GRASS-News Geographic Resources Analysis Support System Volume 3, June 2005 Editorial proaches on the GRASS user inferface. These articles outline pretty well some capabili- by Martin Wegmann ties of GRASS but far more functions could be pre- sented, personally I would like to see the actual use Dear GRASS user, of GRASS functions in different projects and a more detailed presentation of GRASS visualisation poten- tials. welcome to the third volume of GRASSNews which features a broad spectrum of articles. Looking forward to No 4, with kind regards Preprocessing of SRTM data and its further use in GRASS is the topic of the first two articles. Followed Martin Wegmann by GRASS- R articles describing the new GRASS 6 - R interface and the use of R for raster manipulation. Moreover r.infer is presented, a tool for Martin Wegmann knowledge management, this shall be the begin- DRL - German Aerospace Centre @ ning of a series featuring different approaches on Remote Sensing and Biodiversity Unit knowledge management in GRASS. Dept. of Geography, University of Würzburg, Germany A very promising preview of QGIS 0.7 including BIOTA-Project the new capabilities to interact with GRASS and the ¢¡£¡¥¤§¦£¨£¨ ©£©£© ¢ ¡ presentation of the GRASS extension manager (GEM) ¢¡£¡¥¤§¦£¨£¨ ©£©£© ¢ ! " ¢ in the News section shows the two parallel ap- #%$&'()£)+*£,.-¢/!01$)2£34!' 564£)¢/!7!#£4%$3£1-£43£&85¥9$ Contents of this volume: Use of R tightly coupled to GRASS for correc- tion of single-detector errors in EO1 hyper- spectral images . 16 Editorial . 1 Knowledge Management and GRASS GIS: SRTM and VMAP0 data in OGR and GRASS . 2 r.infer . 19 Mapping freely available high resolution Quantum GIS . 21 global elevation and vector data in GRASS . 7 News . 23 Interfacing GRASS 6 and : . 11 Recent and Upcoming Events . 25 GRASS-News Vol. 3, June 2005 SRTM and VMAP0 data in OGR and GRASS SRTM data acquisition There are (at least) two possibilities to acquire SRTM by Markus Neteler raw data tiles: 1. Original tiles at 0.00083333 deg (3 arc-seconds, Abstract around 90m) resolution from NASA FTP site (NASA SRTM Website, 2004). Interestingly, Years ago, hunting for free geospatial data was rather these files irregularly disappear or are shifted challenging. Today elevation data sets with an al- to another FTP site. The file format is “hgt” most global coverage at high resolution are available with zip compression which corresponds to from the Shuttle Radar Topography Mission (SRTM a BIL (band interleave by line) file without data set). Also a global set of vector maps at 1:1 mil- header file. Instead of having a header, the lion scale is available. Combined, both data sets pro- spatial reference is coded into the file name. vide a base cartography for most parts of the world. SRTM file name coordinates refer to the center The technical issues for SRTM raster data are void of the lower left pixel. To generate a BIL header, filling, peak elimination and coastline extraction. To this coordinate pair has to be transformed to use the VMAP0 vector data, the user must deal with the center of the upper left pixel. While GRASS its unusual data format. In this article the prepara- also refers to cell centers, the GDAL library tional steps for using these data sets are described. ( ¢¡£¡¥¤§¦©¨£¨ £ § ¢£ £¢¨ ) which is used to read the raw SRTM data refers to pixel corners. The tile size is one degree by one degree. 2. Probably more convenient are the larger SRTM SRTM elevation data tiles from (Global Land Cover Facility (GLCF; GLCF SRTM Website (2004)) which have been The Shuttle Radar Topography Mission (SRTM) is patched to WRS2 size in oder to match LAND- based on single-pass radar interferometry, for which SAT scene positions and sizes. Here the format two radar antennas were mounted onto the Space is GeoTIFF. Shuttle to simultaneously take two images from slightly different locations. One antenna was in- SRTM data preparation and import into board, the other at the end of a 60 meter mast. The GRASS sent radar signal was reflected back and received by both the main and outboard antennas. First of all, a latitude-longitude location with WGS84 SRTM data are distributed at different resolutions ellipsoid and geodetic datum is needed. If you don't depending on the part of the world in which you have it, such a location can be easily generated from are interested. Within the U.S.A. these data are de- either the startup screen (use the EPSG code button livered at nominally 30 meters horizontal resolution in GRASS 6 and enter “4326” as code number along (pixel size). For the rest of the world they are dis- with a new location name) or from within an existing tributed at 90 meters resolution. The vertical pre- location (such as the Spearfish sample location) with cision is estimated as around 10 meters mean error. following command: The horizontal datum is the World Geodetic System ! #"!