GIS4Freedom Blog

PostgreSQL

GDAL_DATA=C:\Program Files\GDAL\gdal-data
GDAL_DRIVER_PATH=C:\Program Files\GDAL\gdalplugins
PROJ_LIB=C:\Program Files\GDAL\projlib
PYTHONPATH=C:\Program Files\GDAL\python
set PGPORT=5432
set PGHOST=localhost
set PGUSER=postgres
set PGPASSWORD=password_of_postgres_user
set THEDB=template_postgis20
set PGBIN=C:\Program Files\PostgreSQL\8.4\bin\
set PGLIB=C:\Program Files\PostgreSQL\8.4\lib\

After that, we make a backup of our PostgreSQL bin and lib directories (PGBIN and PGLIB). Just in case.
select postgis_full_version(), postgis_raster_lib_build_date(), postgis_raster_lib_version()
createdb -U postgres -T template_postgis20 your_database
;
;PostGIS shp2pgsql-gui (Windows):
;
Title=PostGIS Shapefile and DBF loader
Command="$$PGBINDIR\postgisgui\shp2pgsql-gui.exe" -h "$$HOSTNAME" -p $$PORT -U "$$USERNAME" -d "$$DATABASE" -W "$$PASSWORD"
Description=Open a PostGIS ESRI Shapefile or Plain dbf loader console to the current database.
KeyFile=$$PGBINDIR\postgisgui\shp2pgsql-gui.exe
Platform=windows
ServerType=postgresql
Database=Yes
SetPassword=Yes
python C:\Program Files\Postgresql\8.4\bin\raster2pgsql.py -r image.tif -t tablename -o image.sql
psql -h localhost -U postgres -d your_database -f image.sql
gdal_translate PG:"dbname=your_database user=postgres table=your_table mode=2" your_file.tif
gdal_translate -of "PNG" PG:"dbname=your_database user=your_user password=your_password table=your_table mode=2" your_file.png
gdalinfo --formats
gdal_translate -of GTiff -a_srs epsg:4326 -anodata -32768 -co “TFW=YES” -co “INTERLEAVE=PIXEL”
-co “TILED=YES” -co "BLOCKXSIZE=50" -co "BLOCKYSIZE=50" image.tif image_new.tif
DECLARE
geor SDO_GEORASTER;
BEGIN
-- Initialize an empty GeoRaster object into which the external image
-- is to be imported.
INSERT INTO spain_images
values( 1, 'Spain_TIFF_1', sdo_geor.init('spain_images_rdt') );
-- Import the TIFF image.
SELECT image INTO geor FROM spain_images
WHERE image_id = 1 FOR UPDATE;
sdo_geor.importFrom(geor, 'blocksize=(50,50) spatialExtent=TRUE', 'TIFF', 
'file', 'C:\orcl_tut\srtm_35_04_new.tif',
'WORLDFILE', 'FILE', 'C:\orcl_tut\srtm_35_04_new.tfw');
UPDATE spain_images SET image = geor WHERE image_id = 1;
END;
DELETE FROM user_sdo_geom_metadata WHERE table_name = 'spain_images' AND 
column_name = 'IMAGE.SPATIALEXTENT';
INSERT INTO user_sdo_geom_metadata VALUES ('spain_images', 'IMAGE.SPATIALEXTENT', 
SDO_DIM_ARRAY(SDO_DIM_ELEMENT('X', -180, 180, .00000005),
SDO_DIM_ELEMENT('Y', -90, 90, .00000005)), 4326);
DROP INDEX spain_images_sidx;
CREATE INDEX spain_images_sidx ON spain_images(image.spatialExtent) INDEXTYPE IS mdsys.spatial_index;
> gdal2wktraster.py" -r C:\orcl_tut\*.tif -t spain_images -s 4326 -k 50x50 -I 
-o C:\orcl_tut\srtm.sql
> psql -d tutorial01 -f C:\orcl_tut\srtm.sql
create table cariboupoint_buffers_wgs AS
select t.id, sdo_geom.sdo_mbr(sdo_geom.sdo_buffer(sdo_cs.transform(t.geom,
4326), 1000, 1)) geom
from cariboupoints t;
DELETE FROM user_sdo_geom_metadata WHERE table_name = 'cariboupoint_buffers_wgs' AND 
column_name = 'geom';
INSERT INTO user_sdo_geom_metadata VALUES ('cariboupoints_buffers_wgs', 'geom', 
SDO_DIM_ARRAY(SDO_DIM_ELEMENT('X', -180, 180, .00000005),
