The researchers studied the water quality in Lake Taihu, China, to understand how different factors like chlorophyll-a, total suspended matter, and dissolved organic carbon vary across the lake. They used geostatistics and fractal dimension methods to analyze the spatial patterns. They found that chlorophyll-a and total suspended matter had strong spatial structures, while dissolved organic carbon was more influenced by random factors. The size of the sampling unit and the resolution of remote sensing images were important for accurate retrieval of water quality information. The study suggested that using smaller units and higher resolution images could improve the precision of water quality measurements in Lake Taihu.