DOI: 10.57760/sciencedb.08659
title: Chlorophyll-a and total suspended solids data from the Inanda Dam, Kwa-Zula Natal, South Africa
title: Chlorophyll-a and total suspended solids data from the Inanda Dam, Kwa-Zula Natal, South Africa

description: This repository contains in-situ chlorophyll-a and total suspended solids for the Inanda Dam for 6 March 2020 and 12 May 2021. Forty-five samples were collected on each day, leading to a total of 90 samples collected overall, however nine samples were outliers and therefore were not used. Landsat 8 and Sentinel 2 satellite data were downloaded to correspond with in-situ water sample collection and the images were atmospherically and radiometrically corrected to obtain radiance and reflectance data. Landsat 8 atmospheric and radiometric corrections were completed using FLAASH, an atmospheric correction module found in the ENVI software, to obtain radiance and reflectance values for bands one to seven of Landsat 8 satellite imagery. Sentinel 2 images are already atmospherically corrected and were downloaded in two formats: Top-of-Atmopshere (TOA) and Bottom-of-Atmosphere (BOA) reflectance, however, TOA reflectance images contained 13 bands with three different resolutions, therefore the bands of TOA reflectance images were resampled to one resolution which was completed using the resampling function in SNAP. A Pearson correlation was used to determine the correlation between in-situ chl-a and TSS with bands/band ratios of satellite images. Landsat 8 band/band ratio radiance and reflectance of bands one to seven, and Sentinel 2 TOA and BOA band/band ratio reflectance of bands one to twelve were correlated with in-situ chl-a and TSS.The bands/band ratios which obtained a correlation coefficient of 0.8 and above with in-situ chl-a and TSS were used to maximise the accuracy of the algorithms developed. Fifty-seven data points were used to calibrate the algorithms, and the remaining 24 data points to validate the algorithms. Linear regression algorithms were developed in SPSS, using the form of y = a+bx, where a and b are statistically generated values, x represents the band/band ratios value, and y represents the estimated water quality parameter. The algorithms generated from Landsat 8 radiance, Landsat 8 reflectance, Sentinel 2 TOA reflectance, and Sentinel 2 BOA reflectance, which obtained the highest R2-values, were further validated using a correlation analysis in SPSS, to determine the most accurate retrieval algorithms. In ArcMap version 10.8.1, a geostatistical interpolation method was used to map and display the surface distribution of chl-a and TSS in the Inanda Dam using the developed algorithms.
description: This repository contains in-situ chlorophyll-a and total suspended solids for the Inanda Dam for 6 March 2020 and 12 May 2021. Forty-five samples were collected on each day, leading to a total of 90 samples collected overall, however nine samples were outliers and therefore were not used. Landsat 8 and Sentinel 2 satellite data were downloaded to correspond with in-situ water sample collection and the images were atmospherically and radiometrically corrected to obtain radiance and reflectance data. Landsat 8 atmospheric and radiometric corrections were completed using FLAASH, an atmospheric correction module found in the ENVI software, to obtain radiance and reflectance values for bands one to seven of Landsat 8 satellite imagery. Sentinel 2 images are already atmospherically corrected and were downloaded in two formats: Top-of-Atmopshere (TOA) and Bottom-of-Atmosphere (BOA) reflectance, however, TOA reflectance images contained 13 bands with three different resolutions, therefore the bands of TOA reflectance images were resampled to one resolution which was completed using the resampling function in SNAP. A Pearson correlation was used to determine the correlation between in-situ chl-a and TSS with bands/band ratios of satellite images. Landsat 8 band/band ratio radiance and reflectance of bands one to seven, and Sentinel 2 TOA and BOA band/band ratio reflectance of bands one to twelve were correlated with in-situ chl-a and TSS.The bands/band ratios which obtained a correlation coefficient of 0.8 and above with in-situ chl-a and TSS were used to maximise the accuracy of the algorithms developed. Fifty-seven data points were used to calibrate the algorithms, and the remaining 24 data points to validate the algorithms. Linear regression algorithms were developed in SPSS, using the form of y = a+bx, where a and b are statistically generated values, x represents the band/band ratios value, and y represents the estimated water quality parameter. The algorithms generated from Landsat 8 radiance, Landsat 8 reflectance, Sentinel 2 TOA reflectance, and Sentinel 2 BOA reflectance, which obtained the highest R2-values, were further validated using a correlation analysis in SPSS, to determine the most accurate retrieval algorithms. In ArcMap version 10.8.1, a geostatistical interpolation method was used to map and display the surface distribution of chl-a and TSS in the Inanda Dam using the developed algorithms.