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Jul
23
comment Spatial segregation from a raster of racial distribution in the USA
I believe that past literature has used entropy measures such as Shannon's.
Jul
22
revised Merge multiple SpatialPolygonDataFrame into 1 SPDF in R (analogue to “Merge” Tool in ArcGIS)
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Jul
22
answered Merge multiple SpatialPolygonDataFrame into 1 SPDF in R (analogue to “Merge” Tool in ArcGIS)
Jul
17
comment Grid vs. Polygon Overlay in R gives different results than in QGIS
Reproducing your subset extent, I am getting exactly 6 cells intersecting the Nyctiellus polygons with 1%, 4%, 8%, 13%, 30%, 38% polygon cell coverage. So, I am not sure what is going on. Try: plot(s); plot(as(bins, "SpatialPolygons"), add=T) to insure that there is overlap and please use my example that returns percent coverage as it seems to be more stable.
Jul
17
comment Grid vs. Polygon Overlay in R gives different results than in QGIS
If you look at the resulting raster stack each species has an associated binary raster that indicates occupancy ie., plot(spp.pa). With a quick look at results I would recommend using the getCover argument and remove the [0,1] assignment in my example thus, directly using the resulting percents. One genus "Nyctiellus" exhibits a 1-13% pixel coverage at bin=10 and could potentially get dropped during rasterization with large pixels. It is much more stable when I drop bin to 1. You could use my last example and set p=0 and then make the assignments: sfp[sfp <= p] <- 0; sfp[sfp > p] <- 1
Jul
17
comment Extracting Data from Raster based on Aspect Raster file
You can nest even further by just applying the which index directly: snowThawNorth <- getValues(snowThawDate)[which(getValues(aspect)==1)]
Jul
17
revised Grid vs. Polygon Overlay in R gives different results than in QGIS
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Jul
17
comment Extract DEM and DTM information from LIDAR image using E-Cognition
A DSM or DTM would represent an unfiltered, interpolation of the point cloud were the DEM is the filtered interpolated ground or "bare earth" surface.
Jul
17
comment Extract DEM and DTM information from LIDAR image using E-Cognition
eCognition is not remotely designed for this type of analysis. Whereas methodology such as watershed segmentation have been used to identify ground returns this was a specialized algorithm and segmentation on a single image is not an appropriate approach. It is time for you to dig into the literature to understand how lidar filtering works and settle on an appropriate methodology.
Jul
17
revised Grid vs. Polygon Overlay in R gives different results than in QGIS
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Jul
17
answered Grid vs. Polygon Overlay in R gives different results than in QGIS
Jul
17
comment How is R used with ArcGIS for Desktop?
I have been alpha testing the ESRI bridge and it is fairly useful both in passing data back-and-forth but also in running R as an inline process. Toolbox scripts are easy to deploy where R function calls are as simple as (in.parm, out.parm).
Jul
17
comment How should i combine these rasters?
Stop and apply some logic to the problem. Rather than thinking in terms of explicit assignment for the outcome think of assignment in terms of a mathematical operator.
Jul
16
answered iterate over spatial polygon data frame in R
Jul
16
comment Grid vs. Polygon Overlay in R gives different results than in QGIS
I would need to work though your problem. Could you subset the data so it can be posted? I have no idea how QGIS is coded for this but one thing that comes to mind is if the pixels are being treated as cell centroids it could make a huge difference. The SpatialPixelsDataFrame class represents cells as polygons whereas SpatialGridDataFrame are cell centroid points. Because of this, one could test the differences in results based on different input vector topologies. You could also use rasterToPoints to directly test cell-centroid based representation of the raster.
Jul
16
comment How to reclassify a raster in R?
@gsa, To avoid the pain of another question, I went ahead and modified my answer to include combining the buffers. In the future please limit your post to one question. Here you have: 1) how do I assign raster values, 2) how do I check values in a raster and now, 3) how to I combine rasters and finally 4) how do I mask a raster.
Jul
16
revised How to reclassify a raster in R?
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Jul
16
comment Changing the extent of a Shape file in ArcMap for distrubution modelling in R
Yes, that is exactly what I addressed. If you plot x you will see that the plot extent does not encompass y, By changing the limits of the plot you change the plot extent to encompass the additional data without changing the source data, only the display. However, in my last example, where you modify the @bbox slot, you are changing the extent of x which will modify the data. By doing this you do not need to change the plot limits. This would be a critical step if you doing something like creating random samples that needed to match the larger extent.
Jul
15
comment Generate grid shapefile in R
After creating the raster, you could also use something like: "res(r) <- 3.7" or the "resolution" argument in the raster function directly, but this would ignore the specified number of rows and columns.
Jul
15
revised Generate grid shapefile in R
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