TRANSFORMATION OF THE NORMALIZED DIFFERENCE CHLOROPHYLL INDEX TO RETRIEVE CHLOROPHYLL-A CONCENTRATIONS IN MANILA BAY

Manila Bay is one of the most significant harbors in the region, enabling commerce and trade between the Philippines and other countries. Its abundant natural resources have provided for generations of its inhabitants and have driven socio-economic development for centuries. Like other water bodies...

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Main Authors: A. Manuel, A. C. Blanco
Format: Article
Language:English
Published: Copernicus Publications 2023-02-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVIII-4-W6-2022/217/2023/isprs-archives-XLVIII-4-W6-2022-217-2023.pdf
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author A. Manuel
A. Manuel
A. C. Blanco
A. C. Blanco
A. C. Blanco
author_facet A. Manuel
A. Manuel
A. C. Blanco
A. C. Blanco
A. C. Blanco
author_sort A. Manuel
collection DOAJ
description Manila Bay is one of the most significant harbors in the region, enabling commerce and trade between the Philippines and other countries. Its abundant natural resources have provided for generations of its inhabitants and have driven socio-economic development for centuries. Like other water bodies adjacent to highly urbanized cities, the increased organic and nutrient loading from untreated domestic, industrial, and agricultural wastes resulted to further degradation of its water quality. While frequent water quality monitoring is ideal, data from traditional field sampling methods might not be sufficient to assess the spatial and temporal variations of water quality in Manila Bay. Remote sensing fills the need for a frequent and full overview of the bay’s water quality. Sentinel-3 images were initially processed through the Case 2 Regional CoastColour (C2RCC) model to retrieve the remote sensing reflectance. The Normalized Difference Chlorophyll Index (NDCI) was computed for the images and were modeled against the C2RCC-derived chlorophyll-a estimates. From this, we were able to get a general equation (TNDCI – transformed NDCI) to retrieve chlorophyll-a concentrations from two reflectance bands (Oa8 and Oa11). TNDCI gave an R<sup>2</sup> of 0.9 and RMSE = 5.12 &micro;g/L as compared to C2RCC values, and an R<sup>2</sup> = 0.85 and RMSE = 2.44 &micro;g/L with field data.
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spelling doaj.art-66786239126e4cd59f4cbf20f04612fc2023-02-08T08:27:21ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342023-02-01XLVIII-4-W6-202221722110.5194/isprs-archives-XLVIII-4-W6-2022-217-2023TRANSFORMATION OF THE NORMALIZED DIFFERENCE CHLOROPHYLL INDEX TO RETRIEVE CHLOROPHYLL-A CONCENTRATIONS IN MANILA BAYA. Manuel0A. Manuel1A. C. Blanco2A. C. Blanco3A. C. Blanco4Department of Geodetic Engineering, University of the Philippines Diliman, PhilippinesTraining Center for Applied Geodesy and Photogrammetry, University of the Philippines Diliman, PhilippinesDepartment of Geodetic Engineering, University of the Philippines Diliman, PhilippinesTraining Center for Applied Geodesy and Photogrammetry, University of the Philippines Diliman, PhilippinesSpace Information Infrastructure Bureau, Philippine Space Agency, Diliman, Quezon City, PhilippinesManila Bay is one of the most significant harbors in the region, enabling commerce and trade between the Philippines and other countries. Its abundant natural resources have provided for generations of its inhabitants and have driven socio-economic development for centuries. Like other water bodies adjacent to highly urbanized cities, the increased organic and nutrient loading from untreated domestic, industrial, and agricultural wastes resulted to further degradation of its water quality. While frequent water quality monitoring is ideal, data from traditional field sampling methods might not be sufficient to assess the spatial and temporal variations of water quality in Manila Bay. Remote sensing fills the need for a frequent and full overview of the bay’s water quality. Sentinel-3 images were initially processed through the Case 2 Regional CoastColour (C2RCC) model to retrieve the remote sensing reflectance. The Normalized Difference Chlorophyll Index (NDCI) was computed for the images and were modeled against the C2RCC-derived chlorophyll-a estimates. From this, we were able to get a general equation (TNDCI – transformed NDCI) to retrieve chlorophyll-a concentrations from two reflectance bands (Oa8 and Oa11). TNDCI gave an R<sup>2</sup> of 0.9 and RMSE = 5.12 &micro;g/L as compared to C2RCC values, and an R<sup>2</sup> = 0.85 and RMSE = 2.44 &micro;g/L with field data.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVIII-4-W6-2022/217/2023/isprs-archives-XLVIII-4-W6-2022-217-2023.pdf
spellingShingle A. Manuel
A. Manuel
A. C. Blanco
A. C. Blanco
A. C. Blanco
TRANSFORMATION OF THE NORMALIZED DIFFERENCE CHLOROPHYLL INDEX TO RETRIEVE CHLOROPHYLL-A CONCENTRATIONS IN MANILA BAY
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title TRANSFORMATION OF THE NORMALIZED DIFFERENCE CHLOROPHYLL INDEX TO RETRIEVE CHLOROPHYLL-A CONCENTRATIONS IN MANILA BAY
title_full TRANSFORMATION OF THE NORMALIZED DIFFERENCE CHLOROPHYLL INDEX TO RETRIEVE CHLOROPHYLL-A CONCENTRATIONS IN MANILA BAY
title_fullStr TRANSFORMATION OF THE NORMALIZED DIFFERENCE CHLOROPHYLL INDEX TO RETRIEVE CHLOROPHYLL-A CONCENTRATIONS IN MANILA BAY
title_full_unstemmed TRANSFORMATION OF THE NORMALIZED DIFFERENCE CHLOROPHYLL INDEX TO RETRIEVE CHLOROPHYLL-A CONCENTRATIONS IN MANILA BAY
title_short TRANSFORMATION OF THE NORMALIZED DIFFERENCE CHLOROPHYLL INDEX TO RETRIEVE CHLOROPHYLL-A CONCENTRATIONS IN MANILA BAY
title_sort transformation of the normalized difference chlorophyll index to retrieve chlorophyll a concentrations in manila bay
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVIII-4-W6-2022/217/2023/isprs-archives-XLVIII-4-W6-2022-217-2023.pdf
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