I used Vector > Geoprocessing tools > Difference function in QGIS to obtain difference between two vectors (Shown as vectors - overall and polygon in the figure below). But the difference is not clean. There is a intersection between polygon and the difference layer. Is there a way to have a clean cut?
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I have a large raster (145.927.240 cells) with categorical data. The data can be found here:
https://developers.google.com/earth-engine/datasets/catalog/ESA_GLOBCOVER_L4_200901_200912_V2_3
For each cell I would like to calculate the distance to the nearest neighbor of each class. What is the most efficient (i.e. feasible) way to do this? I've looked for suitable packages, but so far I haven't found one that does what I want (with a raster of that size).
To give some context:
I would like to combine several raster files, convert them to a data table to use them as input in different models and then convert the result back to a raster file.
I have a shape file of a road network and another shape-file containing area boundaries. Is there any better code that I can use to get length of roads that lies inside each polygon?
This Question was asked earlier with the difference that I want to use R instead of QGIS.
I tried:
intersec=intersect(roads,Polygon)
road_length=tapply(intersec$length, intersec$polygon, sum)
This works, but the problem is that the intersection does not divide the length of the roads, that cross to Polygons, but doubles them in the intersec file and assigns the full length of those roads to both Polygons.
How I found out about that Problem: There is no error message, but the following proove tells me that something is wrong:
a=sum(roads$length) and b=sum(intersec$length)
a and b do not have same length -> a is smaller than b.
I actually did this for a project about 8 months ago.
I had been getting into the sf way of dealing with spatial data, and so my solution uses Classes, Methods, and functions from that package.
First, I made sure both my roads and shapes had the same coordinate-reference-system (CRS) by using sf::st_transform on one of them. Then I used sf::st_intersection() to find the intersections, and used sf::st_length() on the result to get the lengths. You may need to aggregate the lengths at this point, depending on whether your roads were combined into one super-multi-line or if each road is its own object. The following gives the gist of what I think ought to work:
sf::st_intersection(road, shape) %>% # Find the intersections, which should all be points or multilines
dplyr::mutate(len_m = sf::st_length(geom)) %>% # Find the length of each line
dplyr::group_by(SHAPE_COLUMNS) %>% # Here you need to insert all the columns from your shapes
dplyr::summarize(len_m = sum(len_m))
Is there a function in the R raster package that is analogous to sampleRandom but which extracts n random pixel values from within an irregularly shaped polygon feature rather than a rectangular extent object?
I know there are alternative approaches such as generating random points within a polygon and then use the extract() function to get pixel values, but am wondering if there is a more direct path I have missed.
Thanks
No, there is not a single function for this.
I'm trying to achieve smooth shading of triangles in my graphics program, however I'm currently stuck on how to do it exactly, I've got two options.
Option 1: (per vector)
Create a "zero" Vector.
Add the non-normalized normal of every incident triangle to the created vector.
Scale the resulting vector by 1 / incidentTriangleCount.
Return the normalized version of the resulting vector.
Option 2: (per vector)
Create a "zero" Vector.
Add the normalized normal of every incident triangle to the created vector.
Scale the resulting vector by 1 / incidentTriangleCount.
Return the non-normalized version of the resulting vector.
Both approaches are giving me different results and I don't really know which one to take, can anyone give me advice on this?
Always work with normalized normals. Thus your two options will merge in single one :)
Besides, you have to be careful when using "every" incident triangle, because in this case you will have your entire model smoothed, which is not good. E.g. a model of pencil that actually have edges will look like a rounded one. Implement a treshold, i.e. only consider triangles, which normals have relatively small angle beetween them.
This might be a stupid question...
I've two vectors containing Y coords
X is simply 1:8
I've added the lines to a plot area and would like to identify the point of intersection of the two lines.
Is there a default package to find this?
Thanks
The intersection of two lines is found analytically by solving the two linear equations which define the lines. I'll leave the math as an exercise to the OP.
If you want to use a very helpful and powerful package, you could read up on the package spatstat . Once you've converted your lines into psp objects, use spatstat:crossing.psp to find intersections.