Re: [R-sig-Geo] help

[Andrew Duff]

Shouldn't this line be

xlist <- nb2listw(neighbours,glist = NULL,style = "W",zero.policy =TRUE)


instead of


xlist <- nb2listw(neighbours,glist = NULL,style = "W",zero.policy =TRU)

?



On Wed, Apr 4, 2018 at 9:44 PM, Yalemzewod Gelaw 
wrote:

> I am a new student to R learning for spatial analysis. I was hoping
> someone could help me with the
> error message I keep getting when I try to convert the neighbour data to a
> listw object use the nb2listw()  function.
>
> plot(xw_nbq, coords,add=TRUE,col="red")> summary(xw_nbq)
>
>
> Neighbour list object:
> Number of regions: 140
> Number of nonzero links: 680
> Percentage nonzero weights: 3.469388
> Average number of links: 4.857143
> 2 regions with no links:
> 3 138
> Link number distribution:
>
>  0  1  2  3  4  5  6  7  8  9
>  2  6  4 16 32 35 17 13 13  2
> 6 least connected regions:
> 11 32 57 117 124 137 with 1 link
> 2 most connected regions:
> 28 71 with 9 links
>
> ​when I try to run nb2listw, i got repated error following the below error
> message. ​
>
> xlist <- nb2listw(neighbours,glist = NULL,style = "W",zero.policy =TRU) > 
> summary.listw(xlist)
> Error in summary.listw(xlist) : regions with no neighbours found, use
> zero.policy=TRUE
>
> I wonder if someone advises me how to fix the error message from my
> working directory
> ​
>
>
> *Regards, *
>
> Yalem
>
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>

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Re: [R-sig-Geo] How to “smooth” a raster map

[Andrew Duff]

You mean re sample?



 On Jun 28, 2015, at 4:25 PM, Thiago V. dos Santos thi_vel...@yahoo.com.br 
 wrote:
 
 Dear all,
 
 I am trying to create a map from raster data. The file came from a crop 
 model, with resolution of 0.5 degree. Even when I disaggregate it (i.e. 
 increase spatial resolution), the map looks really pixelated. I am trying to 
 make it look better.
 My current code produces this image: http://i.stack.imgur.com/WssPy.png
 
 where I would like to smooth the data, by supressing the pixelated look. 
 Some other visualization programs do this automatically, so I guess it should 
 not be hard to reproduce using R. 
 
 For example, this is the same file plotted using Panoply: 
 http://i.stack.imgur.com/jXYI7.png
 
 It doesn't look absolutely smooth, but at least it doesn't have the pixelated 
 look neither. How to achieve a similar result in R? 
 
 This is the code to reproduce my problem:
 
 --
 library(RCurl) 
 library(rasterVis)
 
 # Go to temp dir and download file - approx. 1.7M
 old - setwd(tempdir())
 
 # download raster and shapefile
 download.file('https://dl.dropboxusercontent.com/u/27700634/yield.nc', 
 'yield.nc', method='curl')
 download.file('https://dl.dropboxusercontent.com/u/27700634/southern.zip', 
 'southern.zip', method='curl')
 unzip('southern.zip', exdir='.')
 
 # load southern Brazil shapefile
 mapaSHP - shapefile('southern.shp')
 
 # load brick
 b - brick('yield.nc', level=16)
 
 # create color scheme
 mycols - rasterTheme(region=colorRampPalette(brewer.pal(9,'Greens'))(100))
 
 # use second brick layer to plot map
 levelplot(b[[2]], margin = FALSE, main = Rice yield in tons/ha, 
 par.settings = mycols) +
 layer(sp.lines(mapaSHP, lwd=0.8, col='darkgray'))
 
 # return to your old dir
 setwd(old)
 
 --
 Thanks in advance for any input,
 --
 Thiago V. dos Santos
 PhD student
 Land and Atmospheric Science
 University of Minnesota
 http://www.laas.umn.edu/CurrentStudents/MeettheStudents/ThiagodosSantos/index.htm
 Phone: (612) 323 9898
 
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Re: [R-sig-Geo] Help with latlong to UTM conversion when UTM zones are different

[Andrew Duff]

A number of field folks prefer UTM because 

-it matches legacy paper USGS quad map series traditionally used for field 
navigation
-units are in meters and can be used to gauge field distances from a coordinate 
readout 



 On Mar 27, 2015, at 10:48 AM, Michael Sumner mdsum...@gmail.com wrote:
 
 There is no good natural reason to use UTM, it mistifies me why our
 community tolerates this bizarre default. I always use a local equal-area
 projection unless some other compromise dictates a different choice.
 Cheers, Mike
 
 On Fri, 27 Mar 2015 21:28 Barry Rowlingson b.rowling...@lancaster.ac.uk
 wrote:
 
 If you have lat-long data that crosses two UTM zones then its
 generally okay to just pick *one* and transform all the points to
 that. Use the one that has the most points in. Basically use the UTM
 zones as guidelines to pick one UTM zone coordinate system. Unless
 your data spans several zones and you want quite high accuracy of
 distance measurements. Some points bleeding over into an adjacent zone
 are no problem.
 
