Estimation of area burned by forest fires in Mediterranean countries: A remote sensing data mining perspective

2011 ◽  
Vol 262 (8) ◽  
pp. 1597-1607 ◽  
Author(s):  
Carmen Quintano ◽  
Alfonso Fernández-Manso ◽  
Alfred Stein ◽  
Wietske Bijker
Keyword(s):  
Remote Sensing ◽  
Data Mining ◽  
Forest Fires ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Area Burned ◽  
Mediterranean Countries

Application of the Parallel Spatial Association Rule in Remote Sensing Data Mining

2012 ◽  
Vol 500 ◽  
pp. 598-602
Author(s):  
Jun Ma ◽  
Dong Dong Zhang
Keyword(s):  
Remote Sensing ◽  
Data Mining ◽  
Association Rule ◽  
Spatial Association ◽  
Remote Sensing Data ◽  
Inner Product ◽  
Data Mining Algorithm ◽  
Sensing Data ◽  
The Common ◽  
Frequent Item Sets

Since the remote sensing data are multi-resources and massive, the common data mining algorithm cannot effectively discover the knowledge what people want to know. However, spatial association rule can solve the problem of inefficiency in remote sensing data mining. This paper gives an algorithm to compute the frequent item sets though a method like calculating vectors inner-product. And the algorithm will introduce pruning in the whole running. It reduces the time and resources consumption effectively

scholarly journals Risk prediction of forest fires based on the Remote sensing data

2014 ◽  
Vol 6 (29) ◽  
pp. 170
Author(s):  
Olga Vladimirovna Brovkina ◽  
Frantisek Zemek
Keyword(s):  
Remote Sensing ◽  
Risk Prediction ◽  
Forest Fires ◽  
Remote Sensing Data ◽  
Sensing Data

Preliminary research in using the technology of data mining to analyze remote sensing data

2003 ◽  
Author(s):  
Xiongfei Zhang ◽  
Xing Li ◽  
Xia Zhang ◽  
Qingxi Tong ◽  
Wei Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Mining ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Preliminary Research
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