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4

I'm guessing you never worked with SAR data before, so I'll break your question down into parts I can answer: 1) Create high resolution DEMs in GIS The process of creating a DEM just from SAR data is quite complex and requires a lot of processing power and memory. I don't know of a GIS software that implements DEM creation due to these constraints. 2) ...


1

The task could feel trivial by reading the gdalwarp documentation http://www.gdal.org/gdalwarp.html and GDAL AAIGrid -- Arc/Info ASCII Grid driver documentation http://www.gdal.org/frmt_various.html. The target pixel size is three times bigger than the native resolution 0.008333333333 degrees/pixel (not 1000 m/pixel, see the comments). gdalwarp -of AAIGrid ...


4

If you are open to using alternative software to solve your problem, then I can suggest the Remove Off-Terrain Objects tool of the cross-platform open-source GIS Whitebox Geospatial Analysis Tools (of which I am lead developer). I realize that you said in your question that you could not convert your data to LAS format, but the tool takes a raster, not LAS ...


3

I would have to say that without the original LAS point cloud, you will only be incorporating more inaccuracies into the data through raster manipulation. The DEM provided looks relatively clean for a heavily urbanized 1m resolution DEM. The "uplifted squares" are a result of triangulations across data voids, where the buildings are not included in the ...


0

I figured it out (got the hint from the user forum on rapidlasso.com): like mdsumner indicated with his/her question, it is a problem of the open source lastools version (LGPL 2.1). With the licenced model these bands will not be generated.


1

In GRASS GIS, use r.in.arc for the import or simply r.in.gdal (Menu: File -> Import raster data -> Common formats import). This should read the file right away.


0

I suggest you refer to the following publication: C. Devaraj and C.A. Shah, 2014. Automated geometric correction of Landsat MSS L1G imagery, IEEE Geoscience and Remote Sensing Letters, 11(1): 347-351.


2

This is a wonderful question. I agree with you that option 1 is suboptimal because it modifies the elevations of the DEM. Rather than solely looking at the scaling effect, you'll also be comparing the impact of varying roughness. With option 2 there is no particularly obvious way to set-up the kernel and you might have to fit planar surfaces to elevations ...


0

The format looks like AAIGrid, see How can I convert a ascii file to geotiff using Python? for an example. You can use gdal_translate to convert it to geotiff: gdal_translate -of "GTiff" fname.asc outname.tif The file extension .asc is important to tell gdal which format to use. Or use the python code from the linked question.


1

DEM pixel size is based of your topographic map scale . DEM pixel size that calculate using topographic map with 1:25000 scale has 10 * 10 meters pixel size. For 1:50000 scale the pixel size must be 20*20 meters and so on. consider the below links : What are appropriate pixel resolutions for DEMs based on source map scales? Mathematical relationships ...


2

In addition to what has been mentioned there are a few more things to consider. You can enhance the 3-dimensional impression of the map by not only varying the color hue but also the saturation, brightness and vibrance. Saturated colors will appear closer and are suitable for mountain tops while the lowlands and valleys can be colored rather unsaturated or ...


4

The Root Mean Square Error (RMSE) is one of those rare indices that is perfectly named, in that the name actually tells you how to calculate it. First difference the two DEMs ('error' or more properly in this case the deviation). Then square the differences. These first two steps can be calculated using a single expression in the Raster Calculator. Next, ...


1

Try lastools. Many parts are free and you could BLAST2EM and get just get what you need. Do not try to interpolate lidar in ArcGIS unless you are prepared for a long wait. You have a robust set of options and it runs from command line. It will use the TIN approach to create your dem. It is fast and efficient.


2

First, if needed, create a LAS Dataset from your .las files. Then use LAS Dataset to Raster, select Average for a DEM output.


0

For the task, it is of course important that you have a sampling of profiles that is dense enough to ensure that the result becomes precise enough. If you have a 1,6m DEM and profiles pr. 100 m. then your profiles may be more precise, but your overall uncertainty will be huge. If you have sufficient data in profiles, then you create points along your ...


2

What a great question! The problem is that contours are a cartographic lie. They're a convenient way of conveying information about the relief within a landscape. However they don't translate directly to the real-life experience of topography, except perhaps in the heavily modified and engineered landscapes of our urban environments. Topography in reality is ...


3

Answer for others so confused people as I am: To know how to deal with downloaded raw Landsat data - what else in pre-processing do I need? Firstly check their processing level in_MTL.txt file (included in downloaded Landsat image: http://landsat.usgs.gov/Landsat_Processing_Details.php) Processing level = DATA_TYPE L1T - terrain corrected processing. ...


