DocumentCode :
2783801
Title :
A study on decision tree classification method of land use/land cover -Taking tree counties in Hebei Province as an example
Author :
Ping Wang ; Ji-xian Zhang ; Wei-jie Jia ; Zong-jian Lin
Author_Institution :
Shandong Univ. of Sci. & Technol., Qingdao
fYear :
2008
fDate :
June 30 2008-July 2 2008
Firstpage :
1
Lastpage :
5
Abstract :
Adopting the decision tree technology, utilizing its process pattern that imitates human judgment and thinking and fault-tolerance features, the authors developed a decision tree classification method. Initially utilizing SPOT and TM, the work effectively enhanced LULC information and established the synthetic database; then, combining geoscience synthetic analysis with ground spectral feature information, utilizing the CART system; the authors built the decision tree model that is based on the decision rules. At last, we discussed the wild use of LULC decision tree classified and stratified extractive technology. Taking three counties in Hebei province as examples, we divided the research area to classify each unit (county area) by ecological division, utilized multiple data resources and geoscience rules to build the decision tree model and test and verify the method. The results demonstrated that the method improves the speed and precision of classification.
Keywords :
decision trees; geophysical techniques; image classification; vegetation mapping; CART system; China; Hebei Province; LULC information; SPOT data; TM data; decision tree classification; fault-tolerance feature; ground spectral feature information; land cover classification; land use classification; Biological system modeling; Classification tree analysis; Data mining; Decision trees; Fault tolerance; Geoscience; Humans; Information analysis; Spatial databases; Spectral analysis; LULC; decision model; decision tree; sub-district;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Earth Observation and Remote Sensing Applications, 2008. EORSA 2008. International Workshop on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2393-4
Electronic_ISBN :
978-1-4244-2394-1
Type :
conf
DOI :
10.1109/EORSA.2008.4620331
Filename :
4620331
Link To Document :
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