1) TWINSPAN classification software
TWINSPAN植被分类
2) TWINSPAN classification
TWINSPAN分类
1.
Based on the results of TWINSPAN classification, 60 quadrats of C.
通过TWINSPAN分类,将青冈栎群落60个样方划分为8个群丛类型,探讨了各群丛类型的基本特征。
2.
TWINSPAN classification results showed that the subalpine vegetation could be divided into bush and meadowland large groupings, including 8 community types, which are distributed at different altitudes, from 2 500 m to 2 755 m.
应用数量分类(TWINSPAN)和DCA排序方法,对关帝山灌丛草甸群落进行了多元分析,TWINSPAN分类结果表明,该地区亚高山植被可分为灌丛群落、草甸群落2大类,包括8个群落类型,分别位于不同的海拔高度。
3.
The TWINSPAN classification and DCA ordination were employed for the quantitative analysis of the shrub layer and herbage layer under different stands.
TWINSPAN分类将灌木层和草本层分别分为14个类型和10个类型,分类的结果与林分类型之间存在着较好的对应关系。
3) TWINSPAN
TWINSPAN分类
1.
Using heavy metals content data,we analyzed the pattern of heavy metals and its influencing factor by TWINSPAN and CCA.
根据江苏省农用地22个标准样地的7种重金属元素含量测定结果,应用TWINSPAN分类、CCA排序的多元统计方法,对江苏农用地耕作层土壤重金属元素含量格局和影响因子进行了定量分析。
2.
By using the niche breadth,niche overlap,and TWINSPAN,DCA,The gradual change of the dominant species niche in the process of vegetation restoration,the role of the dominant species in communities and the relationships of communities have been studied.
通过生态位宽度与生态位重叠指数 ,结合 TWINSPAN分类与 DCA排序 ,研究植被恢复过程中优势种生态位的梯度变化 ,以及这些种在不同群落类型中的地位、各群落之间的关系 。
4) TWINSPAN quantitative classification
TWINSPAN数量分类
5) vegetation classification
植被分类
1.
Forest vegetation classification of TM images using artificial neural network;
人工神经网络在遥感图像森林植被分类中的应用
2.
This paper used Nanjing city as the research object for vegetation classification based on IKONOS image.
以南京市区的植被覆盖为研究对象,基于IKONOS遥感影像,采用决策树分类算法,根据各种植被光谱特征建立知识库,提出基于光谱信息的植被分类方法,继而结合高分辨率影像特有的纹理特征引进局部一致性指数对该方法进行改进,提出结合纹理信息的高分辨率遥感植被分类方法,分类总体精度从仅利用光谱信息的83。
6) city's vegetation classification
城市植被分类
补充资料：[3-(aminosulfonyl)-4-chloro-N-(2.3-dihydro-2-methyl-1H-indol-1-yl)benzamide]
分子式：C16H16ClN3O3S
分子量：365.5
CAS号：26807-65-8
性质：暂无
制备方法：暂无
用途：用于轻、中度原发性高血压。
分子量：365.5
CAS号：26807-65-8
性质：暂无
制备方法：暂无
用途：用于轻、中度原发性高血压。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条