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The first is a bounding box, a matrix of numerical coordinates with column names c(‘min’, ‘max’), and at least two rows, with the first row eastings (x-axis) and the second northings (y-axis). Most often the bounding box is generated automatically from the data in subclasses of Spatial. character(NA)), its default value. Operations on Spatial* objects should update or copy these values to the new Spatial* objects being created. We can use getClass to return the complete definition of a class, including its slot names and the types of their contents: > library(sp) > getClass("Spatial") Class "Spatial" [package "sp"] Slots: Name: Class: Known Class Class Class Class Class Class Class Class Class Class bbox proj4string matrix CRS Subclasses: "SpatialPoints", directly "SpatialGrid", directly "SpatialLines", directly "SpatialPolygons", directly "SpatialPointsDataFrame", by class "SpatialPoints", distance 2 "SpatialPixels", by class "SpatialPoints", distance 2 "SpatialGridDataFrame", by class "SpatialGrid", distance 2 "SpatialLinesDataFrame", by class "SpatialLines", distance 2 "SpatialPixelsDataFrame", by class "SpatialPoints", distance 3 "SpatialPolygonsDataFrame", by class "SpatialPolygons", distance 2 As we see, getClass also returns known subclasses, showing the classes that include the Spatial class in their definitions.

Remote sensing satellites continue to make great contributions to earth observation, with multi-spectral images supplementing visible wavelengths. The Shuttle Radar Topography Mission (SRTM) in February 2000 has provided elevation data for much of the earth. Other satellite-borne sensor technologies are now vital for timely storm warnings, amongst other things. These complement terrestrial networks monitoring, for example, lightning strikes and the movement of precipitation systems by radar. Surveying in the field has largely been replaced by aerial photogrammetry, mapping using air photographs usually exposed in pairs of stereo images.

Ripley (1988) supplements and extends the earlier work, and is worth careful attention. The comprehensive text by Cressie (1993) is referred to very widely; careful reading of the often very short passages of relevance to a research problem can be highly rewarding. Schabenberger and Gotway (2005) cover much of the same material, incorporating advances made over the intervening period. Banerjee et al. (2004) 6 Reprinted in 2004. 14 1 Hello World : Introducing Spatial Data show how the Bayesian approach to statistics can be used in applied spatial data analysis.

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