# Tag Info

9

It is a consequence of a theorem of Archimedes (c. 287-212 BCE) that for a spherical model of the earth, the area of a cell spanning longitudes l0 to l1 (l1 > l0) and latitudes f0 to f1 (f1 > f0) equals (sin(f1) - sin(f0)) * (l1 - l0) * R^2 where l0 and l1 are expressed in radians (not degrees or whatever). l1 - l0 is calculated modulo 2*pi (e.g., -179 -...

9

An elegant principle provides a simple answer: All points on a smooth curved surface are flat at a sufficiently large scale. This means that after affine change of coordinates (usually involving just a rescaling of one of them), we can use formulas of Euclidean geometry, such as the Pythagorean Theorem for computing distances and the negative-...

5

The crux of the matter is finding a quantitative definition of "width" of the channel. Consider a point P located anywhere within the river. The width certainly cannot be any less than the shortest distance from P to the left bank plus the shortest distance from P to the right bank. A moment's thought suggests this is an excellent candidate for the width ...

4

Assuming you're using ArcGIS 10, you can use the arcpy RasterToNumPyArray command to get a NumPy array, which if you read the NumPy Input and Output routines documentation you can see you can easily dump the raster data to disk as a text file with a format of your choice. For example: import arcpy import numpy as np arr = arcpy.RasterToNumPyArray('C:/some/...

4

This is how you can do that with R/raster library(raster) r <- raster() # by default 1 by 1 degree, just what you want a <- area(r) Each cell of RasterLayer 'a' has a value representing its approximate area To illustrate the results for one column (it is the same for all columns), as area varies by latitude, not by longitude lat <- yFromRow(r, ...

3

1) If you want to run the script from inside GRASS GIS, it is relatively easy to transform the original Matlab script (.m) in a Python script if it do not uses specific toolboxes (with numpy and the others scientific Python modules) 2) if you want to run the .m script outside GRASS GIS, you can use Octave, open source alternative to run m-code (MATLAB ...

3

Within ArcMap, I think you're looking for the Raster to ASCII tool (under the Conversion Tools -> From Raster toolboxes). (The Matlab output, if it's in ASCII, can in theory be imported into arc with the related ASCII to Raster tool -- not sure if you've tried that.)

3

You can add the matrices as ASCII Grid file to QGIS, and create contours from the lat and lon values. This will create a degree grid like this: In this mailing list topic I described how to set up a suitable projection for it: http://osgeo-org.1560.x6.nabble.com/Have-LCC-center-terms-need-PROJ-4-terms-td5102799.html EDIT Sample data can be found in ...

3

Your projection is likely to be the World Mercator projection. (EPSG 3395) You can use the package proj4 in R to transform your coordinates. It is also supported by Matlab (as you can see here). projection = +proj=merc +lon_0=0 +k=1 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs inverse=true to go from cartographic coordinates to geographic ...

3

I would convert the GRID to ASCII format first using Raster to ASCII (Conversion). If you have many GRIDs, use the batch conversion by right-clicking on the tool and selecting "batch". Then you can easily bring in the ASCII files into MATLAB using arcgridread. Here's an example from Mathworks: [Z,R] = arcgridread('MtWashington-ft.grd'); mapshow(Z,R,'...

3

If you have gdal command line setup you can try this: gdal_translate -outsize xsize[%] ysize[%] <src_dataset> <dest_dataset> Example: creating 25% of original image. gdal_translate -otusize 25% 25% input.tif output.tif ......

3

Some (slightly) theoretical pointers: Instead of focusing on attributes, one approach to the problem might focus on exploring characteristics of movement patterns. Those could be explored by calculating aggregated characteristics of movement or dividing your data into logical 'chunks' (for instance, daily trajectories of certain objects). At next stage you ...

3

This can be accomplished in the same way we would lay out a grid of squares in the plane: Lay off a baseline in any direction. Mark it off in equal increments (of 20 km). Call these points p(0,0), p(0,1), ..., p(0,n), in order. It does not have to be geodesically straight, but it should be close to straight. Starting with the first marked point p(0,0), ...

3

I'm not sure whether your LiDAR data are raw (i.e. a point cloud) or have already been interpolated to a raster DEM, but if it is the former, you'll need to interpolate the data to a raster DEM first. The next thing you need to do is to perform a 'Depression Filling' operation. Most GIS will have a tool for this task. Once you've created your filled DEM ...