6

There is a new, 30 meters resolution SRTM DTM coming out. As stated on the NASA JPL official page, The next release is planned for later in 2014, and it is expected to include all of South America plus North America south of the United States. It is incomplete, for now, it has only limited coverage. You can read an article about SRTM coverages here ...


2

ArcGIS solutions: Convert the x,y,z data to a feature class then: Build a TIN using x,y,z data and then convert this to a raster. Interpolate the x,y,z to raster. Use Anudem (topo2raster) to create a DEM. Convert point to raster and just set a cell size that is suitable for your x,y,z data (usually only for dense data). I would output a GeoTiff. x,y,z ...


1

If you are new to hydrology/arc I'd suggest using arc hydro (for 10.2 try download and documentation). This will give you average slope and 10-85 using Watershed Processing - Flow Path Parameters - Flow Path Parameters from 2D Line. elrobis's is correct that you may need to sample the slope more often depending on: (1) how the rivers were defined (think ...


2

You can use the SAGA Contour lines from grid tool, and there set both the minimum and maximum to your elevation contour of choice Here's an example with an elevation of 500 meters


0

I think your best bet is to use r.contour.level from GRASS in the Processing toolbox. This allows you to provide a list of specific contours (a list of one in your case). In this way you should be able to specify the individual contour you are interested in. The Raster->Extraction->Contour tool requires you to specify just a contour interval which ...


2

You might see both datasets aligned because On-the-fly-reprojection is enabled. This works when both datasets have different CRS. Other software does not offer this tool, so you have to reproject one of your datasets to the CRS of the other to make them align in every software. BTW this applies also to some tools integrated in QGIS, like intersection or ...


2

I find openWind normally works very well so, without any further information, I suspect you are spot on about mismatched CRS. According to the documentation: openWind is fundamentally based on a meter grid so the projection only comes into play when converting to and from geographic coordinates. openWind does not carry out on-the-fly projection so ...


3

A DEM (digital elevation model) is a raster and not contour lines or polylines. If the point data is a systematic grid of points (equal spacing) then it is as simple as converting straight to raster using a rasterize tool. In QGIS you can use "Raster > Conversion > Rasterize (Vector to raster)". However, if the points are irregular then the becomes a ...


2

In QGIS, there is also (in addition to r.walk which @radouxju has mentioned) the Walking time plugin which you can download (Plugins > Manage and Install Plugins...). This uses the Tobler's hiking function which estimates the travel time based on data from your line layer in relation with the elevation values of the raster layer:


3

Ordnance Survey As the name suggests, OS Terrain 50 is a product with a 50 metre grid resolution (http://www.ordnancesurvey.co.uk/business-and-government/products/terrain-50.html). OS Terrain 50 has been compared with GPS points in a range of sample areas to provide a Route Mean Square Error (RMSE) value for the height points in each geographic ...


1

You might like to check out one of the presentations at FOSS4GIS 2014 titled " Open Source Work-flow for Surface Interpolation with Curvilinear Anisotropy — Michele Tobias, University of California Davis." http://vimeo.com/106235881


2

GRASS can do what you're asking. Here's how I would approach the mssion: First get or digitize the banks of the river as a (long, winding) polygon. Then import your xyz data as a point vector (v.in.ascii), and your river polygon in the appropriate GRASS location/mapset with v.in.ogr. Now you'll have to think about the region settings with g.region . You ...


3

The USGS DEM format is a default GDAL input and output format. See this link for more information. This means you can "clip" is using the -a_ullr command in gdal_translate or use gdal_warp using the -cl and -crop commands. Here is some code to get you moving gdalwarp -of DEM -cutline C:\temp\area_of_interest.shp -crop_to_cutline C:\temp\input.dem ...


3

It is an open format See Link but not one typically used as an Output. I believe GRID is a far more commonly used format for DEM data but that may just be a personal preference. I did find a reference for converting "TO" that format but it is an old solution (written in Avenue ... the old language used with ArcView 3.X). A link I found indicated that it may ...


5

if you compute the statistics of your raster, (or with zonal statistics if you look for a specific zone), you can find its maximum value (properties > source > Statistics > max) Then you can use the value in raster calculator Con("raster" == maxvalue, 1) EDIt: where maxvalue is either the raster created by zonal statistics or the value that you read in ...


1

From GWR by Roger Bivand: Geographically weighted regression (GWR) is an exploratory technique mainly intended to indicate where non-stationarity is taking place on the map, that is where locally weighted regression coefficients move away from their global values. Its basis is the concern that the fitted coefficient values of a global model, ...


1

I'm not surprised that you haven't got an answer to this seemingly simple question yet. You've opened a whole can of worms here! Take this DEM and vector streams layer as an example: At the simplest level, you could always perform a profile analysis with your streams and see whether they have predominantly downward profiles: Consider for a moment what ...



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