SDO_DIM_ELEMENT('Y', -90, 90, .00000005)), 4326);
DROP INDEX spain_images_sidx;
CREATE INDEX cariboupoints_buffers_wgs_gidx ON cariboupoints_buffers_wgs(geom) 
INDEXTYPE IS mdsys.spatial_index;
declare
cellCoordinate mdsys.sdo_geometry;
ret varchar2(256);
generated_statistics sdo_number_array;
gr sdo_georaster;
begin
-- create statistics table
create table srtm_caribou_inter_statistics (
id number, -- buffer id
rid number,
statistics sdo_number_array
);
-- Intersects spatial extent of the rasters with the buffers
for intersection in
(select t.id, t.geom, r.image_id as rid from spain_images r,
cariboupoint_buffers_wgs t
where sdo_geom.sdo_intersection(r.image.spatialExtent, t.geom, 0.005)
is not null)
loop
-- Get georaster image
select image into gr from spain_images where image_id
= intersection.rid for update;
-- First, we need geom coordinates in raster space coordinates
sdo_geor.getCellCoordinate(gr, 0, intersection.geom,
cellCoordinate);
-- Generate statistics for a given georaster object
ret := sdo_geor.generateStatistics(gr,
'samplingFactor=1', cellCoordinate, 'FALSE', '1-1', 'TRUE', NULL,
'TRUE');
-- update object
update spain_images r set r.image = gr where
r.image_id = intersection.rid;
-- commit changes
commit;
-- get generated statistics
generated_statistics := sdo_geor.getStatistics(gr, 1);
-- insert them in statistics table
insert into srtm_caribou_inter_statistics(id, rid, statistics) values
(intersection.id, intersection.rid, generated_statistics);
end loop;
commit;
end;
/
create table means_table(id number, rid number, mean number)
declare
st_array sdo_number_array;
sql_stmt varchar(256);
begin
for c1 in (select * from srtm_caribou_inter_statistics) loop
for i in c1.stats_array.FIRST..c1.stats_array.LAST loop¡
if i = 3 then
sql_stmt := 'insert into means_table values (:1, :2, :3)';
execute immediate sql_stmt using c1.id, c1.rid, c1.stats_array(i);
end if;
end loop;
end loop;
commit;
end;
select m.id, m.mean*sdo_geom.sdo_area(sdo_cs.transform(cpb.geom,
32198), 1)  / sdo_geom.sdo_area(sdo_cs.transform(cpb.geom, 32198), 1)
as meanelev from means_table m, cariboupoint_buffers_wgs cpb where cpb.id = m.id;

GIS4Freedom Blog

Updating GDAL PostGIS Raster driver

NOTE: Please, update your feeds. This blog has been moved to http://www.libregis.org

I’m moving to www.libregis.org

http://www.libregis.org

Web-based PostGIS geometry/raster viewers

Free and ready to use anywhere GIS Virtual Machine!

Collaborate with an Open Source project and win 5000$

How to install and configure PostGIS Raster on Windows

Enviroment: Windows 7 32 bits

Step 1: Installing Python and Numpy

Step 2: Installing GDAL

Step 3: Installing PostgreSQL

Step 4: Installing PostGIS

Additional notes:

PostGIS Raster meets Desktop

GDAL PostGIS Raster Driver

WKT Raster is now PostGIS Raster

Comparing Oracle GeoRaster with PostGIS WKT Raster (II)

PREVIOUS STEPS

Loading shapefiles (caribou distribution shapefiles)

Visualizing the caribou point in OpenJUMP

Loading raster data

Making buffers around the caribou points

Intersecting the caribou buffers with the elevation rasters

Summarizing the elevation values for each buffer and exporting the table to CSV

Conclussions