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What is Spatial Auto Correlation

Chapter 160
Encyclopedia of Information Science and Technology, Fourth Edition
The values of a spatial attribute tend to be close to each other and vary gradually from core to periphery of a geographic region.
Published in Chapter:
Neighborhood Rough-Sets-Based Spatial Data Analytics
Sharmila Banu K. (VIT University, India) and B. K. Tripathy (VIT University, India)
Copyright: © 2018 |Pages: 10
DOI: 10.4018/978-1-5225-2255-3.ch160
Abstract
Rough Set Theory partitions a universe using single layered granulation. The equivalence classes induced by rough sets are based on discretised values. Considering the fact that the spatial data are continuous at large, discretising them may cause loss of data. Neighborhood approximations can lead to closely related coverings using continuous values. Besides, the spatial attributes also need to be given due consideration and should be handled unlike non-spatial attributes in the process of dimensionality reduction. This chapter analyses the use of Neighborhood rough sets for continuous data and handling spatially correlated attributes using rough sets.
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