黑龙江省森林空间自相关分析

Spatial Autocorrelation Analysis of Forests in Heilongjiang Province

运用空间自相关和自回归模型对黑龙江省森林空间分布的聚集性和相关性进行研究。结果表明:黑龙江省森林及其人文、地貌、气候等影响因子具有明显的空间正自相关;与经典回归模型相比,空间滞后模型模拟的效果是最优的;对于空间自相关关系显著的地区利用空间滞后模型,而对于空间自相关不显著的地区利用经典回归模型模拟的效果会更好一些。

A study was conducted on the spatial correlation of the forests in Heilongjiang Province by spatial autocorrelation analysis and spatial autoregressive model. Results show that the forest and its related physiognomy and climate show significandy positive spatial autocorrelation. Spatial lag model is better than the traditional multiple linear regression models. Spatial lag model is fit for the area with significant spatial autocorrelation, and the traditional multiple linear regression models are suitable for the area without significant spatial autocorrelation.