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From ASCII files to orthophotos : the processing of high resolution aerial survey data using open source GIS software
| Content Provider | Semantic Scholar |
|---|---|
| Author | Stevenson, John Alford Mitchell, Neil C. Pinkerton, Harry |
| Copyright Year | 2009 |
| Abstract | High quality maps are an important tool in volcanology. In August 2007 the NERC Airborne Research and Survey Facility (ARSF) mapped the Nesjavellir region in Iceland's Western Volcanic Zone. LiDAR, aerial photos and multispectral infrared data were collected with the purpose of surveying the Nesjahraun, a lava flow that was erupted there approximately 2000 years ago and which exhibits complex and varied surface textures. To allow maximum flexibility for the end user, only low-level processing was carried out by NERC. The remaining processing was carried out using open source tools, mainly GRASS, GMT, GDAL and gstat to generate higher level products. The command-line interface of these tools allows tight integration with standard textand filemanipulation tools that are built into the GNU/Linux operating system and lends itself easily to the creation of scripts for the batch processing of multiple files. The LiDAR data were provided as 6.5 Gb of ASCII text containing information on the location and intensity of each laser return. A preliminary DEM was prepared by binning the data onto a 10 m grid in GRASS. For more detailed work, the LiDAR points were interpolated onto a 1 m grid by kriging using the gstat software in combination with GRASS. This high-resolution DEM was used to orthorectify the aerial photos and multispectral infrared data by providing both ground control points and a topographic model. The rectified photos were formatted for printing in GMT to produce hard-copy maps while false-colour composite images were made by combining different bands of the multispectral infrared data in GRASS. GRASS was also used to digitise roads and other features from the orthophotos and to plot measurements made in the field. Conversion of the format and projection via the GDAL software allows visualisation of much of the data in Google EarthTM. The article outlines the GRASS modules and other software tools used to generate high-level datasets from ARSF data, as a workflow template. It also demonstrates that open source software is a viable and cost-effective alternative to proprietary software in analysis of GIS data. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.geos.ed.ac.uk/~jsteven5/blog/GRASS_remote_sensing_article.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
