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GIS na GNU/Linux-u Darko Boto APIS IT d.o.o . GIS analiti膷ar CLI Geoproccesing GDAL/OGR

Sadr啪aj : Uvod O radionici Povijest FLOSS GIS-a Anatomija FLOSS GIS-a 艩to je GIS?听 Projekcije Prostorni podaci CLI geoprocesiranje - GDAL/OGR sa primjerima听 Pode拧avanje PostGIS baze PostGIS SQL upiti sa primjerima i skriptama Pregled alata WEB GIS

O radionici OSGeo VM - Linux distribucija bazirana na Ubuntu-u http://wiki.osgeo.org/wiki/Live_GIS_Disc Arramagong - http://www.arramagong.com/Arramagong Predinstaliran SW isklju膷ivo pod pokroviteljstvom OSGeo听fondacije (http://www.osgeo.org)

WEB arhitekture? Desktop alati? Osnove GIS-a? CLI Geoprocesiranje 鈥� u duhu konferencije Biblioteke u pozadini UI Demistifikacija geoprocessing-a Anatomija FLOSS GIS stack-a

Povijest FLOSS GIS-a 1978 - MOSS 1983 - Proj4 1995 - UMN Mapserver 1998 - GDAL/OGR 1999 - GRASS GIS 2000 - JTS Topology suite 2001 - PostGIS 2002 - Quantum GIS 2002 - GEOS 2006 - OSGEO

艩to je GIS? 艩to je pored standardne radne okoline potrebno da bi bi sustav bio geografski tj. da bi nam omogu膰io podr拧ku za prostorne analize? Tri funkcionalna zahtjeva za prostorne analize (tj.GIS-a): Data driver (GDAL - Geospatial Data Abstraction Library) GDAL/OGR = u pravlja膷ki program za rasterske/vektorske GIS formate podataka tj. omogu膰ava da se pristupi raznim rasterskim/vektorskim zapisima prostornih podataka. PostGIS (PostgreSQL extenzija za "geometry" tip podataka u听 bazi - Simple Feature Specification for SQL) Geometry engine (GEOS - Geometry Engine - Open Source) GEOS = C++ port od JTS-a Omogu膰ava operacije nad vektorima tj. logiku operacija nad skupovima te听 osnovne topolo拧ke analize. Uklju膷uje prostorne operatore i Simple Features for SQL funkcije. Projection engine (PROJ4 - Cartographic Projections library) PROJ4 = Podr拧ka za geografske datume, projekcije i transformacije me膽u njima.

Projekcije http://spatialreference.org/

Prostorni podaci Vektorski podaci: 听 Arc/Info Binary Coverage, Arc/Info .E00 (ASCII) Coverage, Atlas BNA, AutoCAD DXF, CSV, ESRI Personal GeoDatabase, ESRI Shapefile, GeoJSON, GeoRSS, GML, GMT, GPX.... Simple features (OGC- http://www.opengeospatial.org/standards/sfa) POINT(6 10) LINESTRING(3 4,10 50,20 25) POLYGON((1 1,5 1,5 5,1 5,1 1),(2 2,2 3,3 3,3 2,2 2)) MULTIPOINT(3.5 5.6, 4.8 10.5) MULTILINESTRING((3 4,10 50,20 25),(-5 -8,-10 -8,-15 -4)) MULTIPOLYGON(((1 1,5 1,5 5,1 5,1 1),(2 2,2 3,3 3,3 2,2 2)),((6 3,9 2,9 4,6 3))) GEOMETRYCOLLECTION(POINT(4 6),LINESTRING(4 6,7 10)) POINT ZM (1 1 5 60) POINT M (1 1 80) Rasterski Podaci: Arc/Info ASCII Grid, Arc/Info Binary Grid, Bathymetry Attributed Grid, ESRI .hdr, Erdas Imagine Raw, Generic Binary (.hdr), Oracle Spatial GeoRaster,Graphics Interchange Format (.gif), GMT Compatible netCDF, GRASS Rasters, TIFF/BigTIFF/GeoTIFF (.tif), JPEG JFIF, JPEG2000, NetCDF, PNG, Netpbm (.ppm,.pgm), Rasterlite - Rasters in SQLite DB, SRTM HGT Format, Terralib, USGS ASCII DEM, OGC Web Coverage Server, WKTRaster, OGC Web Map Server.... $wget http://slobodniatlas.mapnix.org/~dboto/DORS_workshop.tar.gz && tar -xvzf DORS_workshop.tar.gz

