Data mining about hyperspectral data of winter wheat based on data warehouse and data organization

被引：0

作者：

Liu, F ^{[1
]}

Shuai, YM ^{[1
]}

Xin, D ^{[1
]}

Zhu, QJ ^{[1
]}

Liu, SH ^{[1
]}

Tian, ZK ^{[1
]}

机构：

[1] Beijing Normal Univ, Res Ctr Remote Sensing, Dept Geog, Beijing 100875, Peoples R China

来源：

IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES | 2003年

关键词：

data mining; data warehouse; spectral simulation; dimension table; fact table;

D O I：

暂无

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

How to effectively manage spectrum data to find information oriented subjects? How to mine the spectra data in observation intervals from data in existence? In this paper, a tree data structure, which includes dimension tables and fact tables, is presented to establish the top architecture and tie together the various data tables, for instance, spectrum data and its interrelated matching parameters. A new method on mining canopy spectra in observation intervals is discussed, which is based on certain crop models and the tree structure data warehouse. At last, a case on vegetation spectral simulation is given to test structure of data warehouse and verify data mining method using SE590 data obtaining during the field experiment conducted during the year before last in Shunyi, Beijing, China (40degrees00'-40degrees18', 116degrees28'-116degrees58').

引用

页码：3679 / 3681

页数：3

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