Graphics Programs Reference
In-Depth Information
7 Spatial Data
7.1 Types of Spatial Data
Most data in earth sciences are spatially distributed, either as vector data,
(points, lines, polygons) or as raster data (gridded topography). Vector data
are generated by digitizing map objects such as drainage networks or out-
lines of lithologic units. Raster data can be obtained directly from a satellite
sensor output, but in most cases grid data can be interpolated from irregu-
larly-distributed samples from the field (
gridding
).
The following chapter introduces the use of vector data by using coast-
line data as an example (Chapter 7.2). Subsequently, the acquisition and
handling of raster data is illustrated with help of digital topography data
(Chapters 7.3 to 7.5). The availability and use of digital elevation data has
increased considerably since the early 90·s. With 5 arc minutes resolution,
the ETOPO5 was one of the fi rst data sets for topography and bathymetry.
In October 2001, it was replaced by the ETOPO2 that has a resolution of 2
arc minutes. In addition, there is a data set for topography called GTOPO30
completed in 1996 that has a horizontal grid spacing of 30 arc seconds (ap-
proximately 1 km). Most recently, the 30 and 90 m resolution data from the
Shuttle Radar Topography Mission (SRTM) have replaced the older data
sets in most scientifi c studies.
The second part of the chapter deals with surface estimates from irregular-
spaced data (Chapters 7.6 to 7.9). In earth sciences, most data are collected
in an irregular pattern. Access to sample rocks is often restricted to natural
outcrops such as shoreline cliffs and the walls of a gorge, or anthropogenic
outcrops such as road cuts and quarries. Clustered and traversed data is a
challenge for all gridding techniques. The corresponding chapters illustrate
the use of the most important gridding routines and outline the potential
pitfalls while using these methods.
This chapter requires the Mapping Toolbox although most graphics rou-
tines used in our examples can be easily replaced by standard MATLAB func-
