Analyzing the Application of Spatial Statistics in Modeling Geographic and Environmental Data Correlations
Posted: Dec 28, 2022
Abstract
The analysis of geographic and environmental data presents unique challenges due to the inherent spatial dependencies that violate the assumption of independence central to many statistical methods. Spatial statistics has emerged as a critical discipline for understanding these complex relationships, yet traditional approaches often struggle with the non-stationary and multi-scale nature of environmental phenomena. This research addresses these limitations by developing an innovative hybrid methodology that integrates classical spatial statistics with contemporary machine learning techniques.
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