摘要
洪泛区是地球上最丰富生物栖息地之一,具有很高保育价值。由于其分布广、具有季节性河水泛滥特点,难以通过短期监测方法进行获取,可通过系统地分析流域内水文观测站的日流量信息,选取洪水期和枯水期Landsat卫星影像,作为洪泛区分析的影像分析源。该文依据洪泛区域在近红外和中红外的光谱特征和地形特点,建立多时相洪泛区分析模型,通过非监督分类方法及子类分类进行洪泛区信息提取。实践证明,该模型是一种比较经济、可靠和高效的洪泛区信息提取方法。
Floodplain is one of the richest habitats on earth with a high conservation value.Because of its wide distribution and seasonal flooding characteristics,it is difficult to identify floodplain through short-term monitoring methods.By systematic analysis on daily flow gages data in the watershed,this paper selected a pair of representative high flow and low flow Landsat satellite images as data source.Based on floodplain spectral characteristics in the near-infrared and mid-infrared band,combined with its topographic features,it used unsupervised classification method and sub-unsupervised classification to extract floodplain information.The practice has proved that the model is more economical,reliable and efficient for floodplain identification.
出处
《遥感信息》
CSCD
北大核心
2015年第3期74-79,共6页
Remote Sensing Information
