Two new tools for aggregation and geoprocessing of raw spatial data

Abstract

The journey to successful data analysis is vulnerable to loss of accuracy at several key steps in its progression. Thus the ease of understanding the results and strength of insight into a work’s implications depends on special care being taken at all opportunities. If a dataset is too large for a computer software system to handle, data and resolution will need to be sacrificed in the name of practicality. If the tools to process the data do not exist, then only a crude superficial analysis can ever be conducted. In this paper I present two new data import tools written for the Free and Open Source GRASS GIS software. The first module, r.in.xyz, has been designed for processing massive point cloud datasets, for example raw LIDAR or multibeam sonar swath data. Data is binned into a raster map using a variety of univariate statistical methods. The module has proven to be extremely fast, even when faced with datasets of many dozens of gigabytes. Data may be fed directly into the program from the output source and there is no known limit to the number of input points. The second module, i.warp, was designed to convert twisted analogue imagery into a highly spatially accurate raster GIS layer with minimal loss of information using thin plate spline warping. Raw sea floor imagery printed to paper rolls on a historic sidescan sonar survey was successful resurrected into a useful map of nearshore reefs. The workflow takes advantage of the existing GIS user interfaces for applying ground control points and the module is run as a slot-in replacement for the standard 2nd and 3rd order georectification modules. Examples for both modules are given for studies undertaken in the waters off the Otago coast.