论文部分内容阅读
对小的生态经济区开展自然资源统计是很困难的,政府决策人员只能依靠州水平的数据库来评价一定区域或局部的自然资源(森林、牧场、草地、农田等)状况。小面积评估技术可以用于评定这些资源。然而,哪一种小面积估测法可以给出最可靠、最准确的结果还不得而知。本研究检测了小面积评估分析常用的两种方法(即综合估计法和回归估计法)的可靠性、准确性。运用这两种方法分析墨西哥哈里斯科(Jalisco)州全州的自然资源数据,从而检测每种方法对所选择的森林林分结构特征预测结果的好坏。研究表明,回归方法在多个地理尺度上,对森林林分结构特征预测的可靠性和准确性均最好。因此,推荐州或地方资源管理者,在没有其他适当的辅助信息资料的情况下,可运用回归分析法来评估小区域内自然资源状况。
It is very difficult to conduct statistics on natural resources in small eco-economic zones. Government policymakers can only rely on state-level databases to evaluate the status of natural resources (forests, pastures, grasslands, farmland, etc.) in certain regions or regions. Small area assessment techniques can be used to assess these resources. However, it is not known which small area estimation method can give the most reliable and accurate result. This study examined the reliability and accuracy of the two commonly used methods for small area assessment (ie, synthetic and regressive estimation methods). Both methods are used to analyze natural state data from the statewide state of Jalisco, Mexico, to examine how well each method predicts the structural characteristics of the selected forest stand. The research shows that the regression method has the best reliability and accuracy in predicting the structural characteristics of forest stand on multiple geographical scales. Therefore, it is recommended that state or local resource managers use regression analysis to assess the status of natural resources in a small area without other appropriate supporting information.