An efficient query strategy for integrated remote sensing and inventory (spatial) databases

Ranga Raju Vatsavai, T. Burk, S. Shekhar, M. Hansen
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引用次数: 1

Abstract

The integration of disparate heterogeneous spatial databases for extending queries is a challenging task. The authors present a novel framework, based on a k-nearest neighbor (kNN) algorithm, for integrating remote sensing imagery with Forest Inventory Analysis (FIA) sample point/plot data managed in a relational database system. We then demonstrate how queries to this system may be extended over any arbitrary region of interest in a Web based geographical information system. To build the integrated database, spectral signatures are collected at FIA plot locations from the Landsat TM image. A plot-id image is produced by assigning each pixel to the closest FIA plot in multi-dimensional spectral space. The resulting image provides an interface to the Forest Inventory Analysis Data-Base (FIADB) and allows generalizations of the estimates for any user defined query window or region of interest (ROI). This methodology, along with geostatistical analysis, is integrated into a client/server Web based geographical information system, which provides Internet users with an easy to use query interface for the FIADB and spatial databases.
遥感与库存(空间)集成数据库的高效查询策略
集成异构空间数据库以扩展查询是一项具有挑战性的任务。作者提出了一种基于k近邻(kNN)算法的框架,用于在关系数据库系统中管理遥感图像与森林清查分析(FIA)样本点/样地数据的集成。然后,我们将演示如何将对该系统的查询扩展到基于Web的地理信息系统中感兴趣的任意区域。为了建立综合数据库,从Landsat TM图像中收集FIA地块位置的光谱特征。通过将每个像素分配给多维光谱空间中最接近的FIA图来生成plot-id图像。生成的图像为森林清查分析数据库(FIADB)提供了一个接口,并允许对任何用户定义的查询窗口或感兴趣的区域(ROI)进行概化估计。这种方法与地理统计分析一起集成到一个基于客户端/服务器Web的地理信息系统中,该系统为Internet用户提供了一个易于使用的FIADB和空间数据库查询界面。
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