Mapping inland water carbon content with Landsat 8 data

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.     

Retrieval of water quality from airborne imaging spectrometry of various lake types in different seasons

The suitability of the AISA airborne imaging spectrometer for monitoring lake water quality was tested in four surveys carried out in southern Finland in 1996-1998. Altogether, 11 lakes were surveyed and the total number of stations with concurrent remote sensing and limnological measurements was 127. The ranges of the water quality variables were: the sum of chlorophyll a and phaeophytin a 1-100 microg l(-1), turbidity 0.4-26 FNU, total suspended solids 0.7-32 mg l(-1), absorption coefficient of aquatic humus at 400 nm 1.2-14 m(-1) and secchi disc transparency 0.4-7 m. For the retrieval analyses, 24 AISA channels in the 450-786 nm range with a channel width of 6-14 nm were used. The agreement between estimated and observed water quality variables was generally good and R2 for the best algorithms was in the range of 0.72-0.90 over the whole dataset. The channels used for May were, in most cases, the same as those for August, but the empirical parameters of the algorithms were different. After seasonal grouping, R2 varied from 0.84 to 0.95. The use of apparent reflectance instead of radiance improved the estimation of water quality in the case of total suspended solids and turbidity. In the most humic lake, the empirical algorithms tested were suitable only for the interpretation of total suspended solids and turbidity.     

Passive optical remote sensing of cyanobacteria and other intense phytoplankton blooms in coastal and inland waters

Increased frequency and extent of potentially harmful blooms in coastal and inland waters world-wide require the development of methods for operative and reliable monitoring of the blooms over vast coastal areas and a large number of lakes. Remote sensing could provide the tool. An overview of the literature in this field suggests that operative monitoring of the extent of some types of blooms (i.e. cyanobacteria) is relatively straightforward. Operative monitoring of inland waters is currently limited to larger lakes or using airborne and hand-held remote sensing instruments as there are no satellite sensors with sufficient spatial resolution to provide daily coverage. Extremely high spatial and vertical variability in biomass during blooms of some phytoplankton species and the strong effects of this on the remote sensing signal suggest that water sampling techniques and strategies have to be redesigned for highly stratified bloom conditions, especially if the samples are collected for algorithm development and validation of remote sensing data. Comparing spectral signatures of different bloom-forming species with the spectral resolution available in most satellites and taking into account variability in optical properties of different water bodies suggests that developing global algorithms for recognizing and quantitative mapping of (harmful) algal blooms is questionable. On the other hand some authors cited in the present paper have found particular cases where satellites with coarse spectral and spatial resolution can be used to recognize phytoplankton blooms even at species level. Thus, the algorithms and methods to be used depend on the optical complexity of the water to which they will be applied. The aim of this paper is to summarize different methods and algorithms available in an attempt to assist in selecting the most appropriate method for a particular site and problem under investigation.     

Mapping coloured dissolved organic matter concentration in coastal waters

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.     

A sun glint correction method for hyperspectral imagery containing areas with non-negligible water leaving NIR signal

Present sun glint removal methods overcorrect data collected in very shallow (less than 2 m) waters if the sensors used do not have bands in far infrared part of the spectrum. The reason is assuming of zero water leaving signal at near infrared (NIR) wavelengths. This assumption is not valid in very shallow waters, but also in areas where aquatic vegetation reaches water surface and in case of phytoplankton blooms that reach very high biomass or form surface scum. We propose an alternative method that can be used for successful glint removal even if the sensor does not have spectral bands beyond 800 nm. The proposed method utilises the presence and depth of the oxygen absorption feature near 760 nm as an indicator of glint contamination. This method allows removing sun glint from hyperspectral imagery preserving shape and magnitude of reflectance spectra in the cases where the negligible water leaving NIR signal is not valid.     

Estimation of the water quality of the Baltic Sea and lakes in Estonia and Finland by passive optical remote sensing measurements on board vessel

In the years 1993, 1995 and 1996, passive optical remote sensing measurements taken on board ships or boats were carried out at 16 lakes in Estonia and five lakes in Finland, and also in some regions of the Baltic Sea. Simultaneously, the Secchi disk depth was measured and water samples were taken, from which chlorophyll a and suspended matter concentrations were determined in the laboratory. Using an Hitachi spectrophotometer, the attenuation coefficient spectra for filtered and unfiltered water were obtained, and the effective amount of yellow substance was estimated. The properties of the waters under consideration varied within rather wide limits, the Secchi disk depth changing from 0.4 to 8.5 m, chlorophyll concentration from 0.65 to 45 mg m^?3 and the effective amount of yellow substance from 1.8 to 32 mg L^?1. Applying the correlation method for interpretation of the optical remote sensing data, we derived algorithms for estimating the water properties in the Estonian and Finnish lakes and in the Baltic Sea. The correlation coefficients between remote sensing and other water characteristics are in the limits |r| = 0.61-0.84. This shows that despite difficulties caused by a small thickness of the‘informative’water layer and shadowing of the influence of some substance on the remote sensing spectrum by other substances in turbid, multicomponent waters, the passive optical remote sensing method is applicable for estimating the water transparency and quality in lakes and inland seas. However, the method is not suitable for (i) determining the value of a very small amount of some substance in the water if the concentrations of other optically active substances are remarkably higher or for (ii) investigating the water-bodies with a large amount of yellow substance, where extremely strong absorption of light in the water leads to an‘abnormal’shape of the remote sensing reflectance spectra. Our results confirm also that remote sensing algorithms derived for the open ocean waters are in most cases not applicable for lakes and inland seas.     

Obtaining steel powders from ball-bearing production wastes

Summary After filing operations, wastes are obtained at ball-bearing plants in the form of partially oxidized steel powder, which can be used for manufacturing parts by powder metallurgy methods. The modes of reduction of the steel powder and its basic properties are discussed.