GDAL = GDAL+OGR GDAL Raster (Geospatial Data Abstraction Library) 听 Omogu膰ava manipulaciju rasterskim podacima Frank Warmerdam 1998, Veliki broj podr啪anih formata (http://www.gdal.org/formats_list.html) Koristi ga veliki broj i FLOSS i vlasni膷kog SW-a听 (3D DEM Viewer, ESRI ArcGIS 9.2+, Feature Data Objects (FDO), FME, GeoServer, Google Earth, GRASS GIS, gvSIG, IDRISI, ILWIS, MapGuide, Mapnik, MapServer, MapWindow, QGIS...) Vrlo dobar programski interface - API (SWIG):听Python, Perl, Java, C#, Ruby Dobro dokumentiran.

GDAL Utilities gdalinfo - Iscrpan pregled metapodaka gdal_translate -Transformacija izme膽u razli膷itih rasterskih formata sa kontrolom output-a gdalwarp - Transformacija slike prema koordinatnom sistemu, gdaltindex -Izrada tile indexa za optimizaciju MapServer-a, gdal_contour - Generiranje izolinija iz visinskih modela, gdaldem - PerryGeo alati (1.7.0) osjen膷avanje, izra膷un nagiba i koloriziranje visinskih modela, gdal_merge.py - Izrada mozaika od kolekcije georeferenciranih rastera, gdal2tiles.py -Izrada TMS strukture i preglednika (OL), gdal_rasterize - Rasterizacija vektora, gdaltransform - Transformacija koordinata, gdal_retile.py -Izrada piramida i retile-anje, gdal_polygonize.py -Generiranje poligona iz rastera, gdal_fillnodata.py - Punjenje "nodata" regiona.

gdalinfo $gdalinfo ASTGTM_N44E015_dem.tif Driver: GTiff/GeoTIFF Files: ASTGTM_N44E015_dem.tif Size is 3601, 3601 Coordinate System is: GEOGCS["WGS 84", 听听听 DATUM["WGS_1984", 听听听听听听听 SPHEROID["WGS 84",6378137,298.2572235629972, 听听听听听听听听听听听 AUTHORITY["EPSG","7030"]], 听听听听听听听 AUTHORITY["EPSG","6326"]], 听听听 PRIMEM["Greenwich",0], 听听听 UNIT["degree",0.0174532925199433], 听听听 AUTHORITY["EPSG","4326"]] Origin = (14.999861111111111,45.000138888888891) Pixel Size = (0.000277777777778,-0.000277777777778) Metadata: 听 AREA_OR_POINT=Area 听 TIFFTAG_DOCUMENTNAME=created at 听 TIFFTAG_IMAGEDESCRIPTION=SILC TIFF 听 TIFFTAG_SOFTWARE=IDL 6.3, Research Systems, Inc. 听 TIFFTAG_DATETIME=2008:10:27 20:50:05 听 TIFFTAG_XRESOLUTION=100 听 TIFFTAG_YRESOLUTION=100 听 TIFFTAG_RESOLUTIONUNIT=2 (pixels/inch) Image Structure Metadata: 听 INTERLEAVE=BAND Corner Coordinates: Upper Left听 (听 14.9998611,听 45.0001389) ( 14d59'59.50"E, 45d 0'0.50"N) Lower Left听 (听 14.9998611,听 43.9998611) ( 14d59'59.50"E, 43d59'59.50"N) Upper Right (听 16.0001389,听 45.0001389) ( 16d 0'0.50"E, 45d 0'0.50"N) Lower Right (听 16.0001389,听 43.9998611) ( 16d 0'0.50"E, 43d59'59.50"N) Center听听听听听 (听 15.5000000,听 44.5000000) ( 15d30'0.00"E, 44d30'0.00"N) Band 1 Block=3601x1 Type=Int16, ColorInterp=Gray 听 < format zapisa 听 < veli膷ina 听 <projekcija <EPSG kod - $ less /usr/share/proj/epsg | grep 4326 < metapodaci 听听听听听听听听 < koordinate extenta < type Int16

