柴达木盆地植被覆盖度的分析与模拟——空间自相关方法的运用(英文)

Relationship between vegetation and environmental factors has always been a major topic in ecology, but it has also been an important way to reveal vegetation’s dynamic response to and feedback effects on climate change. For the special geographical location and climatic characteristics of the Qaidam Basin, with the support of traditional and remote sensing data, in this paper a vegetation coverage model was established. The quantitative prediction of vegetation coverage by five environmental factors was initially realized through multiple stepwise regression (MSR) models. However, there is significant multicollinearity among these five environmental factors, which reduces the performance of the MSR model. Then through the introduction of the Moran Index, an indicator that reflects the spatial auto-correlation of vegetation distribution, only two variables of average annual rainfall and local Moran Index were used in the final establishment of the vegetation coverage model. The results show that there is significant spatial autocorrelation in the distribution of vegetation. The role of spatial autocorrelation in the establishment of vegetation coverage model has not only improved the model fitting R2 from 0.608 to 0.656, but also removed the multicollinearity among independents.     

森林湿地遥感信息提取方法研究现状

森林湿地是湿地的重要组成部分,因其群落结构复杂,从景观尺度上对其进行识别是湿地研究的难点之一。在分析国内外相关科学文献的基础上,从地理生态环境、影像特征及影像信息处理单元角度分析了森林湿地遥感信息提取方法的研究现状,总结了当前森林湿地遥感提取的特点,并在此基础上初步预测未来森林湿地遥感信息提取方法的发展趋势。结果表明:以水文特征反演为依据,认为基于地理生态环境的提取方法包括基于水文地貌学方法、基于光学遥感和微波遥感的分类方法;基于影像特征提取方法包括基于雷达散射特征决策树、随机森林决策树及航片目视解译法;基于影像信息处理单元角度方法主要有基于像元和对象分类2种方法。