[R-sig-Geo] overlapping polygons in shapefile
Roger Bivand
Roger.Bivand at nhh.no
Wed Mar 12 10:30:54 CET 2014
On Wed, 12 Mar 2014, Alice C. Hughes wrote:
Please do not take threads off-list - I am not offering private advice,
and what is said on the list is intended to be public so that others can
contribute.
> Hi
>
> Thanks so much for the informative answer-but I'm not certain if it will
> yield what I am looking for-basically I have distribution range polygons for
> multiple species and I want to collapse them down to give the number or
> species sugested to be in an area-whether that be 1 or 1000 in map form-so
> basically you have a "heat-map" or species occurences: which tool would yield
> this? I have all the polygons in one shapefile at present in geographic
> projection and WGS 84, decimal degrees Thanks so much for your help
The whole point of using R is that users are encouraged to create and modify
tools from parts (aka functions or methods). Most research problems are coerced
into fixed subsets of problems that can be tackled with "other people's" tools.
If researchers are to take responsibility for actually tackling research
questions with the best alignment of data collection, data representation,
workflow in data handling, analysis, it is their respopnsibility to ensure that
the tools are as well aligned with the problem as possible. Otherwise, your
ability to infer about the actual processes will have been amputated by the
limitations imposed by using tools not matching your problem.
Change of support is particularly important here, so your ourput map of species
incidence (don't call it a heatmap, it isn't measuring heat) depends crucially
on steps in the workflow (for example, what is the error involved in
delineating the range polygons?).
I was mislead by your phrasing to think that you also needed the areas of each
species x species overlap (counts are a bit trivial), and you haven't said what
you mean by area (is it a measure, a polygon, or a raster cell?). What does:
"number o[f] species sugested to be in an area" mean? Do you mean a raster
cell? Or the polygonal intersection output for each unique count? Or what?
gOverlaps(..., byid=TRUE) should give counts (it returns a matrix, and the
rows/columns should be the counts if the polygons are species). However, if you
have many polygons, do use the STR tree approach only to search for overlaps
among polygons that actually have intersecting bounding boxes. You can count
the number of overlaps in this way. If someone can provide random overlapping
polygons in a SpatialPolygons object, it would be easier to show. All R lists
do ask for reproducible cases with built-in or simulated data.
Roger
>
> Alice
>
>
>
> Alice C. HughesAssociate ProfessorCentre for Integrative
> Conservation,Xishuangbanna Tropical Botanical Garden,Chinese Academy of
> SciencesMenglun, Mengla, Yunnan 666303, P.R. ChinaPh:
> 15198676559achughes at xtbg.ac.cn
>
>> Date: Tue, 11 Mar 2014 20:56:02 +0100
>> From: Roger.Bivand at nhh.no
>> To: dr_achughes at hotmail.co.uk
>> CC: r-sig-geo at stat.math.ethz.ch
>> Subject: Re: [R-sig-Geo] overlapping polygons in shapefile
>>
>> On Tue, 11 Mar 2014, Alice C. Hughes wrote:
>>
>>> Hi All
>>> This should be simple-but ArcGis keeps getting stuck at 22%...I have a
>>> large shapefile, which contains multiple overlapping polygons for
>>> various species-and I would like to count for any area how many polygons
>>> overlap.A script would be really fantastic!Thanks in advance
>>
>> Wouldn't it just? However, as usual, such scripts will only cause grief,
>> as they will not (necessarily) match your workflow. Most likely, you
>> have two choices, one to rasterise thr polygons separately (not
>> together, because they overlap), then count overlapping cells.
>>
>> If the shapefile is "large", like tens of thousands of polygons, you could
>> try the rgeos package, first using gUnarySTRtreeQuery() or
>> gBinarySTRtreeQuery() to identify possible overlapping candidates (these
>> functions report intersecting bounding boxes of polygons).
