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2

My general opinion is that this is a lousy tool for creating a DSM however, @Andre Silva hit the nail on the head in using the maximum argument and you should mark his answer as correct because it directly addresses your question. Ideally, for a DSM you should use the first or last returns with an interpolation algorithm, and not merely a binning approach. ...


2

An average point spacing of 0.3 is approximately equal to a point density of 11 returns per unit of area. In theory, it should be sufficient to generate a DSM with pixel of area 1. As explained here, my understanding of a LiDAR DSM is: DSM as a raster. This represents the first echo the laser received for each laser pulse sent out, and represents the ...


1

ASCII files are text files that can be readable in any text editor and you can check their contents. However, the ASCII files may represent raster data, such as DEM, but they should be formatted in a specific way in order to be able to convert them into raster DEM. You can use ASCII to Raster tool in ArcToolbox, but the data should be formatted in the ...


1

QGIS can use the GRASS GIS and SAGA GIS tools that solve the problem (example uses GRID VOLUME by SAGA GIS from processing).


0

The value on a chart tells the user the least depths that can be expected associated with some reference station (vertical datum) be it feet or meters. The sign is irrelevant it is an absolute value. If you are looking at a chart and it says 12 that means it is 12 units below the vertical datum usually it is MLLW because for navigation you want to know ...


0

I get an error meassage that MrSID.dll can not be found, but it is not needed for Geotiff output, and I get the expected raster result: Your project CRS is EPSG:4326, so the grid cell size should be in degrees. The default of 100 might be nonsense.


1

To load SRTM data in MapInfo and create a DEM from it, you need two things: (1) Vertical Mapper (an extension to MapInfo) (2) SRTM of ASCII format. The Vertical Mapper has a tool to import external formats, but it has limited number of formats that can be imported into MapInfo, but luckily ASCII format is one of them. If the SRTM that you have is not in ...


1

Another option to extract raster values to point shapefile is to use QGIS which is a free open source software. From plugin manager in QGIS download Plugin: Point sampling tool, which can extract multiple raster values to point shapefile similar to Extract Multi Values to Points which requires Spatial Analyst extension in ArcGIS. The tool works perfectly ...


4

You can't use linear units with the projection your data is using. The feature class you have is using a Geographic Coordinate System, which only use angular units like degrees and radians. You have to Project this feature class to a Projected Coordinate System, like State Plane coordinates, to be able to use linear units like meters. The Project tool is ...


1

It is not possible to directly improve the DTM without carrying out some sort of smoothing or interpolation. Auxiliary data is needed or the DTM needs to be rebuilt. To improve the assigned values of elevation in the part covered by forest, return to the raw LiDAR data and test alternative ways to classify ground points and generate a new DTM. For example: ...


0

I assume that what you call “DEM of the lake” is DEM of lake bottom and surrounding area. If this a case, it is a few steps procedure main ones being calculation of lake bank altitude and average lake depth. Convert lake polygon to polyline, using feature to line tool Set environment settings snap raster to DEM, cell size = one for DEM and convert ...


0

You could transform the sea level rise raster to a vector format. Than you can use an intersection analysis to select the lines that are affected.


3

Actually you don't need to load the layer into the GUI first. In ArcMap and QGIS it works similar. Just run the tool from the toolbox. This way you don't need any python code. For ArcMap use the raster clip tool. I think in Qgis it is called "clip raster by mask layer". If all else fails you can revert to ogr2ogr to handle the clipping for you.


3

From the IDLE interface that comes in the python folder of ArcGIS, you can execute any tool without actually loading the layer into the GUI. Go to IDLE's File Menu, New File, and type something like: import arcpy arcpy.Clip_management("c:/your_path/your_raster.tif","","c:/your_path/catchment_clip.tif", "c:/your_path/your_catchment.shp", "#", ...


2

You need to download the DSM pointclouds instead of DTMs. Please see here the differences: What is the difference between DEM, DSM and DTM?


2

Assuming you have column with elevation values for these points there are many ways to go depending on what is the nature of your data. You must decide what interpolation method you want to choose. Do you have billions of points or just few? How are the points scattered - relatively regularly, dense in some parts and sparse in others? These are very ...


2

If the points has a field that represents elevation values, you need to interpolate the points to convert them to raster elevation. You can refer to this tutorial on how to do that in QGIS.


1

You need to know the vertical datum they are using and its relationship to depth. For example, in coastal Washington the mean high tide line is about 2.2 meters NAVD 88 and the tide range is 5 m, that means if they took soundings during high tide the elevation would be positive an the "mean sea level" elevation of zero would be several hundred yards ...


1

For commercial solution take a look at http://www.3dsurvey.si/ And for opensource I would certainly try https://github.com/OpenDroneMap/OpenDroneMap


10

There is a difference, and I recommend the typology presented by Lindsay (2015) be used. Lindsay (2015) presents a typology which defines a pit as a single cell in a DEM whose elevation is below that of the surrounding cells and a depression as a region of cells which drain inwards to a pit. This is consistent with the definitions used by O'Callaghan and ...


2

To put things clear, I assume that you want to compute the area which responds to the following conditions: located inside your DEM altitude interval located inside your vector boundaries located where your second raster (let's call it raster2) has values other than "nodata" (this is the unclear part of your post, feel free to correct me if I ...


2

What you have is a hillshade surface built from a LiDAR point cloud. According to ESRI: A hillshade is a grayscale 3D representation of the surface, with the sun's relative position taken into account for shading the image. So each pixel of your .tif raster has an hypothetical illumination value given a reference position of the sun. What you want is ...


1

I believe it is possible, but probably not very accurate. Multiple elevations do not have same RGB value if the ramp is continuous and not like having red at both extremes. I would probably start by reducing the number of colors and saving the result into a paletted image by using rgb2pct-py. Then, I would vectorize the paletted version with ...



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