This article gives a brief overview of classical spatial statistics. Three main types of spatial data are considered: geostatistical data, lattice data, and spatial point patterns. Modeling themes common to all three data types are emphasized. In addition, some basic structural identification procedures for each data type are described. Finally, maximum likelihood estimation and spatial predict...

In this study, the weighted distance method, which combines the cumulative sum method and the inverse distance, is devised for monitoring spatial patterns of point events around fixed points. It is found the weighted-distance approach can better reveal the cluster scale and is less subject to observations far away from the monitor site than the distance-based method developed by Rogerson and Su...

Spatial patterns of pathogen inoculum in field soils and the resulting patterns of disease may reflect the underlying mechanisms of pathogen dispersal. This knowledge can be used to design more efficient sampling schemes for assessing diseases. Spatial patterns of Verticillium dahliae microsclerotia were characterized in commercial cotton fields through quadrat and point sampling in 1994 and 20...

A spatial point process is a random pattern of points in d-dimensional space (where usually d = 2 or d = 3 in applications). Spatial point processes are useful as statistical models in the analysis of observed patterns of points, where the points represent the locations of some object of study (e..g. trees in a forest, bird nests, disease cases, or petty crimes). Point processes play a special ...

Understanding spatial controls on wildfires is important when designing adaptive fire management plans and optimizing fuel treatment locations on a forest landscape. Previous research about this topic focused primarily on spatial controls for fire origin locations alone. Fire spread and behavior were largely overlooked. This paper contrasts the relative importance of biotic, abiotic, and anthro...

Persistent Scatterer Interferometry (PSI) has been widely used for landslide studies in recent years. This paper investigated the spatial patterns of PSI point targets and landslide occurrences in the Arno River basin in Central Italy. The main purpose is to analyze whether spatial patterns of Persistent Scatterers (PS) can be recognized as indicators of landslide occurrences throughout the who...

the complexity of urban systems in our recent world, make it difficult to evaluation and explanation of their changes with traditional and customarily methods. in the past, remote sensing has shown an ability to detect and describe urban growth patterns at different spatial scales. with new remote sensing devices (e.g. ikonos), with innovative image processing techniques and with further develo...

BACKGROUND AND AIMS Characterization of spatial patterns of plant disease can provide insights into important epidemiological processes such as sources of inoculum, mechanisms of dissemination, and reproductive strategies of the pathogen population. Whilst two-dimensional patterns of disease (among plants within fields) have been studied extensively, there is limited information on three-dimens...