Estimation of Chlorophyll-a Concentrations in Small Water Bodies: Comparison of Fused Gaofen-6 and Sentinel-2 Sensors

Abstract

Chlorophyll-a concentrations in water bodies are one of the most important environmental evaluation indicators in monitoring the water environment. Small water bodies include headwater streams, springs, ditches, flushes, small lakes, and ponds, which represent important freshwater resources. However, the relatively narrow and fragmented nature of small water bodies makes it difficult to monitor chlorophyll-a via medium-resolution remote sensing. In the present study, we first fused Gaofen-6 (a new Chinese satellite) images to obtain 2 m resolution images with 8 bands, which was approved as a good data source for Chlorophyll-a monitoring in small water bodies as Sentinel-2. Further, we compared five semi-empirical and four machine learning models to estimate chlorophyll-a concentrations via simulated reflectance using fused Gaofen-6 and Sentinel-2 spectral response function. The results showed that the extreme gradient boosting tree model (one of the machine learning models) is the most accurate. The mean relative error (MRE) was 9.03%, and the root-mean-square error (RMSE) was 4.5 mg/m3 for the Sentinel-2 sensor, while for the fused Gaofen-6 image, MRE was 6.73%, and RMSE was 3.26 mg/m3. Thus, both fused Gaofen-6 and Sentinel-2 could estimate the chlorophyll-a concentrations in small water bodies. Since the fused Gaofen-6 exhibited a higher spatial resolution and Sentinel-2 exhibited a higher temporal resolution.

Performance of Sentinel-2 and Landsat-8 satellites in estimating Chlorophyll-a concentration in a shallow freshwater lake

“…In a recent study on Chl-a concentration of several small water bodies such as rivers, reservoirs, and arti cial ponds China (Shi et al, 2022), the estimation equations for the Sentinel 2 satellite are similar to the present study. Also, Bohn et al (2018) veri ed the NDCI index with an exponential equation for the concentration of Chl-a in high turbid shallow waters, which is similar to the equation obtained for the Sentinel-2 satellite in the present study.…”

“…Moreover, spatial, radiometric, spectral, and temporal resolutions of the sensors can affect performance of satellite measurements (NASA, 2022). These challenges can limit remote sensing applications, especially in small water bodies (Shi et al, 2022). Also, in shallow lakes, the effect of bottom re ection can make errors in the prediction of Chl-a concentration (Allan et al, 2007).…”

“…Landsat-8 OLI/TIRS and Sentinel-2 satellites' images are available since February 2013 and June 2015, respectively. Table 1 illustrates the common bands of both satellites (Toming et al, 2016; Ha et al, 2017; Wagle et al, 2019; Buma & Lee, 2020; Tóth et al, 2021; He et al, 2021;Shi et al, 2022) and their speci cations (USGS, 2022) which are used in the present study to estimate Chl-a concentration. Landsat-8 and Sentinel-2 satellite images were used with a maximum of one day difference with the eld data sets to develop and verify the models.…”

An evidence-based study mapping the decline in freshwater ponds in the Severn Vale catchment in the UK between 1900 and 2019

“…Dörnhöfer and Oppelt, (2016)], however, fewer equivalent tools for small water bodies have been developed [e.g. (Shi et al, 2022)], therefore well-developed manual assessment techniques such as PSYM (Environment Agency and Pond Action, 2002) are more commonly used for ponds. Defining the overall condition of existing ponds would enable a more comprehensive landscape analysis which is key to understanding the vigour of the pondscape.…”

UAV Multispectral Image-Based Urban River Water Quality Monitoring Using Stacked Ensemble Machine Learning Algorithms—A Case Study of the Zhanghe River, China

“…Monitoring of inland water bodies with complex bio-optical characteristics typically requires high-resolution remote sensing images [12,13]. Owing to the low spatial resolution, long return visit period, and susceptibility to interference by clouds, application of satellite images to real-time monitoring of water quality of small water bodies and complex environments such as nearshore waters (affected by mixed pixels) is limited [14,15].…”