SPATIO-TEMPORAL WATER QUALITY MAPPING USING SATELLITE DATA AROUND A MANGROVE PLANTATION IN CAGSAO, CALABANGA, CAMARINES SUR

The Cagsao mangrove is a thriving young forest along the San Miguel Bay (SMB), Camarines Sur. To establish the Spatio-temporal Water Quality mapping, data from the Chesapeake Bay, an estuary in the United States of America (USA), was sourced as the train set for this study. Spatio-temporal maps of c...

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Autor principal:	K. C. M. Saddi
Formato:	article
Lenguaje:	EN
Publicado:	Copernicus Publications 2021
Materias:	Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820
Acceso en línea:	https://doaj.org/article/c2659543737d4bfbb35c0d7994889fe0
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spelling	oai:doaj.org-article:c2659543737d4bfbb35c0d7994889fe02021-11-19T01:46:12ZSPATIO-TEMPORAL WATER QUALITY MAPPING USING SATELLITE DATA AROUND A MANGROVE PLANTATION IN CAGSAO, CALABANGA, CAMARINES SUR10.5194/isprs-archives-XLVI-4-W6-2021-257-20211682-17502194-9034https://doaj.org/article/c2659543737d4bfbb35c0d7994889fe02021-11-01T00:00:00Zhttps://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVI-4-W6-2021/257/2021/isprs-archives-XLVI-4-W6-2021-257-2021.pdfhttps://doaj.org/toc/1682-1750https://doaj.org/toc/2194-9034The Cagsao mangrove is a thriving young forest along the San Miguel Bay (SMB), Camarines Sur. To establish the Spatio-temporal Water Quality mapping, data from the Chesapeake Bay, an estuary in the United States of America (USA), was sourced as the train set for this study. Spatio-temporal maps of chlorophyll and dissolved oxygen were generated using Linear Regression (LR) models which were derived from the train set and satellite images of the SMB. GNU (GNU’s not UNIX) Octave was used for the image processing, computing, and analysis. There were three phases in the image processing conducted in this study, 1) extraction of image data of the corresponding measure points from the train area, 2) conversion of the satellite study area to a two-color raster image, and 3) generation of the spatio-temporal maps from the analysis. The study found that the SMB is in the range of Mesotrophic to Moderate Eutrophic classification. The decay from two other point sources (Manga River and Libmanan River) was compared to that of Tigman River, an adjacent river to the Cagsao mangrove forest to determine variations and impact of the mangrove forest in the water quality of the SMB. The presence of Cagsao mangrove forest was found to affect the gap of increasing chlorophyll levels from shore toward the bay center in the adjacent Tigman River unlike Manga River and Libmanan River, which have both no adjacent mangrove forest in the river mouth area. The corresponding satellite images for the dataset taken during and near the date of the train area measurements were also extracted.K. C. M. SaddiK. C. M. SaddiCopernicus PublicationsarticleTechnologyTEngineering (General). Civil engineering (General)TA1-2040Applied optics. PhotonicsTA1501-1820ENThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVI-4-W6-2021, Pp 257-264 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820
spellingShingle	Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820 K. C. M. Saddi K. C. M. Saddi SPATIO-TEMPORAL WATER QUALITY MAPPING USING SATELLITE DATA AROUND A MANGROVE PLANTATION IN CAGSAO, CALABANGA, CAMARINES SUR
description	The Cagsao mangrove is a thriving young forest along the San Miguel Bay (SMB), Camarines Sur. To establish the Spatio-temporal Water Quality mapping, data from the Chesapeake Bay, an estuary in the United States of America (USA), was sourced as the train set for this study. Spatio-temporal maps of chlorophyll and dissolved oxygen were generated using Linear Regression (LR) models which were derived from the train set and satellite images of the SMB. GNU (GNU’s not UNIX) Octave was used for the image processing, computing, and analysis. There were three phases in the image processing conducted in this study, 1) extraction of image data of the corresponding measure points from the train area, 2) conversion of the satellite study area to a two-color raster image, and 3) generation of the spatio-temporal maps from the analysis. The study found that the SMB is in the range of Mesotrophic to Moderate Eutrophic classification. The decay from two other point sources (Manga River and Libmanan River) was compared to that of Tigman River, an adjacent river to the Cagsao mangrove forest to determine variations and impact of the mangrove forest in the water quality of the SMB. The presence of Cagsao mangrove forest was found to affect the gap of increasing chlorophyll levels from shore toward the bay center in the adjacent Tigman River unlike Manga River and Libmanan River, which have both no adjacent mangrove forest in the river mouth area. The corresponding satellite images for the dataset taken during and near the date of the train area measurements were also extracted.
format	article
author	K. C. M. Saddi K. C. M. Saddi
author_facet	K. C. M. Saddi K. C. M. Saddi
author_sort	K. C. M. Saddi
title	SPATIO-TEMPORAL WATER QUALITY MAPPING USING SATELLITE DATA AROUND A MANGROVE PLANTATION IN CAGSAO, CALABANGA, CAMARINES SUR
title_short	SPATIO-TEMPORAL WATER QUALITY MAPPING USING SATELLITE DATA AROUND A MANGROVE PLANTATION IN CAGSAO, CALABANGA, CAMARINES SUR
title_full	SPATIO-TEMPORAL WATER QUALITY MAPPING USING SATELLITE DATA AROUND A MANGROVE PLANTATION IN CAGSAO, CALABANGA, CAMARINES SUR
title_fullStr	SPATIO-TEMPORAL WATER QUALITY MAPPING USING SATELLITE DATA AROUND A MANGROVE PLANTATION IN CAGSAO, CALABANGA, CAMARINES SUR
title_full_unstemmed	SPATIO-TEMPORAL WATER QUALITY MAPPING USING SATELLITE DATA AROUND A MANGROVE PLANTATION IN CAGSAO, CALABANGA, CAMARINES SUR
title_sort	spatio-temporal water quality mapping using satellite data around a mangrove plantation in cagsao, calabanga, camarines sur
publisher	Copernicus Publications
publishDate	2021
url	https://doaj.org/article/c2659543737d4bfbb35c0d7994889fe0
work_keys_str_mv	AT kcmsaddi spatiotemporalwaterqualitymappingusingsatellitedataaroundamangroveplantationincagsaocalabangacamarinessur AT kcmsaddi spatiotemporalwaterqualitymappingusingsatellitedataaroundamangroveplantationincagsaocalabangacamarinessur
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SPATIO-TEMPORAL WATER QUALITY MAPPING USING SATELLITE DATA AROUND A MANGROVE PLANTATION IN CAGSAO, CALABANGA, CAMARINES SUR

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