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7

I think I can answer it for you. If you look at the precision vs. accuracy image on the link you provided, precision refers to the repeatability of the observation. For example, if I measure the distance from one point to another and it is always vaying only by a very small amount, then I am making measurements at a high precision. But, basically, ...


7

Files ending with 'w' (tfw, jpw or jgw, bpw and so on) are world files. These files are used to geolocate rasters that otherwise have no means of geolocation. They tell the GIS where the file's origin is in the real world and the size and rotation of the pixels. however, they do not store any information about projection. You only need a world file if ...


7

By default an RGB image will be written to an RGB color model JPEG image, but this is not actually the most efficient way of writing to JPEG. It is better to convert to the YCbCr color space, and encode that. This is in fact the typical form of standalone JPEGs and what GDAL will produce when writing to a free standing JPEG file. Compressing a 4K x 2.6K ...


6

It isn't nice code, but for your specific circumstance, here is some python that should save typing them out by hand: f = open('list.txt', 'r') lines = f.readlines() for line in lines: lineparts = line.split(' ') outfile = open(lineparts[0], 'w') for i in range(1, 4): outfile.write(lineparts[i] + '\n') outfile.write(lineparts[4] + ...


4

You should be able to do this using the gdal_translate command line tool. http://www.gdal.org/gdal_translate.html To convert to Arc/Info ASCII Grid: gdal_translate -of AAIGrid elevation.tif elevation.asc To convert to ASCII Gridded XYZ: gdal_translate -of XYZ elevation.tif elevation.xyz Binary executables of the GDAL tools are available here: ...


4

Yo can access to the centroid of each pixel as doc says with ST_PixelAsCentroids (postgis 2.1) SELECT x, y, val, ST_AsText(geom) FROM (SELECT (ST_PixelAsCentroids(rast, 1)).* FROM dummy_rast WHERE rid = 2) foo; x | y | val | st_astext ---+---+-----+-------------------------------- 1 | 1 | 253 | POINT(3427927.775 5793243.975) 2 | 1 | ...


4

It looks like your original tiffs are reprojected. In their original projection, there are no black borders. Best strategy is to take the tiffs in their original CRS, build a virtual index on both with gdalbuildvrt, then reproject the vrt to the desired CRS with gdalwarp and do the tiling or pyramiding on that with gdal_retile.py.


4

You probably don't need to convert a GeoTiff to a Tiff. As a GeoTiff your image will not only be readable by any GIS package but probably can also be read by any image manipulation package too (e.g. Photoshop, GIMP etc) baring some exceptions. Image editing packages simply ignore the bits in the Tiff header that make it a GeoTiff - either that or they ...


4

AWK is perhaps the most effective tool for such text conversion (although if you're familiar with Perl you might prefer it, out of habit): it was designed for exactly this kind of one-off quick reformatting work. Here is the full AWK code to perform the requested operation on the input specified: BEGIN {OFS="\n"} {print $2, $3, $4, $5 $6, $7, $8 > $1} ...


4

A very simple approach which springs to mind is to export the tiff to an ascii grid format such as ESRI's .asc file. You will then have a space delimited plain text file. It will have a few header lines which describe the origin, resolution and NoData values etc and you can easily skip over these for the sake of you calculations. You can do the ...


4

Is Python an option? Use RasterIO (a Python GDAL/ numpy bridge) to load the raster to NumPy array, then use numpy.amax() to find the maximum value, followed by numpy.where() to find the row/column indices, then calculate the lat and lon from the raster extents.


3

You can indeed use gdal_translate either giving the source coordinates ([-srcwin xoff yoff xsize ysize]) or the georeferenced coordinates ([-projwin ulx uly lrx lry]). For instance: import os inDS = ... # input raster outDS = ... # output raster lon = ... # lon of your flux tower lat = ... # lat of your flux tower ulx = lon - 24.5 uly = lat + 24.5 lrx = lon ...


3

Resolution in raster/grid context is the "cellssize", or the width/height in a certain unit (meter, feet etc) of each cell/pixel in the grid. I have seen the term precision used in two ways with grids: Most of the time, the same as you referred to, the accuracy of the measurement Datatype being used for cell/band values, e.g float, double, integers


3

Install the Image Mosaic JDBC plugin A GeoServer webpage hints at the root of the problem: GeoServer does not come built-in with support for Postgis raster columns, it must be installed through an extension. Proceed to Image Mosaic JDBC for installation details. This extension includes the support for Postgis raster. I followed the complex setup ...


3

I would create a virtual raster with both images. You can do it in Raster > Miscelaneous > Build Virtual Raster (Catalog). It will be a quite small file that will allow you to open both images at the same time in QGIS, and set blending to them globally. That way the overlapping blending mode or transparencies won't show. Two overlapping images with ...


