Abstract
Abstract. Spatial distribution of chlorophyll-a (chla) concentration in Lake Taihu is non-uniform and seasonal variability. Chla concentration retrieval algorithms were separately established using measured data and remote sensing images (HJ-1 CCD and MODIS data) in October 2010, March 2011, and September 2011. Then parameters of semi- variance were calculated on the scale of 30m, 250m and 500m for analyzing spatial heterogeneity in different seasons. Finally, based on the definitions of Lumped chla (chlaL) and Distributed chla (chlaD), seasonal model of chla concentration scale error was built. The results indicated that: spatial distribution of chla concentration in spring was more uniform. In summer and autumn, chla concentration in the north of the lake such as Meiliang Bay and Zhushan Bay was higher than that in the south of Lake Taihu. Chla concentration on different scales showed the similar structure in the same season, while it had different structure in different seasons. And inversion chla concentration from MODIS 500m had a greater scale error. The spatial scale error changed with seasons. It was higher in summer and autumn than that in spring. The maximum relative error can achieve 23%.
Highlights
Chlorophyll-a plays a significant role in water ecosystem
Spatial scale effect and uncertainty based on remote sensing images had been studied domestic and abroad
The results showed that the MODIS R1-R2, R1/R2, (R1 -R2) / (R1 + R2) and HJ-1 H3-H4, H3/H4 had a high correlation with chla concentration
Summary
Chlorophyll-a (chla) plays a significant role in water ecosystem. It is a basic indicator of lake eutrophication (Zhou et al, 2009). Spatial heterogeneity could cause scale effect in the retrieval of chla concentration from multi-resolution remote sensing images (Bao et al, 2011). It brings scale error (Chen et al, 2010). Researches usually provided variogram function for studying spatial heterogeneity and spatial effect of water quality parameters They found that spatial distribution of chla concentration exist structure (Xia et al, 2011; Liu et al, 2002). As there is no sensor for inland water quality remote sensing, land satellites and ocean colour satellite were used to estimate chla concentration (Zhou et al, 2009) Both of the data souses and spatial heterogeneity of chla concentration can affect the retrieval accuracy. The paper analyzed seasonal results which were calculated in different spatial scales
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