>>
>> Next try gOverlaps() subsetting the input objects by the output of the
>> intersecting bounding boxes. Once you've found the overlaps, take their
>> intersections with gIntersection(), and get the area with gArea(). Note
>> that this only applies to planar, projected polygons. If they are in
>> geographical coordinates, project before using gArea(). Look carefully at
>> the byid= arguments in gOverlaps, gIntersection and gArea. Depending on
>> the complexity of the setting, you may be using for loops and subsetting
>> by indices - there are examples in Ch. 5 of ASDAR (2nd edition) of this
>> kind of subsetting (or see the online code at www.asdar-book.org), about
>> chunks 41-3 in http://www.asdar-book.org/book2ed/cm2_mod.R.
>>
>> Hope this helps,
>>
>> Roger
>>
>>> Alice
>>>
>>> Alice C. HughesAssociate ProfessorCentre for Integrative
>>> Conservation,Xishuangbanna Tropical Botanical Garden,Chinese Academy of
>>> SciencesMenglun, Mengla, Yunnan 666303, P.R. ChinaPh:
>>> 15198676559achughes at xtbg.ac.cn
>>>
>>> Date: Mon, 6 May 2013 14:33:29 +1000
>>> Subject: Re: [Trop-R] Kernel Density Estimation Bootstrap
>>> From: lhodgson86 at gmail.com
>>> To: tropical-r at googlegroups.com
>>>
>>> Hi Christian,
>>> This formatting shows that the data has been read in as a single column
>>> with 'V1' as the column name and 'x,y' as the value of row 1, and so on:
>>>
>>>> test<-read.table("test.csv")> test
>>> V11 x,y
>>> 2 648501,89104003 641686,8917264
>>> 4 645984,89143285 647058,8913794
>>> 6 649659,89129257 649613,8912828
>>> .....
>>>
>>> You can check how many columns there are in a data frame using 'ncol':
>>>
>>> ncol(test)
>>> To troubleshoot, I would first try using read.csv:
>>>
>>> test=read.csv(test,as.is=TRUE)ncol(test)
>>>
>>> If this does not give you two columns, then I would check that the file
>>> really is in standard .csv format.
>>>
>>> Lauren
>>>
>>> On Mon, May 6, 2013 at 1:17 PM, Christian Gredzens
>>> <christian.gredzens at my.jcu.edu.au> wrote:
>>>
>>> Leila,
>>>
>>> Thanks for your reply. I'm using likelihood cross validation (CVh) instead
>>> of least squares cross validation (LSCV). To my knowledge adehabitatHR
>>> doesn't run CVh so I think I will need to write a script or find another
>>> program which can calculate CVh.
>>>
>>>
>>> I used GME from spatialecology.com to calculate all of my KDEs, but I don't
>>> think GME runs bootstrapping. So I'm trying to run it through the
>>> bootstrapping package in R. Here is what I need to do:
>>>
>>>
>>> 1) Create my spatial points layer
>>> =mydata
>>>
>>> 2) Run the bootstrapping script:
>>>
>>>> mydataboot<-boot(mydata, (KDE script), R=1000)
>>>
>>> mydata= my spatial points file
>>> (KDE script)= what formula to run the bootstrap on
>>>
>>> R=1000 = the number of iterations I would like to run
>>>
>>> The issue I'm having is getting the bootstrapping script to run the KDE
>>> formula=(KDE script)
>>>
>>> Cheers,
>>> Christian
>>>
>>> On Friday, May 3, 2013 12:58:55 AM UTC-7, Leila Brook wrote:
>>> Hi Christian,
>>>
>>> There is a package called adehabitatHR that does kernel density estimation
>>> with LSCV bandwidth using a function called kernelUD(). I don't know if
>>> this will is similar to what you want? You will need to have the data in
>>> UTM and in SpatialPoints or SpatialPointsDataFrame format, which you can do
>>> using the sp package.
>>>
>>>
>>>
>>> There is a great vignette for adehabitatHR that will help with data
>>> formatting and running the KDE. I exported the utilisation distribution
>>> for ArcGIS using writeRaster() in the raster package, but you can also
>>> export as contours.
