@Article{10798587.2016.1267237,
AUTHOR = {Zhiquan Huang, Yu Fu, Fuchu Dai},
TITLE = {Study for Multi-Resources Spatial Data Fusion Methods in Big Data Environment},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {24},
YEAR = {2018},
NUMBER = {1},
PAGES = {29--34},
URL = {http://www.techscience.com/iasc/v24n1/39721},
ISSN = {2326-005X},
ABSTRACT = {The rapid development and extensive application of geographic information system (GIS) and the 
advent of the age of big data bring about the generation of multi-resources spatial data, which makes 
data integration and fusion share more difficult due to the differences on data source, data accuracy 
and data modal. Meanwhile, study for multi-resources spatial data fusion methods has an important 
practical significance for reducing the production cost of geographic data, accelerating the updating 
speed of existing geographical information and improving the quality of GIS big data. To expound the 
formation and developing trends of multi-resources spatial data fusion methods systematically, and 
on the basis of referring to lots of related technical documents both at home and abroad, this paper 
makes a conclusion and discussion about multi-resources spatial data fusion methods, and foresees 
the prospects of data fusion in big data environment, which has certain reference value for the related 
research work.},
DOI = {10.1080/10798587.2016.1267237}
}