$% ! '&(*),+ -/.¥-'0(!1'¥2'34&!5687*):9!$<;<0-8'.(9!;<0 98'. 1984 (WGS84). The vertical datum is mean sea level as defined by the Earth Gravitational Model geoid The import of the SRTM data into this location (EGM96 geoid model (1996)). Users commonly ig- then depends on the data source: nore the original vertical datum and use SRTM data HGT files from NASA: Use the = />8?§ A@!£¡ B script to as referenced to the WGS84 ellipsoid as geoid models import a SRTM , ¢£¡= CD>8¤ file. The script takes are mostly unavailable in GIS. A test for the Trentino care of the relevant referencing and also auto- (Northern Italy) province has shown that the devia- matically applies a color table. tions between the EGM96 geoid undulation and the WGS84 ellipsoid are for this area within the submeter GeoTIFF file from GLCF: Use E />8?E ¢¢¢ to import range which is beyond the vertical error of the SRTM a SRTM GeoTIFF file. Additionally, the NULL data. (No Data) value has to be assigned afterward ISSN 1614-8746 2 GRASS-News Vol. 3, June 2005 "§#$ (%!&7 ¤&& ¡ with E ,? , otherwise the map won't be prop- " #$ ;!2'0(§' "' erly visible. Finally, you can assign a nice color 418 -8'. "§#$ "§#$ . 1 - ( < 2)' +*0(§' ,¥1;'..- £¢¢ ¥ @ ¤ ¤¥ @§¦ @£¡ B table with E (e.g., ). 180( (;/1< ;<1 2!-!01!(!5 "§#$ "§#$ . 1 - ( < 2)' +*0(§' 2 0 1 11/.- Note, that you can easily zoom to a couple of ad- 180( ( 2'0 111/ 2!-+0!1!(!5 E ¨¥¥*> ? "§#$ jacent tiles with as it accepts multiple raster "§#$ ,£;'$8;!9$.2' 43-89<0(-+365;+2758' "9- "§#$ "§#$ , 1; .¡:9; 6<<' 2'0 1 1!1/ - files. ' "§#$ "§#$ ' , 1; . ' :2 " #$ "§#$ <' =3-<9<0 ;2'0!(§' Void filling $8!98<2 Part of the post-processing is the filling of “no data” holes in many of the SRTM data tiles. These voids ap- The differences can be calculated by subtract- pear in regions with rugged terrain due to the SAR ing the filtered from the original map and visu- (SAR, Side Aperture Radar) data acquisition tech- alized in NVIZ for graphical inspection. nique which was used to generate the SRTM data. Higher mountains shadow the radar signal which using r.resamp.rst: this module can be used to re- leads to holes in the DEM resulting from the interfer- sample the SRTM data to higher resolution, e.g. ometry. Another reason for voids are water bodies to match a pan-sharpened LANDSAT-7 scene © > *@¢>?§ ?>¢¢ with poor reflectance of the RADAR signal. (pan-sharpen with ¥A@ ). It uses © the regularized splines with tension (RST) in- > ?¡ £¢@ The E script usually does an accept- able job at filling these holes. It extracts a ring of terpolation method. Peaks will be smoothed and also data voids will be closed: values around the holes, then it interpolates the val- ues across the holes using the regularized splines "§#$ "§#$ 4 2'0B' 1981/!(§' C&A& 6 D£E- with tension (RST) interpolation method (see the 41 2<; .¥2<(A&A&,6 D 1F (¤&A& ,6 D 01<.2!-8'. (A& © A@ ¢ D@¡ manual for details). Then the closed " #$ 418 -8'. ;!2'0(§' C&A&6 D "' holes are patched into the original data. The un- "§#$ .§/-+0)' G&A& 6 D derlying idea is to leave as many values as possi- ble untouched during the void filling. An example is shown in Fig. 1 and Fig. 2. You can experiment with the tension parameter ¨¥ @!B ¤E D@¡ An alternative is E which we use be- to minimize the “stair” artifacts in the resulting low to resample the SRTM DEM to higher resolution. map. Further details to optimize the interpola- tion are given in Cebecauer et al. (2002). Peaks elimination Besides holes, peaks and outliers also appear in the Coastline extraction SRTM data. They are often artifacts of the interfer- ometry processing. If you intend to use the SRTM The coastlines are not well indicated in SRTM data data just for visualization or rendering, the use of because of the limited Radar backscatter over wa- some simple filters may be sufficient. But to make ter. To some extent this also applies to lakes and a hydrologically sound elevation model, more com- snow/ice. plex steps must be performed. There are at least two free vector map prod- While outlier detection and removal techniques ucts which can be used to solve this problem: the are virtually unlimited, we propose here just some Global, Self-consistent, Hierarchical, High-resolution simple examples. It is probably convenient to repro- Shoreline database (GSHHS; GSHHS vector data set ¡ ject the data set(s) to a metric projection first ( = ,¤¢ (2004)) and the VMAP0 vector data (see next section). ¥¥D> ? within the target location; using /><?§ along Currently original GSHHS data cannot be im- ¤¢ ¡ with can be helpful to “find” the area of in- ported into GRASS 6 (only into GRASS 5 with ¢ ? ¥¥ ¡ terest): A>8?§ D@8 £ *@ ) but by using it can be con- verted from an existing GRASS 5 location.