1) covering classification algorithm
覆盖分类
1.
In order to analyze feature information of remote sensing image efficiently,a new approach based on the quotient space theory and covering classification algorithm is introduced.
为了快速分析遥感图像特征信息,结合覆盖分类算法提出了一种商空间理论方法,其中灵活运用商空间理论的分解方法和合成技术来指导遥感图像信息的提取和整合,覆盖算法能快速精确地挖掘出有限信息的本质,为分类提取提供保障。
2) Land cover classification
土地覆盖分类
1.
Land cover classification in Xianghai Nature Reserve.;
向海自然保护区土地覆盖分类研究
2.
Optimized BP neural network classifier based on genetic algorithm for land cover classification using remotely-sensed data;
基于遗传算法优化的BP神经网络遥感数据土地覆盖分类
3.
The authors studied the regional land cover classification based on MODIS time-series data.
该文采用M OD IS N DV I时序数据对东北区土地覆盖分类进行研究,以验证M OD IS区域土地覆盖制图的可靠性。
3) classification of land cover
土地覆盖分类
1.
This paper explores the application of Fuzzy ARTMAP neural network in classification of land cover.
以TM影像为实例,探讨了FuzzyARTMAP神经网络在土地覆盖分类方面的应用。
2.
Linear Spectral Unmixing(LSU) could extract endmembers such as canopy or other objects at pixel level,but the accuracy of LSU which is presently used in multispectral and relatively broad spectral range data is not available to quantitative research,so an improved technique for LSU which is based on the classification of land cover was employed in this study.
鉴于此,本文提出了一种改进的线性光谱分离方法,该方法在对影像进行土地覆盖分类基础上进行分离,一方面同类土地覆盖类型内同种地物的光谱变异相对较小,更有利于端元选取;另一方面,分影像的地物种类数量明显少于整幅影像,更容易满足模型的适用条件,从而突破了波段数量限制,同时使地物光谱分离更具针对性,经过验证,该方法较传统分离方法相比植被覆盖度的反演精度可提高6。
4) Land cover investigation
陆地覆盖分类
5) precover class
预覆盖类
6) covering clustering
覆盖聚类
1.
A new clustering algorithm,covering clustering algorithm is put forward in this paper.
在此分析基础上,提出一种新的聚类算法———覆盖聚类算法,该算法采用覆盖的概念将比较集中的样本聚合在一起,从而发现隐含在样本集中的类,对于周围稀疏的样本结合最短距离法,获得聚类效果,并用实验数据对分层聚类方法、LBG方法与覆盖聚类算法进行比较,证明了覆盖聚类算法的可行性和有效性。
补充资料：土地利用类型(见土地利用分类)
土地利用类型(见土地利用分类)
type of land use
tudi Iiyong Ieixing土地利用类型(t月祀oflanduse)见土地利用分类。
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