Framework for Multi-Sources Spatial Data Integration Analysis

被引：0
|
作者：
Wang, Ping [3 ]
Huang, Fang [3 ]
Guan, Li [2 ]
Liu, Xiangnan [1 ]
机构：
[1] China Univ Geosci, Sch Informat Engn, Beijing, Peoples R China
[2] Peking Univ, Inst Remote Sensing & GIS, Beijing, Peoples R China
[3] Northeast Normal Univ, Coll Urban & Environm Sci, Changchun, Peoples R China
来源：
2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8 | 2006年
基金：
美国国家科学基金会;
关键词：
multiple sources data; integration; data assimilation geographical analysis;
D O I：
10.1109/IGARSS.2006.717
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
Importance of integrating multi-sources spatial data is widely acknowledged. It is indispensable especially for interdisciplinary projects. This paper brings forward the framework for multi-sources spatial data integration analysis. Types, sources and other issues of the spatial data are discussed, which can bring potential advantages after integration, and data integration issues are summarized. The multiple sources spatial data integration methods are analyzed in detail. Taking land use change study in Changling County as example, the difference between two data sets is analyzed.. And through the linkage of semantics LUT and spectral LUT, the originally incomparable data sets become comparable, and the real change can be found out more accurately.
引用
收藏
页码：2788 / +
页数：2
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