gdal_translate $gdal_translate --formats 听 - mogu膰nost konverzije izme膽u 88 rasterskih formata sa kontrolom izlaznog formata (GeoTiff - defaultni izlazni format). ***Ukoliko fromat ne podr啪ava pohranu metapodataka u samom formatu, metapodatke pohranjuje u xml datoteku. Konverzija TIFF-a u DEM $gdal_translate -of USGSDEM ASTGTM_N44E015_dem.tif translate_output1.dem 听 Konverzija sa kontrolom veli膷ine outputa (resize) $gdal_translate -of USGSDEM -outsize 50% 50% ASTGTM_N44E015_dem.tif translate_output2.dem 听 Konverzija u 16bit-ni raster $gdal_translate -of PNG ot UInt16 ASTGTM_N44E015_dem.tif translate_output3.png 听 Konverzija u JPG + worldfile $gdal_translate -of JPEG -scale -co worldfile=yes ASTGTM_N44E015_dem.tif translate_output3.jpg 听 Konverzija u tekstualnu xyz datoteku $gdal2xyz.py ASTGTM_N44E015_dem.tif translate_output4.xyz 听 Jako velike mogu膰nosti pogledati: $man gdal_translate

gdalwarp Omogu膰ava izradu mozaika, reprojiciranje i prilago膽avanje slike听 koordinatnom sustavu sa kontrolom outputa . $gdalwarp -of GTiff -co "TILED=YES" -srcnodata 32767 -dstnodata 32767 -t_srs "+proj=tmerc +ellps=bessel +k_o=0.9999 +x_0=5500000 +lon_0=15 +units=m +towgs84=519.729316,72.371421,492.743986,5.63370593,-3.33002924,-3.10746598,10.07015476" -rcs -order 3 -tr 15 15 -wt Float32 -ot Float32 -wo SAMPLE_STEPS=100 ASTGTM_N44E015_dem.tif gdalwarp_output1.tif -t_srs - ciljani prostorno referentni sustav, -tr - rezolucija, -wo SAMPLE_STEPS - gusto膰a uzimanja uzoraka Primjer resempliranja gdalwarp -ts 3601 3601 -r cubicspline ASTGTM_N44E015_dem.tif gdalwarp_output2.tif Primjer isijecanja dijela rastera kori拧tenjem poligona (gdalwarp + gdal_translate) #!/bin/bash SHPFILE=$1 BASE=`basename $SHPFILE .shp` EXTENT=`ogrinfo -so $SHPFILE $BASE | grep Extent | sed 's/Extent: //g' | sed 's/(//g' | sed 's/)//g' | sed 's/ - /, /g'` EXTENT=`echo $EXTENT | awk -F ',' '{print $1 " " $4 " " $3 " " $2}'` echo "Clipping to $EXTENT" RASTERFILE=$2 gdal_translate -projwin $EXTENT -of GTiff $RASTERFILE /tmp/`basename $RASTERFILE .tif`_bbclip.tif gdalwarp -co COMPRESS=DEFLATE -co TILED=YES -of GTiff -r lanczos -cutline $SHPFILE /tmp/`basename $RASTERFILE .tif`_bbclip.tif /tmp/`basename $RASTERFILE .tif`_shpclip.tif

