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基于ETM+影像监测的蓝藻水华时空分布特征

发表时间:2014-11-15  浏览量:1867  下载量:675
全部作者: 张晓忆,景元书,简单
作者单位: 南京信息工程大学应用气象学院,江苏省农业气象灾害重点实验室,气象灾害预报和评估协同创新中心
摘 要: 蓝藻水华引起的水环境问题越来越受到人们的关注,实现水域蓝藻水华的快速动态监测成为湖泊水质保护亟待解决的问题。由2010年8景巢湖水域ETM+遥感影像,选取改进的归一化差异水体指数(modified normalized difference water index,MNDWI)以精确提取湖区水体信息,采用归一化植被指数(normalized difference vegetation index,NDVI)模型与湖面水温反演模型对巢湖水体的蓝藻动态信息进行快速监测和预测。在此基础上揭示了巢湖水华的年变化规律,给出了2010年8幅水华分布示意图,从而为湖泊水污染的治理和水环境的改善提供决策依据。
关 键 词: 水域生态学;蓝藻水华;改进的归一化差异水体指数;归一化植被指数;水面温度反演算法
Title: Monitoring for temporal and spatial distribution of blue-green algae based on ETM+image
Author: ZHANG Xiaoyi, JING Yuanshu, JIAN Dan
Organization: Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Najing University of Information Science and Technology
Abstract: The monitoring of Cyanobacteria blooms has been on the focus of environment protection jobs. There often have inconvenience in the measurement and poor comprehensive converge problem during the daily monitoring. In this paper, based on eight sceneries of ETM+ remote sensing images of Chao lake in 2010, the modified normalized difference water index (MNDWI) was used to abstract the accurate information of lake. The normalized difference vegetation index (NDVI) model and the inversion model of lake water temperature were established for rapid monitoring and predictions of algae information in Chao lake. Finally, the annual characteristics blooms provided decision basis for the protection department of water by summarizing the change regularity of Chao blooms in 2010.
Key words: aquatic ecology; Cyanobacteria blooms; modified normalized difference water index; normalized difference vegetation index; lake surface temperature inversion algorithm
发表期数: 2014年11月第21期
引用格式: 张晓忆,景元书,简单. 基于ETM+影像监测的蓝藻水华时空分布特征[J]. 中国科技论文在线精品论文,2014,7(21):2206-2213.
 
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