空间数据采掘是一个很有发展前景的领域，其中空间数据分类的研究尚处在起步阶段。
Spatial data mining is a promising field, where the research work on spatial data classification is still in its initial stage.
对地图生产中的多源数据利用作了较为全面的研究，包括资料分类、数据获取方法和数据处理方法。把各种资料数据统一在一个应用平台上，保证了地图和空间数据的现势性；
Study application methods of the multi-sources data in map production, including sort of sources, data collection, and data processing, in order to updating the map and spatial data in one platform.
在对城市景观主要建模对象进行分类的基础上，建立了三维空间数据结构，实现了地形和地物模型三维重建的系列算法。
Based on the classification of the primary modeling objects in the city scene, we separately rebuild the model of the terrain and objects according to the 3d spatial data structure.
但仅用传统分类算法对高光谱图像分类，会导致分类精度降低、空间数据冗余和资源的极大浪费。
However, classifying hyperspectral images only with traditional classification algorithms will result in low classification precision, data redundancy and great waste of resource.
但仅用传统分类算法对高光谱图像分类，会导致分类精度降低、空间数据冗余和资源的极大浪费。
However, classifying hyperspectral images only with traditional classification algorithms will result in low classification precision, data redundancy and great waste of resource.
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