kolorizacija rastera #! /usr/bin/env python from osgeo import gdal import sys import numpy import os.path gdal.TermProgress = gdal.TermProgress_nocb src_file = sys.argv[1] dst_file = sys.argv[2] out_bands = 3 def MakeColor(z_value): 听 '''LUT for color ramp. Keys are pixel values, hash values are RGB triplets.''' 听 color_dict = { 听听听 0:[102,0,255], 听听 25:[20,82,255], 听听 50:[0,194,224], 听听 75:[0,255,122], 听 100:[41,255,0], 听 125:[204,255,0], 听 150:[245,194,0], 听 175:[224,118,0], 听 200:[168,46,0], 听 225:[105,0,0], 听 250:[64,0,0], 听 255:[0,0,0]} 听 key_list = color_dict.keys() 听 key_list.sort() 听 while len(key_list) > 0: 听听听 last_val = key_list[-1] 听听听 if z_value >= last_val: 听听听听听 return color_dict[last_val] 听听听 else: 听听听听听 key_list.remove(last_val) # Print some info print "Creating %s" % (dst_file) # Open source file src_ds = gdal.Open( src_file ) src_band = src_ds.GetRasterBand(1) # create destination file dst_driver = gdal.GetDriverByName('GTiff') dst_ds = dst_driver.Create(dst_file, src_ds.RasterXSize, src_ds.RasterYSize, out_bands, gdal.GDT_Byte) # create output bands band1 = numpy.zeros([src_ds.RasterYSize, src_ds.RasterXSize]) band2 = numpy.zeros([src_ds.RasterYSize, src_ds.RasterXSize]) band3 = numpy.zeros([src_ds.RasterYSize, src_ds.RasterXSize]) # set the projection and georeferencing info dst_ds.SetProjection( src_ds.GetProjection() ) dst_ds.SetGeoTransform( src_ds.GetGeoTransform() ) # read the source file gdal.TermProgress( 0.0 ) for iY in range(src_ds.RasterYSize): 听 src_data = /slideshow/gdalprocessing/6125950/src_band.ReadAsArray(0,iY,src_ds.RasterXSize,1) 听 col_values = src_data[0]听听听听听听听听听听听听听听听听听听听听听听听听 # array of z_values, one per row in source data 听 for iX in range(src_ds.RasterXSize): 听听听 z_value = col_values[iX] 听听听 # print z_value听听听听听听听听听听听听听听听听听听听听听听听听听听听听听听听听听听听听听听听听 # uncomment to see what value breaks color ramp 听听听 [R,G,B] = MakeColor(z_value) 听听听 band1[iY][iX] = R 听听听 band2[iY][iX] = G 听听听 band3[iY][iX] = B 听 gdal.TermProgress( (iY+1.0) / src_ds.RasterYSize ) # write each band out dst_ds.GetRasterBand(1).WriteArray(band1) dst_ds.GetRasterBand(2).WriteArray(band2) dst_ds.GetRasterBand(3).WriteArray(band3) dst_ds = None 听 #END script Ili jednostavnije: 听 $gdaldem color-relief ASTGTM_N44E015_dem.tif ramp.txt color.tif 听 gdje je ramp.txt 3500 white 2500 235:220:175 50% 190 185 135 700 240 250 150 0 50 180 50 nv 0 0 0 0 100%听 255 255 255 75%听听 235 220 175 50%听听 190 185 135 25%听听 240 250 150 0%听听听 50听 180听 50 nv听听听 0听听 0听听 0

gdal_contour Omogu膰ava generiranje izo linija iz rastera sa visinskim podacima (SRTM, ASTER) 听 $gdal_contour -i 10 -snodata 32767 -a height ASTGTM_N44E015_dem.tif gdalwarp_output1.tif Primjer generiranja izo linija iz SRTM .hgt podataka shell skriptom: # povlacenje SRTM podataka (.hgt binary grid) sa NASA ftp servera. Lista za HR je u srtmhr_list.txt cat srtmhr_list.txt | sed 's!^!ftp://e0srp01u.ecs.nasa.gov/srtm/version2/SRTM3/Eurasia/!' | xargs -i wget -nc {} # apsolutna putanja do direktorija sa podacima DATA_PATH="" # ulazi u direktorij sa podacima cd $DATA_PATH # za听 svaki *hgt.zip izvrsava srtm_generate_hdr.sh http://mpa.itc.it/rs/srtm/srtm_generate_hdr.sh for X in *.hgt.zip do # skripta od .hgt fileova generira BIL headere i priprema podatke za GDAL 听听听听听听听 # GDAL nakon toga radi konverziju u GeoTIFF te napravi .prj za shp 听听听 yes | $DATA_PATH/srtm_generate_hdr.sh $X done # generiranje izohipsi iz pripremljenih tifova for X in $DATA_PATH/*.tif do 听听听 echo $X # izvlacenje izohipsi po visinskim podacima za 10, 50 i 100 m i spremanje u ESRI shape file (.shp) 听听听 gdal_contour -i 10 -snodata 32767 -a height $X ${X%%.tif}c10.shp 听听听 gdal_contour -i 50 -snodata 32767 -a height $X ${X%%.tif}c50.shp 听听听 gdal_contour -i 100 -snodata 32767 -a height $X ${X%%.tif}c100.shp done

