论文标题
3D可视化和空间数据挖掘用于分析LULC图像的
3D Visualization and Spatial Data Mining for Analysis of LULC Images
论文作者
论文摘要
本研究是为在3D可视化中创建一个新工具来创建一个新工具，以分析土地使用土地覆盖（LUCL）图像。这项研究主要使用高分辨率Lulc卫星图像的空间数据挖掘技术。特征空间的可视化允许探索图像数据中的模式以及对分类过程和相关不确定性的见解。视觉数据挖掘为图像分类提供了附加的价值，因为用户可以参与分类过程，从而增加了对结果的信心和理解。在这项研究中，我们提出了图像分割，K-均值聚类和3D可视化工具的原型，用于LUCL卫星图像的视觉数据挖掘（VDM），以供体积可视化。基于体积的表示形式将特征空间划分为球体或体素。可视化工具在Latur区（印度马哈拉施特拉邦）的高分辨率LULC图像的分类研究中显示了可视化工具。
The present study is an attempt made to create a new tool for the analysis of Land Use Land Cover (LUCL) images in 3D visualization. This study mainly uses spatial data mining techniques on high resolution LULC satellite imagery. Visualization of feature space allows exploration of patterns in the image data and insight into the classification process and related uncertainty. Visual Data Mining provides added value to image classifications as the user can be involved in the classification process providing increased confidence in and understanding of the results. In this study, we present a prototype of image segmentation, K-Means clustering and 3D visualization tool for visual data mining (VDM) of LUCL satellite imagery into volume visualization. This volume based representation divides feature space into spheres or voxels. The visualization tool is showcased in a classification study of high-resolution LULC imagery of Latur district (Maharashtra state, India) is used as sample data.
