Geographic Information System for Detecting Spatial Connectivity Brown Planthopper Endemic Areas Using a Combination of Triple Exponential Smoothing - Getis Ord

Abstract

This study aims to develop a GIS application to detect the possible formation of brown planthoppers (BPH) (Nilaparvata lugens.Stal) endemic areas based on spatial trend, hierarchical effects and risks areas caused of spatial connectivity in a particular area. The study was conducted through five stages: (1) the collection and preprocessing of research data, (2) database development, (3) the creation of the component class Exponential Smoothing, Weight Metrics and Getis Ord, (4) development of a Early Warning class and GIS applications, and (5) information visualization in the form of graphs, maps and tables. The results show that the software component in this study; the class prediction engine; Getis Ord class and class early detection function optimally generate predictive, endemic regions and early warning information on the period ahead.

Delineation of Nitrate Reduction Hotspots in Artificially Drained Areas through Assessment of Small-Scale Spatial Variability of Electrical Conductivity Data

“…A cluster of these significantly high values may then be regarded as a hot spot. The Getis-Ord Gi* statistics has been widely used in studies pertaining to transportation [47,48], public health [49][50][51], species distributions [52][53][54], etc., but its application for soil studies is still limited, most likely due to the limited availability of spatially dense data such as EC.…”