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引用本文:焦红波,查勇,李云梅,黄家柱,韦玉春.基于地面实测光谱的太湖水体富营养化水平估算.湖泊科学,2006,18(4):343-348. DOI:10.18307/2006.0404
JIAO Hongbo,ZHA Yong,LI Yunmei,HUANG Jiazhu,WEI Yuchun.Trophic state level monitoring of Lake Taihu based on in situ measurements of hyperspectral reflectance. J. Lake Sci.2006,18(4):343-348. DOI:10.18307/2006.0404
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基于地面实测光谱的太湖水体富营养化水平估算
焦红波, 查勇, 李云梅, 黄家柱, 韦玉春
南京师范大学地理科学学院 南京 210097
摘要:
富营养化指数是评价水体污染情况的一个重要的综合性指标.通过对高光谱遥感数据和水体富营养化指数的分析,确立了反演水体富营养化水平的高光谱敏感波段,进而用选择的敏感波段和波段组合来建立模型.通过对几个模型的比较,选出了较为理想的估算模型.最后对模型进行精度分析,认为该模型具有一定的可靠性和实用性.从而确定了直接由高光谱遥感数据监测水体富营养化水平的可能性,为实现由高光谱遥感数据开展大范围的水质调查奠定了一定的理论基础.
关键词:  太湖  富营养化水平  高光谱遥感
DOI:10.18307/2006.0404
分类号:
基金项目:国家863计划“环境遥感监测软件系统与业务运行示范”(2003AA131060);南京师范大学引进人才科研启动基金资基金“太湖流域水体污染遥感监测研究”(2004105XQ2847)共同资助
Trophic state level monitoring of Lake Taihu based on in situ measurements of hyperspectral reflectance
JIAO Hongbo, ZHA Yong, LI Yunmei, HUANG Jiazhu, WEI Yuchun
Geography science college, Nanjing Normal University, Nanjing 210097, P. R. China
Abstract:
Trophic state index is an important and synthetic standard for estimating the pollution status of water body. It requires large scale field sampling work and complicated indoor chemical analysis involving traditional analytical techniques, as well as complex calculations applying complicated formulas. In this study, through the analysis of the hyperspectral remote sensing data and the water body trophic state level, the remote sensing reflectance and trophic state index of the water body, Lake Taihu, are calculated, The result of correlative analysis, found the hyperspectral sensitive bands to be inverse to the water-body, s trophic state index and sensitive bands and bands, combination (ratio) in established models. The comparative baseline model selected is a power function model TSIC =68. 76χ0.5199, with an independent variable of R717nm. The result, through precision analyses using the other 12 points, found the differences between practice and forecast along half one grading interval, therefore providing reliability and practicability. In conclusion, it is possible to monitor a water-body,s trophic state index directly with hyperspectral remote sensing data and some evidence for the theoretical basis of investigating water quality in a large scope using hyperspectral remote sensing data is justified.
Key words:  Lake Taihu  trophic state level  hyperspectral remote sensing
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