3

When you export the images from ArcGIS, check the Write World File check box. This will create a world file (*.TWF) with the same name as the output tiff. The world file stores the georeferencing information. Always keep the twf file with the tiff. IF you do not resize or crop the image in Photoshop, or change the data frame coordinate system, the tiff ...


3

Do not download multiple files at once You are downloading from TRMMopen (which is an official download source of the NASA / Goddard PMM) via anonymous ftp. You are only prompted a username/password dialogue if you have multiple connections to this ftp site, e.g. because you are attempting to download more then one file at once. Instead, try to download ...


2

In GRASS GIS, the command r.out.xyz does this conversion job. Instead of first importing the GeoTIFF file, you can simply register it beforehand with r.external in the GRASS GIS location (i.e. basically the needed project directory).


2

In a nutshell, the ESRI ASCII grid format is human-readable and is text. This means you can open it in a text editor and see the actual values for yourself without needing specialized software. TIFFs are binary and are therefore not human-readable. You'd need some specialized software like GIS to read it. TIFFs are supported by almost all GIS packages ...


2

Here's an extremely dense but useful explanation of the GeoTIFF specification: http://duff.ess.washington.edu/data/raster/drg/docs/geotiff.txt The PCS tag is the EPSG number of the projection coordinate system. GCS is the EPSG number of the geographic coordinate system. So your first file is in UTM 59S, with linear unit of meters. The second file is World ...


2

I ran into this same problem and in my case it was caused by GeoServer not having write permission for the pyramid data directory, i.e., the directory I passed to gdal_retile.py as the -targetDir argument. The stack trace in the log included: Caused by: java.lang.IllegalArgumentException: This plugin accepts only File, URL and String pointing to a file ...


2

I'll suggest that you can do this using Geoprocessing . This will be the way with the least amount of interaction with ArcGIS. This needs to be just a two stage process. Firstly, you will need to run the Project Raster tool. You can export the raster to ETRS-TM35FIN coordinate system Then you can extract the required area, by using the Extract by Polygon ...


2

The geotiff you describe does have a projection - it's called Plate Carre. As noted in the link this is neither equal area nor conformal, so it's usefulness is very limited. On the other hand, it is very easy to produce, since the lat/lon of a pixel is trivially derived from the pixel indices. As to your question "is this normal?", I'm not sure how to ...


2

You can use the Buffer tool to add buffers to create a new shapefile representing the 1 mile buffers. Then you can use the Extract by Mask tool to clip the raster inside of the buffer shapefile features. Mind you need a Spatial Analyst extension to use this tool. I recommend using Python or even ModelBuilder to create a loop that will step through each ...


2

The coordinates of the target extent have to be expressed in the target SRS: -te xmin ymin xmax ymax: set georeferenced extents of output file to be created (in target SRS). Being... >cs2cs +init=EPSG:4326 +to +init=EPSG:3857 5 43 556597.45 5311971.85 0.00 15 48 1669792.36 6106854.83 0.00 the command should be something like: ...


2

As you know the coordinates of your corner, and assuming you also know the pixel size, you can create a world file that can be interpreted by most software. you just need to create a small text file with the extension .tfw and the same name than your tiff file. See Wikipedia for details. Here is the content : size X rotation X (probably zero) ...


2

I use the tools listgeo and geotifcp. Before you start your work with photoshop retrieve, the geoinfo with listgeo and store it in a file. After your work in photoshop is finished put the information back with geotifcp file (..look also at also Geotiff). Huck


2

I recommend the use of a vrt file, a virtual raster file that would point to your data with the bounding box that you want. you can call it from python using import subprocess subprocess.call(["gdalbuildvrt", "-te", "xmin", "ymin", "xmax", "ymax", "output.vrt", "input.tif"]) then you use your vrt like an image. If you want you can create the vrt with ...


2

It's a well known and longstanding issue that gdalwarp doesn't deal with compression well. The solution is to gdalwarp without compression then gdal_translate with compression. To avoid two lengthy processes, gdalwarp to VRT first, it's really quick, then gdal_translate with the -co compress=lzw option. i.e. $ gdalwarp -tap -tr 30 30 -t_srs "etc..." -of ...


2

I recommend using Python or R (or a GIS software), as @Marc Pfister has suggested. However, you can do it with bash and gdal only, and heavy usage of grep. First get the Min/Max values without coordinates: Obtain the Min / Max values with gdalinfo or gdalinfo -mm like explained in your other question about Min/Max values. Use grep (and possibly some awk) ...



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