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GEOSTATS: Summary of roadkill analysis along a highway segment

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  • Kari_Gunson@pch.gc.ca
    About two months ago I posed a question to the listserver, to help in our spatial analysis of roadkills along the Trans-Canada Highway in Banff National Park.
    Message 1 of 1 , Mar 29, 2000
      About two months ago I posed a question to the listserver, to help in our
      spatial analysis of roadkills along the Trans-Canada Highway in Banff National
      Park. Here is a long overdue summary of the responses I received.


      Hi I am working on a research project that studies roadkills on the Trans-Canada
      Highway, a linear vector spanning over 141 miles. I am looking at hotspots, or
      clusters of roadkills along the highway, from small to large mammals. I am
      starting with a simple analysis that looks if the kills are related to the
      access points, (breaks in the wildlife fence). Firstly, I was wondering if
      someone knows a script that I can use that puts random points on my linear
      vector, so I can look at a Chi-square test or Hines test for randomness. (Do I
      need random points along the line vector or would a ploygon suffice?) Also once
      I have tested for clusters, or aggregation, how do I link these clusters to the
      access points. I am looking at a simple two step analysis, for testing for
      clusters, and are these clusters related to the access points. It would be
      great if someone could lead me in the right direction..............

      Thanks Kari

      Response 1:

      You might want to look at "local statistics" and K functions. The journal
      Geographical Analysis
      has a number of articles on the subject.

      Art Getis

      Response 2:

      1. If you will test against differences between two distributions, then both
      your distributions must be comparable. Therefore you need random points on your
      linerar vector.

      2. Is the highway absolutely linear like a line between two points? In this
      case you can use a simple worksheet function for random number generation like
      in Excel. For testing you should only compare the coordinates of one axis
      (west-east or north-south), its useful to choose the axis with the greatest

      3. If the highway is not absolutely linear you can make a workaround. First
      you should make a buffer around your highway with a very small distance/radius.
      After buffering use a random number generator for polygons. For ArcView exists
      a simple script, which you can find on the ESRI-Website: http://www.esri.com
      Because the lateral extension of the buffer is very small I think you can
      neglect it in all cases where you will find very great differences between both
      the distributions. For testing you should only compare the coordiantes of one
      axis (west-east or south-north), its useful to choose the axis with the greatest

      4. To link the clusters with your access points you can go in different ways.
      For instance you can make buffers with a defined radius around your access
      points and do an identity operation. You will find some tools in Atlas*GIS
      (access points) or ArcView (XTools-Extension, Animal Movement Extension; both
      you can find on ESRI's site). I think the Animal Movement Extension is very
      useful for your aims.

      5. I think the best way to compare your distributions is to perform a
      nearest-neighborhood analysis between your access points and the road kills
      compared with the nearest neighborhood distances between your access points and
      the random points.

      hope this helps
      Dr. Reinhard Klenke
      Society for Nature Conservation and Landscape Ecology (GNL)
      phone 49-39822-20 474
      fax: 49-39822-20 474

      Response 3:

      Hi Kari,

      I'm not really an expert in spatial statitics but it seem to me that you might
      apply the Ripley's K statisitcs to your data. I recomment you to take a look
      athe following article:

      O'Driscoll, R.L. 1998. Description of spatial pattern in seabird distributions
      along line transects using neighbour K statistics. Mar. Ecol. Prog. Ser.

      Also Boots, B.R. and A. Getis. 1988. Point Pattern Analysis. SAGE publications.
      give some examples of the application of measures of dispersion in one
      dimension. As for the software, well the only one I know is available is the
      S-plus and you have to add the libraries Splancs and Spatial. THere is a
      student version of S-plus for a little less than $100 dollars and libraries can
      be downloaded from the internet. However, I am not sure if you can use the
      software for one dimentsion directly, most likely you might need to make some
      modifications and obviously you will need to study the S-plus language for that.
      Anyway, hope this informations is of some help to you. Good luck,

      Jose Alcantara
      School of Forestry, Wildlife and Fisheries
      Louisiana State University
      Baton Rouge, La.

      Response 4:

      First of all numbers from a uniform (0,1) random number generator can be mapped
      onto any stretch of highway. With as many points from the random generator as
      there are road kills you can then create two empirical distributions and test
      for their being the same with the Kolmogorov-Smirnov statistic. This will
      simply tell you that the road kills are (not) from a uniform distribution along
      the highway.

      You actually do not have to generate the points. The cumulative distribution
      along the highway has a slope of 1/L, where L is the length of the highway
      segment. i.e. F=x/L, 0<=x<=L. Now make an empirical distribution of the
      roadkills and use the K-S one sample test statistic.

      You may also look at gap sizes and their distribution to obtain a 'best' Pearson
      type distribution for waitng times, except your waiting time is simply the
      distance between kills.

      You may also divide the road into a set of segments and fill in the counts for a
      one dimensional contingency table.

      Lastly, you can use the scan statistic found in CLUSTER, CLUSTER can be
      downloaded from CDC/ATSDR.

      Send me your data, and I will find an unwilling student to have a look at them.
      I wrote CLUSTER along with three others.

      Sincerely yours,

      Wanzer Drane
      Professor of Biostatistics
      USC School of Public Health, 205
      Columbia, SC 29208

      Response 5:

      Which software are you using for the analysis? I can give you some hints on
      Avenue (ArcVIew script language) and S+, although I have no premade script.
      Shouldn't be too difficult, though.

      You can just transform all your observation in distances from the starting point
      in the hwy, and then you just have to draw a random number.

      BTW, where on the Hwy are you working? Is it the Banff stretch?

      Marco Albani
      PhD Candidate
      Dept. of Forest Sciences - UBC

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