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Dive into the research topics where Birgot Paavel is active.

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Featured researches published by Birgot Paavel.


Remote Sensing | 2016

Remote Sensing of Black Lakes and Using 810 nm Reflectance Peak for Retrieving Water Quality Parameters of Optically Complex Waters

Tiit Kutser; Birgot Paavel; Charles Verpoorter; Martin Ligi; Tuuli Soomets; Kaire Toming; Gema Casal

Many lakes in boreal and arctic regions have high concentrations of CDOM (coloured dissolved organic matter). Remote sensing of such lakes is complicated due to very low water leaving signals. Ther ...


International Journal of Remote Sensing | 2009

Mapping coloured dissolved organic matter concentration in coastal waters

Tiit Kutser; Birgot Paavel; Liisa Metsamaa; Ele Vahtmäe

Optical properties of the Baltic Sea are dominated by coloured dissolved organic matter (CDOM). High concentration of CDOM is probably one of the reasons why standard chlorophyll-retrieval algorithms fail badly in the Baltic Sea. Our aim was to test can CDOM be mapped by remote sensing instruments in coastal waters of relatively CDOM-rich environments like the Baltic Sea. The results show that sensors with high radiometric resolution, such as Advanced Land Imager (ALI), can be used for mapping CDOM in a wide concentration range. The ALI image also showed that optical properties of coastal waters are extremely variable. CDOM concentration may vary 4–5-fold in two adjacent 30 m pixels. This indicates a need for relatively high spatial resolution (30 m or less) remote sensing data in monitoring coastal environments.


Journal of remote sensing | 2016

Mapping inland water carbon content with Landsat 8 data

Tiit Kutser; Gema Casal Pascual; Claudio Clemente Faria Barbosa; Birgot Paavel; Renato Ferreira; Lino Augusto Sander de Carvalho; Kaire Toming

ABSTRACT Landsat 8 is the first Earth observation satellite with sufficient radiometric and spatial resolution to allow global mapping of lake CDOM and DOC (coloured dissolved organic matter and dissolved organic carbon, respectively) content. Landsat 8 is a multispectral sensor however, the number of potentially usable band ratios, or more sophisticated indices, is limited. In order to test the suitability of the ratio most commonly used in lake carbon content mapping, the green–red band ratio, we carried out fieldwork in Estonian and Brazilian lakes. Several atmospheric correction methods were also tested in order to use image data where the image-to-image variability due to illumination conditions would be minimal. None of the four atmospheric correction methods tested, produced reflectance spectra that matched well with in situ measured reflectance. Nevertheless, the green–red band ratio calculated from the reflectance data was in correlation with measured CDOM values. In situ data show that there is a strong correlation between CDOM and DOC concentrations in Estonian and Brazilian lakes. Thus, mapping the global CDOM and DOC content from Landsat 8 is plausible but more data from different parts of the world are needed before decisions can be made about the accuracy of such global estimation.


Remote Sensing | 2017

Mapping Water Quality Parameters with Sentinel-3 Ocean and Land Colour Instrument Imagery in the Baltic Sea

Kaire Toming; Tiit Kutser; Rivo Uiboupin; Age Arikas; Kaimo Vahter; Birgot Paavel

The launch of Ocean and Land Colour Instrument (OLCI) on board Sentinel-3A in 2016 is the beginning of a new era in long time, continuous, high frequency water quality monitoring of coastal waters. ...


Bio-optical Modeling and Remote Sensing of Inland Waters | 2017

Bio-optical Modeling of Colored Dissolved Organic Matter

Tiit Kutser; Sampsa Koponen; Kari Kallio; Tonio Fincke; Birgot Paavel

Recent studies indicate that inland waters play a very important role in the global carbon cycle. Inland water bodies are the main source of drinking water in many parts of the world and important resource for aquaculture and tourism. Neither determining the true role of lakes in the global carbon cycle nor monitoring lake water quality in real time are possible without using remote sensing. The optically active part of carbon that can be detected by remote sensing is colored dissolved organic matter (CDOM). This chapter discusses the importance of carbon in inland waters, its optical properties, and the performance of different empirical and model based approaches in retrieval of the amount of CDOM.


Fourth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2016) | 2016

Assessment of chlorophyll-a concentration in the Gulf of Riga using hyperspectral airborne and simulated Sentinel-3 OLCI data

Dainis Jakovels; Agris Brauns; Jevgenijs Filipovs; Juris Taskovs; Dagnija Fedorovicha; Birgot Paavel; Martin Ligi; Tiit Kutser

Remote sensing has proved to be an accurate and reliable tool in clear water environments like oceans or the Mediterranean Sea. However, the current algorithms and methods usually fail on optically complex waters like coastal and inland waters. The whole Baltic Sea can be considered as optically complex coastal waters. Remote assessment of water quality parameters (eg., chlorophyll-a concentration) is of interest for monitoring of marine environment, but hasn’t been used as a routine approach in Latvia. In this study, two simultaneous hyperspectral airborne data and in situ measurement campaigns were performed in the Gulf of Riga near the River Daugava mouth in summer 2015 to simulate Sentinel-3 data and test existing algorithms for retrieval of Level 2 Water products. Comparison of historical data showed poor overall correlation between in situ measurements and MERIS chlorophyll-a data products. Better correlation between spectral chl-a data products and in situ water sampling measurements was achieved during simultaneous airborne and field campaign resulting in R2 up to 0.94 for field spectral data, R2 of 0.78 for airborne data. Test of all two band ratio combinations showed that R2 could be improved from 0.63 to 0.94 for hyperspectral airborne data choosing 712 and 728 nm bands instead of 709 and 666 nm, and R2 could be improved from 0.61 to 0.83 for simulated Sentinel-3 OLCI data choosing Oa10 and Oa8 bands instead of Oa11 and Oa8. Repeated campaigns are planned during spring and summer blooms 2016 in the Gulf of Riga to get larger data set for validation and evaluate repeatability. The main challenges remain to acquire as good data as possible within rapidly changing environment and often cloudy weather conditions.


Remote Sensing of Environment | 2013

Removing glint effects from field radiometry data measured in optically complex coastal and inland waters

Tiit Kutser; Ele Vahtmäe; Birgot Paavel; Tuuli Kauer


Remote Sensing of Environment | 2015

Estimating lake carbon fractions from remote sensing data

Tiit Kutser; Charles Verpoorter; Birgot Paavel; Lars J. Tranvik


Archive | 2009

Spatial and temporal variations in coloured dissolved organic matter in large and shallow Estonian waterbodies

Kaire Toming; Helgi Arst; Birgot Paavel; Alo Laas; Tiina Nõges


Boreal Environment Research | 2009

Field measurements of spectral backscattering coefficient of the Baltic Sea and boreal lakes

Tiit Kutser; Marian Hiire; Liisa Metsamaa; Ele Vahtmäe; Birgot Paavel; Robert Aps

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Helgi Arst

Marine Institute of Memorial University of Newfoundland

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Tiina Nõges

Estonian University of Life Sciences

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Anu Reinart

Marine Institute of Memorial University of Newfoundland

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