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

Author

Liu, Feng ; Shuai, Yanmin ; Xin, Ding ; Zhu, Qijiang ; Liu, Shuhong ; Zhenkun Tian

Author_Institution

Dept. of Geogr., Beijing Normal Univ., China

Volume

6

fYear

2003

fDate

21-25 July 2003

Firstpage

3679

Abstract

How does one effectively manage spectral data to find information oriented subjects? How does one mine the spectral 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 the structure of a data warehouse and to verify the data mining method using SE590 data obtaining during the field experiment conducted from March to May 2001 in Shunyi, Beijing, China (40°00´-40°18´N, 116°28´-116°58´E).

Keywords

crops; data mining; data warehouses; geophysics computing; tree data structures; vegetation mapping; AD 2001 03 to 05; Beijing; China; SE590 data; Shunyi; crop models; data mining; data organization; data warehouse; hyperspectral data; interrelated matching parameters; mining canopy spectra; tree data structure; tree structure; vegetation spectral simulation; winter wheat; Crops; Data mining; Data warehouses; Databases; Geography; Hyperspectral imaging; Hyperspectral sensors; Remote sensing; Tree data structures; Vegetation;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International

Print_ISBN

0-7803-7929-2

Type

conf

DOI

10.1109/IGARSS.2003.1295235

Filename

1295235