Optiliste veetüüpide põhine lähenemine sise- ja rannikuvee veekvaliteedi hindamiseks

Väitekirja elektrooniline versioon ei sisalda publikatsiooneInimestele on meeldinud ajast aega elada seal, kus maa ja vesi kohtuvad. Mistõttu on järvede, jõgede ja rannikualade lähedal inimtegevuse mõju suurenenud, mis omakorda põhjustab veekogude seisundi muutumist ning loob vajaduse veekogude operatiivseks seireks. Enamasti põhinevad veekogude seireprogrammid veekogudes teostatud punktmõõtmistel. See meetod aga ei suuda kajastada kogu veekogu kiiresti muutuvaid omadusi ja reaalset seisundit. Seetõttu on oluline lisaks punktmõõtmistele rakendada veekeskkonna operatiivse jälgimise meetodeid, millest kaugseire on üks võimsamaid. Kaugseire pakub tõhusaid viise veekvaliteedi ruumiliste ja ajaliste erinevuste jälgimiseks. Euroopa Liidu ja Euroopa Kosmoseagentuuri Copernicus programmi raames loodud Sentinel-2 ja Sentinel-3 seeria satelliitide hea ruumilise, ajalise ja spektraalse lahutusega andmete tasuta kättesaadavus on loonud reaalse võimaluse sise- ja rannikuvete seires operatiivselt kasutada täiendavalt satelliitandmeid. Need andmed võimaldavad jälgida kogu veekogu ajalist ja ruumilist muutlikkust ning seirata ka raskesti ligipääsetavaid veekogusid. Sise- ja rannikuveed on optiliselt keerukad, sest vee optilised omadused on mõjutatud sõltumatult erinevate optiliselt aktiivsete ainete poolt. Seetõttu standardsed kaugseire algoritmid veekvaliteedi hindamiseks neis veekogudes tihti ei tööta. Doktoritöö tulemusena tutvustati optiliste veetüüpide põhist lähenemist sise- ja rannikuvete veekvaliteedi parameetrite hindamiseks kaugseireandmete põhjal. Eelnimetatud meetod võtab arvesse vee optilisi omadusi ega piiritle ennast konkreetse veekoguga, seetõttu on tulemused rakendatavad kõigil sarnaste optiliste omadustega veekogudel üle maailma.Humans have long enjoyed living where land and water meet. At the same time, the impact of human activities close to lakes, rivers, and coastal areas has increased, which has caused the deterioration of water bodies. Therefore, the state of a water body requires constant monitoring to assess the magnitude of the impact of human activity and to respond when needed. Traditional water monitoring programs are mainly based on in situ measurements; however, considering that water bodies are dynamic in nature, this method may not reflect the status of the whole water body. Therefore, in addition to traditional monitoring, it is important to implement methods that allow more operative monitoring of the aquatic environment. Remote sensing offers effective ways to observe spatial and temporal variations in water quality. The free availability of data with high spatial, temporal and spectral resolution from the Sentinel-2 and Sentinel-3 family satellites launched under the European Union and the European Space Agency Copernicus programme has created a real opportunity for satellite data being used operationally for additional water quality monitoring for inland and coastal waters. Such waters are optically complex, as they are independently influenced by different optically significant constituents. Therefore, standard remote sensing algorithms to estimate water quality often fail in these waters. As a result of the thesis, an optical water type guided approach to estimate water quality in inland and coastal waters using remote sensing data was presented. The method considers the optical properties of water but does not limit itself to a particular water body. So, results are applicable to all the water bodies with similar optical properties of water.https://www.ester.ee/record=b534022

Validation and Comparison of Water Quality Products in Baltic Lakes Using Sentinel-2 MSI and Sentinel-3 OLCI Data

Inland waters, including lakes, are one of the key points of the carbon cycle. Using remote sensing data in lake monitoring has advantages in both temporal and spatial coverage over traditional in-situ methods that are time consuming and expensive. In this study, we compared two sensors on different Copernicus satellites: Multispectral Instrument (MSI) on Sentinel-2 and Ocean and Land Color Instrument (OLCI) on Sentinel-3 to validate several processors and methods to derive water quality products with best performing atmospheric correction processor applied. For validation we used in-situ data from 49 sampling points across four different lakes, collected during 2018. Level-2 optical water quality products, such as chlorophyll-a and the total suspended matter concentrations, water transparency, and the absorption coefficient of the colored dissolved organic matter were compared against in-situ data. Along with the water quality products, the optical water types were obtained, because in lakes one-method-to-all approach is not working well due to the optical complexity of the inland waters. The dynamics of the optical water types of the two sensors were generally in agreement. In most cases, the band ratio algorithms for both sensors with optical water type guidance gave the best results. The best algorithms to obtain the Level-2 water quality products were different for MSI and OLCI. MSI always outperformed OLCI, with R2 0.84–0.97 for different water quality products. Deriving the water quality parameters with optical water type classification should be the first step in estimating the ecological status of the lakes with remote sensing

Optical Water Type Guided Approach to Estimate Optical Water Quality Parameters

Currently, water monitoring programs are mainly based on in situ measurements; however, this approach is time-consuming, expensive, and may not reflect the status of the whole water body. The availability of Multispectral Imager (MSI) and Ocean and Land Colour Instrument (OLCI) free data with high spectral, spatial, and temporal resolution has increased the potential of adding remote sensing techniques into monitoring programs, leading to improvement of the quality of monitoring water. This study introduced an optical water type guided approach for boreal regions inland and coastal waters to estimate optical water quality parameters, such as the concentration of chlorophyll-a (Chl-a) and total suspended matter (TSM), the absorption coefficient of coloured dissolved organic matter at a wavelength of 442 nm (aCDOM(442)), and the Secchi disk depth, from hyperspectral, OLCI, and MSI reflectance data. This study was based on data from 51 Estonian and Finnish lakes and from the Baltic Sea coastal area, which altogether were used in 415 in situ measurement stations and covered a wide range of optical water quality parameters (Chl-a: 0.5–215.2 mg·m−3; TSM: 0.6–46.0 mg·L−1; aCDOM(442): 0.4–43.7 m−1; and Secchi disk depth: 0.2–12.2 m). For retrieving optical water quality parameters from reflectance spectra, we tested 132 empirical algorithms. The study results describe the best algorithm for each optical water type for each spectral range and for each optical water quality parameter. The correlation was high, from 0.87 up to 0.93, between the in situ measured optical water quality parameters and the parameters predicted by the optical water type guided approach