Jo拧 primjera kori拧tenja GDAL utilitija $gdaltindex index_tiled.shp *_tiled.tif (izrada indeksa za mapserver) $geotifcp n40e015.tif test_dboto.tif (kopiranje metapodataka) $gdalbuildvrt mosaic.vrt *hgt听 (izgradnja mozaika) $gdal_translate mosaic.vrt mosaic.tif (kreiranje slike iz virtualnog kataloga) $gdal_translate -srcwin 0 0 700 700 -of jpeg p2.tif out.jpg (Rezanje) gdal_rasterize -b 1 -i -burn -32678 -l croatia croatia.shp ASTGTM_N44E015_dem.tif (rezanje rastera koti拧tenjem vektora) gdaldem color-relief clip.tif ramp.txt colored.tif听 (kolorizacija visinskog modela) gdaldem slope clip slope.tif -s 111120 (vizualizacija nagiba) gdaldem hillshade clip.tif hillshade.tif -z 5 -s 111120 (sjen膷anje visina hillshadeing)

Zadatak - primjer analize Koriste膰i GDAL i digitalni model reljefa izra膷unajte podru膷je udara plimnog vala visine 30 m na podru膷ju Starigrada. Kao rezultat proizvesti vektorski poligonski sloj ugro啪enog podru膷ja. podaci: ASTGTM_N44E015_dem.tif ?

Rje拧enje Prvo napraviti color schemu za bojanje visina izme膽u 1m i 30 m i pohraniti kao colors.txt: 1 255,0,0 30 0,0,0 nakon toga sa gdaldem pobojati ciljano podru膷je : $gdaldem color-relief ASTGTM_N44E015_dem.tif colors.txt crveno_podrucje.tif sa gdal_polygonize napraviti vektorizaciju ugro啪enog podru膷ja: $gdal_polygonize.py crveno_podrucje.tif -b 1 -f "ESRI Shapefile" odsjecak.shp gdje je kao band argument postavljena vrijednost 1 (tj. red od r,g,b) ta daaaa... i dobili smo poligone u shapefileu ali nisu isfiltrirani poligoni ostalih podru膷ja koja nisu ugro啪ena. Zada膰a: sa ogrinfo pogledajte atribute i njihove vrijednosti te sa OGR-om izdvojite samo ugro啪eno podru膷je u novi shapefile. Primjetiti kako analiza nije u obzir uzela postojanje otoka i njihov utjecaj na ubla啪avanje plimnog vala... Razmisliti o tome kako uzeti u obzir utjecaj otoka.

OGR 艩to je GDAL za rastere to je OGR za vektore 听 Veliki broj podr啪anih formata (http://www.gdal.org/ogr/ogr_formats.html) 听 Velike mogu膰nosti manipulacije nad podacima (Load u Postgis, SQL query-ji, append, update i sl.) te mogu膰nost geoprocessing-a nad vektorima. ogrinfo - Pregled informacija o podr啪anim vektorskim podacima ogr2ogr - Konverzije izme膽u formata sa kontrolom izlaza ogrtindex - Izrada indeksa 听听

