Abstract
Assessing chlorophyll-a (Chl-a) pigments in complex inland water systems is of key importance as this parameter constitutes a major ecosystem integrity indicator. In this study, a methodological framework is proposed for quantifying Chl-a pigments using Earth observation (EO) data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and 8 Operational Land Imager (OLI) sensors. The first step of the methodology involves the implementation of stepwise multiple regression (MLR) analysis of the available Chl-a dataset. Then, principal component analysis (PCA) is performed to explore Greek lakes’ potential interrelationships based on their Chl-a values in conjunction with certain criteria: their characteristics (artificial/natural), typology, and climatic type. Additionally, parameters such as seasonal water sampling and the date difference between sampling and satellite overpass are taken into consideration. Next, is implemented a stepwise multiple regression analysis among different groups of cases, formed by the criteria indicated from the PCA itself. This effort aimed at exploring different remote sensing-derived Chl-a algorithms for various types of lakes. The practical use of the proposed approach was evaluated in a total of 50 lake water bodies (natural and artificial) from 2013–2018, constituting the National Lake Network Monitoring of Greece in the context of the Water Framework Directive (WFD). All in all, the results evidenced the suitability of Landsat data when used with the proposed technique to estimate log-transformed Chl-a. The proposed scheme resulted in the development of models separately for natural (R = 0.78; RMSE = 1.3 μg/L) and artificial lakes (R = 0.76; RMSE = 1.29 μg/L), while the model developed without criteria proved weaker (R = 0.65; RMSE = 1.85 μg/L) in comparison to the other ones examined. The methodological framework proposed herein can be used as a useful resource toward a continuous monitoring and assessment of lake water quality, supporting sustainable water resources management.
Highlights
Accumulating passive exploitation of natural resources, improper land-use practices, and irregular development activities in lake basins undermine various significant functions of water resources [1]
In purview of the above, this study proposes a methodological framework that aims to provide Chl-a in Case 2 complex inland waters of Greece by generating accurate quantitative models with Earth observation (EO) data from the Landsat 7 ETM+ and 8 Operational Land Imager (OLI) satellite series
A methodological framework was proposed for quantifying Chl-a pigments using Earth observation (EO) data from Landsat 7 ETM+ and 8 OLI sensors
Summary
Accumulating passive exploitation of natural resources, improper land-use practices, and irregular development activities in lake basins undermine various significant functions of water resources [1]. One of the most significant aspects for the sustainable management of water bodies—lakes in particular—is the constant monitoring of their quality, as well as of their watersheds [3]. In situ monitoring provides high accuracy, it is a time-consuming procedure, and it cannot ensure a simultaneous water quality dataset on a regional or greater scale [3,4,5]. Traditional point sampling methods are not capable of detecting the spatial or temporal variations in water quality, as required in extensive assessment and management of water bodies. The combined use of Earth observation (EO) and geographical information systems (GIS) allows monitoring in an efficient and robust way lake parameters over variable spatial scales, including lakes that are otherwise inaccessible [6,7]
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