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1

That's a two step process rasterize the building layer to create a raster with the building height information use field calculator to sum up the DEM and building height Note that the two rasters have to be in the same CRS before you can add them up in the field calculator.


2

The way I have done this in the past is to convert buildings, forested areas, etc. to a raster (rasterize the polygon using the height column for the raster value, using the same pixel resolution as the DEM). Then merge the two rasters (DEM and rasterized buildings). This will add the building height to the DEM. One thing to note is that you will probably ...


3

You can use the Con (Spatial Analyst) tool to calculate the area of specified elevation values. In this example, I stated that I wanted all elevation values of a floating point DEM > 400 = 1, else = 0. The black and yellow image is the result (Figure 1). Then, simply open the attribute table and look at the count next to the Value = 1 row (Figure 2). ...


1

If your elevation raster is integer, Build Raster Attribute Table. Then, select the rows in the table of interest, and look at the Statistics for the Count field (right-click 'Count' -> Statistics). The SUM value is the number of pixels selected. Multiply this value by the area of one pixel (raster layer properties -> Source tab -> cell size). Repeat with no ...


0

In newer QGIS versions (I tested it only in QGIS 2.6) you can set the resolution when you save a raster via "save as" (quite similiar with ArcMap)


0

Actually, it is not granted that you will be able to recover some information from the shadowed areas. However, I once dealt successfully with (cloud) shadows in a hyperspectral image. The aim was simple land cover classification. Here's what I did. I'm not sure how this would work with Landsat images, but since it is very simple you should give it a try. ...


0

I believe this code solves the problem, although it is a bit ugly. It creates a binary raster with 1 values for each null cell in my HAND raster. I then used a cursor to retrieve the count field for the binary raster's table and compare that to the count from the previous iteration in a while loop. The loop ends when the count stops changing (it may be that ...


0

ArcGIS for Maritime: Bathymetry is a new component of the ArcGIS for Maritime platform available with the ArcGIS 10.1 for Desktop release. The software is developed for management and analysis of bathymetric data. Digital Coast is an excellent resource for such data. Not only is digital coast an excellent data resource it is also an excellent training ...


3

This is actually an exceedingly complex problem and not one that you're likely going to be able to solve using conventional ArcGIS tools. To do this, you'll need to develop for each depression in your landscape the relation between depth and volume, i.e. the depth vs volume curve, which will be uniquely defined for each depression based on it's form. To ...


2

3D is not (yet) implemented in QGIS, but you can store the height in an attribute table field and create a 3D output manually with ogr2ogr -z_field fieldname outside QGIS. See Is it possible to create 3D dxf with OGR? for an example. This is rather 2.5D, because all vertices of a line must have the same elevation (as contours have). In QGIS, you could use ...


1

Design a flat raster surface for each height then run the Cut Fill tool. This will also give you volumes if needed. The Cut Fill tool summarizes the areas and volumes of change from a cut-and-fill operation. By taking surfaces of a given location at two different time periods, it identifies regions of surface material removal, surface material ...


1

I think it's the alpha band that's causing problems. To extract the data band: gdal_translate -of hfa -b 1 original.tif band1.img Then to warp: gdalwarp -of GTiff -s_srs epsg:4326 -t_srs epsg:3857 -co "tfw=yes" band1.img band1_warp.tif Gives an image: With GDALINFO > Driver: GTiff/GeoTIFF Files: D:\Testing\Tiff\band1_warp.tif > ...


2

Some things to consider: (1) Your problem is generally known as spatial interpolation because points are distributed in space, or surface interpolation because you are estimating the height of a point on a "surface" (which might be physical or abstract). (2) It's not generally a good idea to label to points in space as X,Y,Z because those letters are ...


0

You can define the labelling style using the label.style argument of lattice::contourplot. In my opinion, you should choose align. It is not a complete solution because it does not break the contour lines, but it is better than the default method. On the other hand you can overlay two different contour plots with different cuts, line widths, and labels ...


0

This is not the answer for your question but may be for your problem. I would populate stream raster, for each point (cell) in streams populate watershad. Within populated watershads, iterate trough all points and calculate HAND something like: cell_value - min(watershad).