ogrinfo $ogrinfo -al region_borders.shp | less $ogrinfo -ro region_borders.shp -sql "SELECT * FROM \ region_borders WHERE CNTRYNAME='Croatia'" | less INFO: Open of `region_borders.shp' 听听听听听 using driver `ESRI Shapefile' successful. Layer name: region_borders Geometry: Polygon Feature Count: 7 Extent: (6.625400, 35.491300) - (23.006200, 49.020300) Layer SRS WKT: GEOGCS["GCS_WGS_1984", 听听听 DATUM["WGS_1984", 听听听听听听听 SPHEROID["WGS_1984",6378137.0,298.257223563]], 听听听 PRIMEM["Greenwich",0.0], 听听听 UNIT["Degree",0.0174532925199433]] ObjectID: Integer (9.0) NATION: String (3.0) CNTRYNAME: String (25.0) CNTRYABB: String (3.0) SQKM: Real (19.5) COLORMAP: Real (11.0) OGRFeature(region_borders):0 < ime datoteke <tip geometrije < broj featurea < prostroni kvadrat (extent) < projekcija < ime/tip atribunog polja

ogr2ogr $ogr2ogr --help (Mala pomo膰 za pregled mogu膰nosti alata) $ogr2ogr -f "KML" region_borders.kml region_borders.shp (Konverzija .shp datoteke u google .kml) 听 $ogr2ogr -f "PostgreSQL" PG:"host=localhost user=user dbname=user password=user" region_borders.kml -nln region_borders (Punjenje .kml datoteke u PostGIS baz) $ogr2ogr -f "ESRI Shapefile" pg_export.shp PG:"host=localhost user=user dbname=user password=user" "region_borders" (Export prostorne tablice u .shp datoteku) 听 $ogr2ogr -s_srs EPSG:4326 -t_srs EPSG:31275 rb_31275.shp region_borders.shp (Konverzija prostornog referentnog sustava) 听 $ogr2ogr -update -append -f PostgreSQL PG:dbname=user region_borders.shp (Update i append iz .shp datoteke u PostGIS bazu)

ogr2ogr - merge (sh vs py) Merge shp datoteka - Shell #!/bin/bash mkdir merged find . -name 'contours*' -exec mv '{}' merged \; for i in $(ls *.shp);听听听听 do ogr2ogr -f 'ESRI Shapefile' -update -append merged $i -nln contours_merge done 听 Merge shp datoteka - Python 听 import sys import glob from osgeo import ogr outfile = "merge.shp" file_list = glob.glob("*.shp") # CREATE OUTPUT FILE out_driver = ogr.GetDriverByName( 'ESRI Shapefile' ) out_ds = out_driver.CreateDataSource(outfile) out_srs = None out_layer = out_ds.CreateLayer("trans", out_srs, ogr.wkbLineString) fd = ogr.FieldDefn('name', ogr.OFTString) out_layer.CreateField(fd) fd = ogr.FieldDefn('height', ogr.OFTInteger) out_layer.CreateField(fd) # READ EACH INPUT FILE AND WRITE FIELDS TO NEW FILE for shapefile in file_list: 听 print shapefile 听 [filename, extension] = shapefile.split('.') 听 in_drv = ogr.GetDriverByName( 'ESRI Shapefile' ) 听 in_ds = in_drv.Open(shapefile) 听 in_layer = in_ds.GetLayer(0) 听 in_feature = in_layer.GetNextFeature() 听 height_field = in_feature.GetFieldIndex('height') 听 counter = 1 听 print height_field while in_feature is not None and (height_field != -1): 听听听 name = filename + "_" + `counter` 听听听 #print kV_field 听听听 #print in_feature.GetField 听听听 height = in_feature.GetField(height_field) 听听听 out_feat = ogr.Feature(out_layer.GetLayerDefn()) 听听听 out_feat.SetField('name', name) 听听听 out_feat.SetField('height', height) 听听听 out_feat.SetGeometry(in_feature.GetGeometryRef().Clone()) 听听听 out_layer.CreateFeature(out_feat) 听听听 out_layer.SyncToDisk() 听听听 out_feat.Destroy() 听听听 in_feature.Destroy() 听听听 in_feature = in_layer.GetNextFeature() 听听听 counter += 1 out_ds.Destroy()