>>>
>>>
>>>
>>> Cheers
>>>
>>> Leila
>>>
>>>
>>>
>>> ________________________________________
>>>
>>> From: tropi... at googlegroups.com [tropi... at googlegroups.com] on behalf of
>>> Stewart Macdonald [stewartm... at gmail.com]
>>>
>>> Sent: Friday, 3 May 2013 5:12 PM
>>>
>>> To: tropi... at googlegroups.com
>>>
>>> Subject: Re: [Trop-R] Kernel Density Estimation Bootstrap
>>>
>>>
>>>
>>> Hi Christian,
>>>
>>>
>>>
>>> What sort of data are you trying to import? A series of lat/longs that are
>>> in a text (or Excel) file? If so, the rGDAL library can be used to create
>>> spatial points:
>>>
>>>
>>>
>>> ###############
>>>
>>> library(rgdal)
>>>
>>> # if you don't already have this installed, you can do:
>>> install.packages('rgdal')
>>>
>>>
>>>
>>> # read in the data from a tab-delimited text file that has a header line
>>>
>>> rawPoints <- read.table('/data.csv', header=TRUE, sep='\t')
>>>
>>>
>>>
>>> # format as a SpatialPoint class and define the projection/datum (WGS84)
>>>
>>> q <- cbind(rawPoints$recordLon, rawPoints$recordLat)
>>>
>>> colnames(q) <- c("x", "y")
>>>
>>> qqq <- SpatialPoints(q, proj4string=CRS("+init=epsg:4326"))
>>>
>>> ###############
>>>
>>>
>>>
>>> Note: the above is a copied-and-pasted fragment from a working script of
>>> mine. I assume this fragment will work for you.
>>>
>>>
>>>
>>> I can't help you with your second question, and the answer to your third
>>> question will depend on the format of the bootstrap data (e.g., more
>>> points, polygons, raster).
>>>
>>>
>>>
>>>
>>>
>>> Hope this helps,
>>>
>>>
>>>
>>> Stewart
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>> On 03/05/2013, at 4:57 PM, Christian Gredzens <christian... at my.jcu.edu.au>
>>> wrote:
>>>
>>>
>>>
>>>> Hi All,
>>>
>>>>
>>>
>>>> I would like to run a bootstrap within R on a spatial dataset using a
>>>> kernel density estimation function. Can anyone help me with this? I am new
>>>> to R and thus have very little experience. It seems relatively easy to run
>>>> the actual bootstrap but I am having problems in the following areas:
>>>
>>>>
>>>
>>>> 1) I don't know how to import spatial data into R and assign it an
>>>> appropriate projection
>>>
>>>> 2) I need to setup a kernel function using a specific bandwidth
>>>> (likelihood cross-validation (CVh)) and create the script so it will run
>>>> within the bootstrap script
>>>
>>>> 3) I need to export the bootstrap data as an ArcGIS 10 file.
>>>
>>>>
>>>
>>>> Best Regards,
>>>
>>>> Christian Gredzens
>>>
>>>>
>>>
>>>> Christian Gredzens
>>>
>>>> MSc Student
>>>
>>>> School of Marine and Tropical Biology
>>>
>>>> James Cook University
>>>
>>>> Townsville, QLD, Australia 4811
>>>
>>>> Christian... at my.jcu.edu.au
>>>
>>>> Phone: 04 3875 3652
>>>
>>>>
>>>
>>>> --
>>>
>>>> An R group for questions, tips and tricks relevant to spatial ecology and
>>>> climate change.
>>>
>>>> All R questions welcome.
>>>
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>>>>
>>>
>>>
>>>
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>>>
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>>>
>>> All R questions welcome.
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>>>
>>>
>>
>> --
>> Roger Bivand
>> Department of Economics, Norwegian School of Economics,
>> Helleveien 30, N-5045 Bergen, Norway.
>> voice: +47 55 95 93 55; fax +47 55 95 95 43
>> e-mail: Roger.Bivand at nhh.no
>>
>
--
Roger Bivand
Department of Economics, Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: Roger.Bivand at nhh.no
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