基于中巴资源卫星数据的森林郁闭度估测研究

Study on the Forest Canopy Density Estimation Based on CBERS Data

森林资源分布具有辽阔性、复杂性、通达性差等特点,而遥感技术具有宏观、动态、便捷、可周期重复和成本低等优点,成为研究森林资源状况的理想手段。目前,在森林遥感应用中,多源遥感数据的提供能力越来越强。但由于遥感信息的综合性、复杂性,遥感信息处理技术相对落后。基于不同区域、不同季相和不同背景特征的森林遥感分类技术远未成熟。利用中巴资源卫星遥感数据,经过图像处理(包括图像的校正、图像的增强和图像的分类等),获取样地的灰度值,结合少量地面实测样地资料,通过线性回归建立森林郁闭度的数学模型,并进行检验以确保估测的精度,为林业生产和建设提供依据。

The distribution of forest resources had characteristics such as extensity, complexity and poor accessibility, but remote sensing techniques had advantages of macroscopic, dynamic, convenience, periodicity and low cost etc and had become the ideal measure to study the forest resources status. At present, in the application of forest remote sensing, the supplying ability of multi-sources remote sensing data was stronger and stronger. But the treatment technique of remote sensing information was relatively backward due to the integration and complexity of remote sensing information. The forest classification technique with remote sensing based on different areas, seasonal aspects and background characteristics was far away from maturity. The gray value of sample land was obtained through image processing （including correction, enhancement and classification of image, etc） by using remote sensing data from CBERS. The mathematical model of forest canopy density was established through linear regression based on combining obtained gray value of sample land with a few sample land data from ground measurement, And the mathematical model was checked to insure the estimation accuracy so as to provide basis for forestry production and construction