A MODIS satellite high-precision monitoring method for chlorophyll-a in eutrophic lake water

Abstract

The invention provides a high-precision satellite MODIS (Moderate-resolution Imaging Spectroradiometer) monitoring method for chlorophyll a of a eutrophic lake water body. The method comprises the following steps: screening a chlorophyll a evaluation index (NDBI) which is sensitive to the concentration change of the chlorophyll a and is not influenced by high suspended solids; obtaining a quantitative relation between the NDBI and the concentration of the chlorophyll a on the basis of biological optical model simulation; combining spectral information of the water body and the corresponding concentration of the chlorophyll a of the water body monitored in the field in Chaohu Lake in year 2013-2014, so as to obtain a chlorophyll a inversion algorithm based on a ground measured spectrum (Rrs) and the NDBI; simulating different aerosol types and thicknesses, different solar altitudes, satellite observation angles and azimuth angles, so as to obtain a quantitative relation between the ground monitored remote sensing reflectance (Rrs) and simulated Rrc subjected to Rayleigh scattering correction; and further extending the chlorophyll a inversion algorithm based on ground measured spectral data to satellite image data subjected to the Rayleigh scattering correction. According to the method, the inter-annual and inter-monthly change rules and space distribution of the rules of the concentration of the chlorophyll a of a eutrophic lake can be accurately obtained.

Description

technical field [0001] The invention relates to a MODIS satellite high-precision monitoring method for chlorophyll-a in eutrophic lake water. Background technique [0002] Remote sensing technology is widely used to monitor water eutrophication and algal blooms, which has greatly improved the real-time monitoring ability of water quality (Matthews, 2010; Odermatt et al., 2012). Chlorophyll a (Chla, μg / L) is an important indicator of algal bloom intensity and water nutrient status, and has become the most common parameter in water quality remote sensing (Chaeffer et al., 2012; Matthews, 2010; Qi et al., 2014). In recent years, due to the frequent occurrence of algal blooms, there has been a serious threat to the quality of drinking water and irrigation water (Duan et al., 2009; Guo, 2007), and the use of remote sensing to monitor water body chlorophyll a has quickly become a research hotspot (Paerl & Huisman, 2008; Paerl & Huisman, 2009; Matthews, 2010; Odermatt et al., 2012...

AI Technical Summary

Problems solved by technology

First, the existing MODIS Chla algorithm (such as OC2, OC3, OC4 and OCI, etc.) is not suitable for highly turbid eutrophic water; The water area is saturated, and there is almost no data available. Therefore, we can only use the unsaturated land wide-band algorithm to invert Chla; finally, there is currently no reliable atmospheric correction method to help MODIS obtain the Rrs data of inland turbid lakes (full and accurate atmospherically corrected data)

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