2

As @PolyGeo points out, convert to shapefile. Looks like you can do this in the Mapping Toolbox.

2

Given you've tagged R in your question I'd take a look at the CRAN Spatial View and the gstat package in particular. Not sure if it has the exact PRISM interpolation method, but it would certainly be a good place to start. Alternately you could look into the SciPy interpolation and ndimage subpackages if you'd prefer to work in Python.

2

I suggest you learn the differences between aerial and satellite images first. They are not the same! The image geometry is different and therefore you would have to have different processing. Stereo images are an advantage, yes, but quite expensive. Lidar is expensive too and you cannot cover a huge area. What are your requirements; height accuracy, ...

2

Either of the following methods will work in your case: Mosaic to New Raster (Data Management). Specify a MAXIMUM pixel overlap rule. This method is beneficial if you want to also reduce the bit depth (i.e. filesize) of the output raster. Cell Statistics (Spatial Analyst) Choose the MAXIMUM statistics type.

2

Eventually, I came up with a good result. This is the procedure I followed to estimate Landsat azimuth at my location. I drew two segments in a GIS, one for each side of my scene (left and right, see figure 1), and added four ("real") corner points on the end of them (green points). This is done in the Reference System of the specific scene (in my case is ...

2

Below is a work around method using python and bunch of libraries such as netCDF4, numpy and shapefile. With Anaconda, these library installations are very much easy. The steps of the method are Import WRF ARW output into python, by python netCDF4 library. Query WRF ARW output variable XLAT, XLONG into numpy array of latitude and longitude using python ...

2

Here is a list of some of the tools I know of that could be helpful for you: The Arc Hydro Tools or the HEC-GeoRas tools (which I think were developed partially from Arc Hydro tools). While there is a lot going on with these you may not need, they have the ability to create Cross Sections at specified distances, from which you could get your widths. The ...

2

If you don't know the datum or coordinate system for a pair of latitude/longitude coordinates, then the coordinates are ambiguous. Ambiguous coordinates means any transform or comparison between them will most likely have incorrect results.

2

David Tarboton does a good job of breaking it down at http://hydrology.usu.edu/taudem/taudem5/help53/D8FlowDirections.html basically as does Jenson. Jenson, S. K., and J. O. Domingue. 1988. "Extracting Topographic Structure from Digital Elevation Data for Geographic Information System Analysis." Photogrammetric Engineering and Remote Sensing 54 (11): 1593–...

1

I try to use gdal in Matlab and I had same issue and I solved it in this manner. I tried both on Matlab 2011a and 2013a and probably solution is quite similar. Mainly, the problem is with proj library and if you try to launch it 1) on bash (gnome-terminal) probably you have proj >> proj Rel. 4.8.0, 6 March 2012 >> which proj /usr/local/bin/...

1

I authored the SWM file format for Esri. All the methods are of course within ArcGIS to read/write/convert etc... but the format is relatively simple and can be read w/o any license whatsoever. The file is written in little endian... with the first line being the header written in text. You should open it with the "rb" option... Here is how to read the ...

1

Well it turns out that it is very simple, to write multiple features you give shapewrite an array of structs, rather than a single struct. It's a shame that the shapewrite documentation doesn't describe that option, but perhaps they assume that it is obvious... Anyway, editing the code above so that it works without using GDAL: % Lines is a structure ...

1

You may achieve the desired result by going to your raster layer properties, pressing the plus (+) sign to add the deired color, and then setting the transparency percent: You can see, in may example, how the raster target color transparency works: Before (no white color transparency / or the transparency percent for the white color = 100%) After (...

1

There may well be a better way to do this for the whole triangulation, but here's a way to do it in Matlab for one triangle, which could be repeated. It uses Heron's forumula for the area of a triangle. trMesh is assumed to be the triangulation object. vertices = trMesh.ConnectivityList(ElementNo,:); vX = trMesh.Points(vertices, 1); vY = trMesh.Points(...

1

A similar question has actually been posed on stackoverflow before and is answered there (with matlab): http://stackoverflow.com/a/702174/545346 Edit: I was actually thinking about writing something about spatial indexing, but I then thought it was not necessary since you spoke about 12 edges. A logical approach would be a filter using the distance of both ...

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