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遥感数据参数反演估计南京紫金山缺失小班蓄积量方法研究
引用本文:吴翼,李明阳.遥感数据参数反演估计南京紫金山缺失小班蓄积量方法研究[J].林业调查规划,2008,33(1):1-3.
作者姓名:吴翼  李明阳
作者单位:南京林业大学森林资源与环境学院,江苏,南京,210037
摘    要:如何对早期小班调查蓄积量缺失的数据进行修补,是进行森林资源动态分析急需解决的一个问题.以南京紫金山1988年森林经理调查数据和同期TM遥感数据为信息源,利用遥感生物参数反演技术,根据已知小班的光谱特征和蓄积量之间的相关关系,在建立蓄积量生物参数反演经验模型的基础上,对缺失小班蓄积量进行修补.研究表明:通过遥感数据生物参数反演进行缺失小班蓄积量数据修补的方法得到的小班蓄积量数据可靠性比较高,这种方法在森林资源调查和规划实践中具有较大的应用价值.

关 键 词:小班蓄积量  遥感数据  参数反演  缺失小班  估算模型  南京紫金山
文章编号:1671-3168(2008)01-0001-03
修稿时间:2007年11月19

Study on Method for Inverse Deduction of Remote Sensing Parameter to Estimate Omissive Subcompartment Stock Volume
WU Yi,LI Ming-yang.Study on Method for Inverse Deduction of Remote Sensing Parameter to Estimate Omissive Subcompartment Stock Volume[J].Forest Inventory and Planning,2008,33(1):1-3.
Authors:WU Yi  LI Ming-yang
Abstract:How to repair the omissive data of stock volume in early period of subcompartment survey is a question which is urgent to be solved in dynamic analysis of forest resource.Taking the forest management data and TM remote sensing data of Zijinshan in Nanjing in 1988 as information source,the study tried to repair the omissive subcompartments' stock volume on the basis of inverse deduction model of biological parameter and interrelation between spectrum feature and stock volume.The result showed the subcompartments' stock volume data obtained with this method is much reliable.The method has of a great value in application and practice of forest resource inventory and planning.
Keywords:subcompartment's stock volume  remote sensing data  inverse deduction with parameter  omissive subcompartment  estimate model  Zijinshan in Nanjing
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