人工神经网络在森林资源管理中的应用

Application of Aartificial Neural Network in Forest Resource Management

传统的数量方法难以解决森林资源管理中的更多的非结构性问题。人工智能新技术能将人类积累的知识传输到决策支持系统中 ,作为人工智能的一个分支 ,人工神经网络已经成为一个在传统统计方法之外 ,十分引人注目的新方法 ,并开始用于预测生物系统中的非线性行为。文中从人工神经网络在森林立地分类和制图 ,森林生长和动态模拟、空间数据的分析和拟合、植物病虫害动态的预测及气候变化研究等方面的应用进行综合评述。并对人工神经网络在应用中的优缺点 ,存在的问题和局限性 。

Making good decisions for adaptive forest management has become increasingly difficult. New artificial intelligence (AI) technology allows knowledge processing to be included in decision support system. The application of Artificial Neural Network(ANN) to date synthesis of the use of ANN in forest resource management. Current ANN applications include: (1) forest land mapping and classification, (2) forest growth and dynamics modelling,(3) spatial data analysis and modelling,(4) plant disease dynamics modelling, and (5) climate change research. The advantages and disadvantages of using ANN are discussed. Although the ANN applications are at an early stage, they have demonstrated potential as a useful tool for forest resource management. As a specific example of an ANN dealing with forest ecosystem mapping, the paper will present an application of a three layer back propagation neural network to calibrate the non linear relationships between biome scores and climate variables, which can improve the accuracy of mapping terrestrial biomass from pollen data.