0

The steps are, requires scripting: i=0 1. Convert DEM to points 2. Select all of them within 10 km radius from point i 3. Interpolate surface using trend 4. Calculate slope of result. 5. Use raster statistics to define mean slope (in theory it must be the same everywhere, but points on the edge are an issue). This is why statistic will do. 6. Record ...


2

Here is some of my C++ code for working with triangles: Structures, in order to understand my code understanding these structures is necessary: struct CoPair // linked list of coordinates { long ID; float X; float Y; float Z; CoPair *NxtPt; }; struct Tri // linked list of triangles made from 3 CoPair { bool Active; CoPair *A; ...


0

GDAL comes with a gdal_grid utility to create a regular grid from scattered data. I'd start with this one since it seems that you are already using GDAL tools. If you have dense LiDAR data, check out LAStools, such as las2dem or lasgrid.


0

Yes, FME has two DEM Generators. They are called, appropriately, DEMGenerator and RasterDEMGenerator. You'll want to use the RasterDEMGenerator. There are several options for tweaking the output: I recently used this tool to process about twice as many points and it took 2 hours and 45 minutes. There were five XYZ files writing directly to the DEM. ...


3

The general terrain attribute that you are describing is called Relative Aspect (RA) and in its general form, it can be calculated for any input azimuth (Az) as follows: RA = Abs(aspect - Az) if (RA > 180) { RA = 360 - RA } where aspect is the terrain slope aspect calculated from the DEM. Here is an example of code that calculates the index ...


1

A DTM raster can be represented by triangle meshes by finding a set of non-overlapping triangles that covers the entire mesh and approximates the elevation field. There are two different types of triangle meshes that can be used for this purpose: a triangulated regular network (TRN), in which every pixel of the raster is represented by a vertex, and all ...


2

In FME it would depend on the precise source format. If - as someone has suggested in the comments - the ASCII lidar is simply a series of x,y,z values then use the Point Cloud XYZ Reader, and a Writer such as LAS (or whatever point cloud format you want). Otherwise using a raster Reader (Esri ASCII Grid format?) and then use the PointCloudCombiner ...


4

The concern that I have is that lidar is not a systematic sample, as shown in your example. This data appears to have already been gridded and then thinned based on terrain or vegetation variation. Given the short-distance variation and observed spatial pattern of the clustering, my guess is higher point spacing was retained due to vegetation (e.g., trees). ...


1

You say you have ArcGIS, but you will need the Spatial Analyst or 3D Analyst extensions. I agree with the above comments. Use IDW or Natural Neighbor interp in SA. Set up the extent and the cell size using the environment settings. Could also build a TIN from these points then use the TIN to Raster tool.


2

If you are not in an urban area, interpolating elevation from 4 meter point density to 1 m grid is quite safe, especially if your 1 m spacing reflects a larger roughness of your terrain (e.g. river bed). Make sure that you use an exact interpolator to preserve the elevation at known points, because LIDAR is precise and accurate.


0

Depending on the source of your DEM files you may be able to use the DEM to Raster GP tool. This tool is specifically for importing USGS DEMs. Otherwise, as Jakub mentioned above, try ASCII to Raster.


1

You need to highlight all the attributes you want to appear in the output from the "Layers with fields/bands to get values from" list. If you have not clicked on 'EUD_CP_DEMS_3500015000-AA-86 : Band 1 (raster)' so that it is highlighted then you will get nothing. This is what the message: Complete the input fields and press OK... means (I think ...


0

Have you tried to add the PostGIS raster layer with the table manager (https://plugins.qgis.org/plugins/tablemanager/) ? I experienced similar problems: be sure to have the connection to PostGIS correctly configured (for example, I think 'user' is mandatory).


1

The resolution is defined as 1/3 degree, that means three cells are one degree high or wide. Near the equator, the cells are square, but next to the poles they get to long rectangles, ending in a triangle at the pole itself. If you want a resolution in real meters on the ground, you have to reproject the data to a projected CRS. Then you will get the ...


5

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) ...


2

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 ...



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