Application of spatial statistical analysis in monitoring cow endemic fluorosis based on GIS

作者：Li Lin; Yang Yong^*; Dong Jing

来源：Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(10): 185-188.

DOI：10.3969/j.issn.1002-6819.2012.10.029

• Endemic fluorosis
• Limited data
• Monitoring methods
• Prediction model
• Spatial characteristics
• Spatial statistics

In the monitoring of animal epidemics, the amount of monitoring spots is few and the monitored data limited. Therefore, how to use the limited data to show the general spatial distribution of animal epidemics is the key to build efficient spatial monitoring method. In this paper the GEODA and ArcGIS were used to analyze the endemic fluorosis spatial distribution of district No. A based on the spatial characteristic of the density of cow endemic fluorosis in district No. A, and a prediction model to estimate the cow endemic fluorosis distribution was established. Compared with the true actual distribution, the prediction model had better results in prediction effect. Moreover, the space statistics-related prediction model provides a reference for space-related animal epidemics.

• 出版日期2012