 All projections are approximations to the earth's spheroid, so points
 that are within a single UTM zone have some distortion in their
 distance or angle relationships. Transforming points that are within
 an adjacent UTM zone is just an extension of that distortion. You can
 compute the precise distance error if you want for the furthest points
 by comparing with the geodesic distance.
 
 Alternatively you might find there is a coordinate system that spans
 your dataset nicely - often when a country or an island or a region
 crosses UTM zones there is an official coordinate system defined that
 is used by the authorities there.
 
 Also alternatively, there's nothing to stop you defining a transverse
 mercator system based on the centre of your data.
 
 Barry
 
 
 
 On Fri, Mar 27, 2015 at 7:44 AM, moses selebatso selebat...@yahoo.co.uk
 wrote:
 Hello
 I have animal movement data that I have converted from Lat/Long to UTM,
 unfortunately the data falls in two UTM zones (34S and 35S). For some
 reason R cannot display both of them in the same window (the 35S data is
 way off the expected location).
 The question is how do I convert the data such that R can correctly read
 it?
 Moses SELEBATSO
 
 (+267) 318 5219 (H) (+267) 716 393 70 (C)
  (+267) 738 393 70 (C
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Re: [R-sig-Geo] 3D KDE to Triangular Irregular Network

[Andrew Duff]

Thanks a lot Michael that was very helpful.  It seems like you might be able
to make a TIN from one of the contour levels, say 75% or something.  I'm not
really sure how to get to those isosurface vertex coordinates for a given
contour level.  Is that possible in R.

-Original Message-
From: r-sig-geo-boun...@r-project.org
[mailto:r-sig-geo-boun...@r-project.org] On Behalf Of Michael Sumner
Sent: Friday, April 12, 2013 2:06 PM
To: Duff, Andrew A (DFW)
Cc: r-sig-geo@r-project.org
Subject: Re: [R-sig-Geo] 3D KDE to Triangular Irregular Network

A TIN cannot represent that data structure, the plot shows multiple surfaces
that wrap around in 3D. (A TIN cannot do that). The plot is made by
contouring (isosurfaces) from a 3D array.

You can represent the array in NetCDF, and maybe your GIS can read that.
Otherwise you could do the same as here but create a 2D raster for every
slice in the 3rd dimension and reconstruct over there.

Bare bones using raster to NetCDF:

library(raster)
r - brick(UD$estimate, xmn = min(UD$eval.points[[1]]), xmx =
max(UD$eval.points[[1]]),
  ymn = min(UD$eval.points[[2]]), ymx = max(UD$eval.points[[2]]))

## Plot each 3D slice
plot(r)

## write to NetCDF, you need ncdf or ncdf4 package writeRaster(r, file.nc)

See ?writeRaster for further options to add descriptors to the file, and you
will likely need to worry about the orientation when making the raster
object.



On Sat, Apr 13, 2013 at 4:29 AM, Duff, Andrew A (DFW) 
andrew.d...@dfw.wa.gov wrote:

 I am interested in being able to export the results of a 3 dimensional 
 kernel density estimate from the ks package in R to a format that 
 could be viewed in 3D GIS application such as ESRI's ArcScene or 
 ArcGlobe.  I want to example the use of airspace in relation to 
 terrain features.  A TIN seems to be the most logical geospatial data 
 structure that would support taking the 3D kde output into GIS.  Does 
 anybody have any ideas on how to get from a 3D kde output in ks to a 
 tin.  A self-contained sample of generating the kde is below.

 ###sample
 library(ks)
 df - data.frame(x=sample(1:200, 10), y=sample(1:200, 10), 
 z=sample(1:500, 10))
 Hpi1 - Hpi(x = df)
 UD - kde(x=df, H=Hpi1)
 plot(UD)

 Thanks in advance.

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--
Michael Sumner
Hobart, Australia
e-mail: mdsum...@gmail.com

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[R-sig-Geo] TWS Spatial Ecology and Telemetry Awards

[Andrew Duff]

Good Afternoon,



The Wildlife Society Spatial Ecology and Telemetry working group offers
some awards each year to people who have created a GIS or Telemetry-related
tool, document, software program or service that has made a significant
difference to our profession.  There is no money involved; it is just a way
to say thank you to people who have made a difference to us in conducting
spatial analysis.  The awards can be given for both commercial and
non-commercial products.  Recipients of the awards get certificates of
appreciation, plus get mentioned in The Wildlife Professional and our
newsletter.



Do you know of a person or product that you would like to nominate for one
of these awards?  I know some of you have depended heavily on some R tools
for spatial analysis, for example.  If those tools really helped you out,
maybe you could nominate the people who wrote the packages.  It means a lot
to the people who created the tools, plus it gives a little more exposure
for the tools they wrote.



If you would like to nominate someone, please send their name and a short
description of why you think they deserve the award to either Jeff Jenness
(jeffj AT jennessent.com) or James Sheppard (spatialecologist AT gmail.com).
The TWS Spatial Ecology and Telemetry working group awards committee will
select three recipients, and we expect to make our final selection by the
end of May.



Andy



Andrew Duff, M.S., Certified Wildlife Biologist

Acting Wildlife Data Systems Lead

Biological Data Systems, Wildlife Science Division

Washington Dept. of Fish and Wildlife

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