PostGIS Podr拧ka za prostorne podatke u relacijskoj PostgreSQL bazi, Pod GPL licencom od 2001. - Refractions Research, Implementacija OGC Simple Feature For SQL standarda, Mogu膰nost R/W preko svih FOSS GIS desktop alata (QGIS, UDIG, JUMP), 膶itanje podataka od strane svih renderera (MapServer, GeoServer, Mapnik) Testiran sa 600 000 000 featurea sa brzinom 膷itanja 14 000 feature-a u sekundi Izvrstan vector geoprocessing alat sa vi拧e od 350 funkcija (koristi GEOS za topolo拧ke analize)听 0 (nula) KN Podr啪ava: geometrijske tipove to膷aka, linija, poligona, multito膷aka, multilinija, multipoligona i geometrijskih kolekcija prostorne operatore za odre膽ivanje prostornih mjera kao 拧to su povr拧ina, du啪ina i opseg prostorno indeksiranje podataka (R-stablo + GiST) koji ubrzavaju upite nad prostornim podacima听听 Dodatni Alati: psql (CLI su膷elje prema PostgreSQLPostGIS bazi) shp2pgsql - loader pgsql2shp - exporter 听 Instalacija: $sudo apt-get install postgresql postgresql-client postgresql-contrib pgadmin3 $sudo apt-get install postgresql-8.4-postgis postgis Instalacija ostalih alata i biblioteka $ sudo apt-get install gdal-bin proj libgeos2c2a听 grass qgis qgis-plugin-grass mapserver-bin cgi-mapserver python-qt4 python-sip4 python-gdal python-mapscript gmt gmt-coastline-dat

Pode拧avanje baze Kreiranje baze i template-a (preporu膷ujem) $ sudo su postgres $ createdb gistemplate Kreiranje PL/PSQL $ createlang plpgsql gistemplate Load funkcija i SRS tablice $ psql -d gistemplate -f /usr/share/postgresql-8.4-postgis/lwpostgis.sql $ psql -d gistemplate -f /usr/share/postgresql-8.4-postgis/spatial_ref_sys.sql Provjera $psql -d gistemplate -c "SELECT postgis_full_version();" Ulazimo u bazu听 $ psql postgres=# Kreiranje grupe, dodjela role i grant postgres=# CREATE ROLE gisgroup NOSUPERUSER NOINHERIT CREATEDB NOCREATEROLE; postgres=# CREATE ROLE gis LOGIN PASSWORD 'gisuser' NOINHERIT; postgres=# GRANT gisgroup TO gis; postgres=# \q

Dodjela ovlasti na prostorne tablice gis user-u i kreiranje sheme $ psql -d gistemplate gistemplate=# ALTER TABLE geometry_columns OWNER TO gis; gistemplate=# ALTER TABLE spatial_ref_sys OWNER TO gis; gistemplate=# CREATE SCHEMA gis_schema AUTHORIZATION gis; gistemplate=# \q Kreiranje baze rv_gis i priprema za load podataka $ createdb -T gistemplate -O gis rv_gis Dodavanje google projekcije u postgis INSERT into spatial_ref_sys (srid, auth_name, auth_srid, srtext, proj4text) values (900913 ,'EPSG',900913,'GEOGCS["WGS 84", DATUM["World Geodetic System 1984", SPHEROID["WGS 84", 6378137.0, 298.257223563,AUTHORITY["EPSG","7030"]], AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich", 0.0, AUTHORITY["EPSG","8901"]], NIT["degree",0.017453292519943295], AXIS["Longitude", EAST], AXIS["Latitude", NORTH],AUTHORITY["EPSG","4326"]], PROJECTION["Mercator_1SP"],PARAMETER["semi_minor", 6378137.0], PARAMETER["latitude_of_origin",0.0], PARAMETER["central_meridian", 0.0], PARAMETER["scale_factor",1.0], PARAMETER["false_easting", 0.0], PARAMETER["false_northing", 0.0],UNIT["m", 1.0], AXIS["x", EAST], AXIS["y", NORTH],AUTHORITY["EPSG","900913"]] |','+proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x_0=0.0 +y_0=0 +k=1.0 +units=m +nadgrids=@null +no_defs'); Primjer kreiranja view-a za MapServer CREATE VIEW gradovi AS SELECT * FROM mjesta WHERE type LIKE 'Small' ORDER BY gid;

