Tag Archives: Sava

Forthcoming MapScore Paper!

Our MapScore paper is now in press at Transactions in GIS! From the abstract:

The MapScore project described here provides a way to evaluate probability maps using actual historical searches.  In this work we generated probability maps based on the statistical Euclidean distance tables from ISRID data (Koester, 2008), and compared them to Doke’s (2012) watershed model. Watershed boundaries follow high terrain and may better reflect actual barriers to travel. We also created a third model using the joint distribution using Euclidean and watershed features. On a metric where random maps score 0 and perfect maps score 1, the ISRID Distance Ring model scored 0.78 (95%CI: 0.74-0.82, on 376 cases). The simple Watershed model by itself was clearly inferior at 0.61, but the Combined model was slightly better at .81 (95%CI: 0.77-0.84).

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Paul Doherty's Research Page

Just a quick note to highlight Paul Doherty's new research page.  It includes:

  • Overview of his research
  • Publications list
  • Software & Datasets page, including links to MapSAR and discussion groups.
  • Linkspage with a SAR & GIS bibliography including the memorably titled
    • Heggie, Travis W, and Michael E Amundson. 2009. “Dead Men Walking: Search and Rescue in US National Parks.” Wilderness & Environmental Medicine.
    • And the humorously mangled:  Is, Information, Releasable To, and Foreign Nationals. “Search and Rescue Optimal Planning System ( SAROPS ).” Training 2.
    • And three articles it sounds like I should read soon:
      • Jobe, T.R., and P.S. White. 2009. “A New Cost-distance Model for Human Accessibility and an Evaluation of Accessibility Bias in Permanent Vegetation Plots in Great Smoky Mountains National Park , USA.” Journal of Vegetation Science: 1099–1109.
      • Miller, Harvey J., and Scott a. Bridwell. 2009. “A Field-Based Theory for Time Geography.” Annals of the Association of American Geographers 99 (1) (January 8): 49–75. link
      • Pingel, Thomas J. 2011. “Estimating an Empirical Hiking Function from GPS Data.” Sports Medicine: 1–3.

At Mason we're collaborating with Paul to test a Watershed-Distance model developed by his research group.  Based on 58 tests run so far by Elena Sava on MapScore, this simple model scores 0.55.  Not bad for a model that doesn't yet discriminate by category (or any other feature).  Elena just finished a multivariate model combining Watersheds with the more usual crows'-flight distance, and we will begin testing that soon.