chlorophyll-a (CCA) from image data from the OLI sensor aboard the Landsat-8 satellite. The LaSRC (Landsat 8 Surface Reflectance Code) atmospheric correction model was validated with on-site...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | Perú |
| Institución: | Universidad Nacional Mayor de San Marcos |
| Repositorio: | Revistas - Universidad Nacional Mayor de San Marcos |
| Idioma: | español |
| OAI Identifier: | oai:revistasinvestigacion.unmsm.edu.pe:article/20321 |
| Acceso en línea: | https://revistasinvestigacion.unmsm.edu.pe/index.php/fisica/article/view/20321 |
| Access Level: | acceso abierto |
| Palabra clave: | Chlorophyll-a Landsat-8 OC2 OC3 Sechura Bay Clorofila-a Bahía de Sechura |
| Sumario: | The purpose of this study is to implement the OC2 and OC3 algorithms to estimate the concentration of surface chlorophyll-a (CCA) from image data from the OLI sensor aboard the Landsat-8 satellite. The LaSRC (Landsat 8 Surface Reflectance Code) atmospheric correction model was validated with on-site measurements of the reflectance of the water surface recorded with a spectroradiometer on the surface of the fan shell crop area of the Sechura Bay. Validation results in a linear correlation coefficient of R = 95.1 % and a mean square error RMSE = 0.0095. A comparison of the CCA derived from the OC2 and OC3 algorithms was also made, resulting in an RMSE = 0.145 mg/m3 and a correlation coecient of R = 99 %. Finally, a contrast was made of the histograms of the spatial distribution of the CCA estimated from the OC2 and OC3 algorithms over a region of the study area. The results indicate a greater ability to discern the OC3 algorithm compared to the OC2 algorithm |
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