Load shp2pgsql - data loader (mo啪e se koristiti i OGR sa podr拧kom za ve膰i broj formata) $shp2pgsql 鈥� s <epsgcode> <ShapeFileName> <TableName> <dbName> > <filename> $psql -d <dbname> -f <filename> 听 $pgsql2shp -f croatia -h localhot -u user -P user gis "SELECT name, wkb_geometry FROM region_borders WHERE name = 'CROATIA'" Primjer $shp2pgsql -W "ISO-8859-1" -I -s 4326 region_borders gis_schema.region_borders | psql -d gis Napomena: Za na拧e dijakriti膷ke znakove -W "WINDOWS-1250" EPSG referenca: $ less /usr/share/proj/epsg | grep 31275 <31275> +proj=tmerc +lat_0=0 +lon_0=15 +k=0.999900 +x_0=5500000 +y_0=0 +ellps=bessel +towgs84=577.326,90.129,463.919,5.137,1.474,5.297,2.4232 +units=m +no_defs听 <> Export podataka iz baze pgsql2shp -f imefilea imebaze gis_schema.region_borders Prostorni upit za extent SELECT EXTENT(the_geom) FROM region_borders; Kreiranje prostorog indexa GIST (auto vacum i analyze) CREATE INDEX <indexname> ON <tablename> USING GIST ( <geometrycolumn> GIST_GEOMETRY_OPS ); Promjena tipa podatka na stupcu alter TABLE gis_schema.contours50 ALTER COLUMN height TYPE integer;

Primjeri: 听 Kreiranje prostorne kolone - AddGeometryColumn SELECT AddGeometryColumn('public', 'region_borders', 'geom', 4326, 'POINT', 2); Kreiranje prostornog indeksa - GIST CREATE INDEX idx_region_borders_geom ON region_borders USING gist(geom); Izra膷unavanje povr拧ine - ST_Area SELECT neigh_name, ST_Area(geom) FROM region_borders ORDER BY ST_Area(geom) limit 1; 听 Prona膽i sve objekte 100 meters od to膷ke POINT(1000 1000) - ST_DWithin SELECT * FROM geotable WHERE ST_DWithin(geocolumn, 鈥� POINT(1000 1000) 鈥� , 100.0); select zup_naziv from gis_schema.zupanija where ST_DWithin(the_geom, 'POINT(5538942 5007927)',100.0); Ukupna du啪ina ceste izra啪ena u kilometrima - ST_Length SELECT sum(ST_Length(the_geom))/1000 AS km_roads FROM roads; Selecija poligona koje se nalaze unutar drugog poligona ST_Within CREATE TABLE gis_schema.corine_cro AS SELECT gis_schema.corine.* FROM gis_schema.corine, gis_schema.granice WHERE ST_WITHIN (gis_schema.corine.the_geom, gis_schema.granice.the_geom) AND gis_schema.granice.CNTRYNAME = 'Croatia'; Simplifikacija - ST_Simplify CREATE TABLE gis_schema.border_genSimplify AS SELECT ST_SIMPLIFY(gis_schema.border_gen.the_geom,2) FROM gis_schema.border_gen; ST funkcije

Pregled alata Desktop: QGIS (C++/Python) UDIG (Java) JUMP (Java) MapWindow (C#) TatukGIS,ILWIS, gvSIG Vrlo 膷esto ali i uspje拧no se koriste kao framework za razvoj alata prema specifi膷nim zahtjevima. Jump ima vi拧e FOSS forkova ovisno o podru膷ju namjene. Pokriva 80% GIS korisnika. Upravljanje podacima: PostGIS MySQL Spatial SpatialLite GDAL/OGR FDO Vrlo solidno pokriven sloj. Spatial implementacije u skladu sa standardima na svim 膷esto kori拧tenim slobodnim bazama i pokrivena ve膰ina formata zapisa GIS podataka.

WEB GIS Map rendereri: MapServer GeoServer Mapnik MapGuide OS 膶etiri jako dobra renderera karata. Ve膰inom podr啪avaju osnovne OGC standarde. Definitivno najja膷i dio FOSS GIS stack-a. Web klijenti: OpenLayers pMapper GeoMayas MapFish Svi osim pMapper-a iz nove generacije web klijenata. Naj膷e拧膰e se koriste kao framewok za razvoj web aplikacija.

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