摘要
By analyzing the enhanced thematic mapper (ETM) images of September 1999, and quality observation data for many consecutive years in several parts of the Donghu Lake in Wuhan, China, the authors discovered a good linear relation between grey scale (GS) abstracted from ETM b5, b7 images and eutrophication level of the lakes, and extended the study to eight other major lakes in the area of Wu- han by using lake eutrophication models. Based on the in situ monitoring data, we also evaluated the eu- trophication level of the lakes with modified trophic index method brought by M. Aizaki et al. The results of the two methods showed that the most of the lakes were eutrophicated, and even hyper-eutrophicated in some areas. Six of the 8 lakes had very similar trophic state index (TSI) values. Although two of them differed in TSI value, but within an order, while it was different largely from the one by traditional method. The difference of the results between the two methods might have been due to three causative reasons. First, remote sensing technology reflects the overall status of a certain area corresponding to the ETM images in a certain period, but the modified TSI reflects the annual average values of the monitoring spots. Second, the time the ETM images taken is later than that of in situ data. Third, ETM images are affected by clouds, water depth, and suspended matter. In short, remote sensing result agreed greatly with the in situ monitoring data, indicating that remote sensing technology is feasible and effective for moni- toring and evaluating the lake eutrophication in the Wuhan area and it also can be used to evaluate large-scope lake eutrophication.
By analyzing the enhanced thematic mapper （ETM） images of September 1999, and quality observation data for many consecutive years in several parts of the Donghu Lake in Wuhan, China, the authors discovered a good linear relation between grey scale （GS） abstracted from ETM b5, b7 images and eutrophication level of the lakes, and extended the study to eight other major lakes in the area of Wuhan by using lake eutrophication models. Based on the in situ monitoring data, we also evaluated the eutrophication level of the lakes with modified trophic index method brought by M. Aizaki et al. The results of the two methods showed that the most of the lakes were eutrophicated, and even hyper-eutrophicated in some areas. Six of the 8 lakes had very similar trophic state index （TSI） values. Although two of them differed in TSI value, but within an order, while it was different largely from the one by traditional method. The difference of the results between the two methods might have been due to three causative reasons. First, remote sensing technology reflects the overall status of a certain area corresponding to the ETM images in a certain period, but the modified TSI reflects the annual average values of the monitoring spots. Second, the time the ETM images taken is later than that of in situ data. Third, ETM images are affected by clouds, water depth, and suspended matter. In short, remote sensing result agreed greatly with the in situ monitoring data, indicating that remote sensing technology is feasible and effective for monitoring and evaluating the lake eutrophication in the Wuhan area and it also can be used to evaluate large-scope lake eutrophication.
基金
Supported by Hubei Provincial Comprehensive Investigation of Land Resources Using Remote Sensing Technology Program (No. 0799210014).
