An index for quantifying geometric point disorder in geospatial applications

Many techniques have been developed to quantify different conceptualizations of self-interaction and patterns within spatial data. We propose a new metric related algorithm that describes the geometric disorder geographic point sets, “Index Disorder” (IoD). The IoD was applied synthetic natural datasets shown be able differentiate between areas high (randomly placed points) low (e.g., curvilinear grids, wallpaper groups, other repeating patterns). Because is quantitative metric, it can used on its own as an aid for identifying unusually or enrichment machine learning classification algorithms. • locational structure in data additional dimension analysis. Anthropogenic structures are ordered compared organically occurring structures. Index Disorder (IoD) quantifies this so-called disorder. anthrophonic naturally any arbitrary set points quantified by comparing relative positions point's neighbors neighbors' neighbors.