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Illegal Border Crossers and Wildfires in AZ Geoffrey Krassy GEOG 594A Prof Todd Bacastow.

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Presentation on theme: "Illegal Border Crossers and Wildfires in AZ Geoffrey Krassy GEOG 594A Prof Todd Bacastow."— Presentation transcript:

1 Illegal Border Crossers and Wildfires in AZ Geoffrey Krassy GEOG 594A Prof Todd Bacastow

2 The Question…  Are the occurrence, rates and/or severity of wildfires in southern Arizona affected by the frequency of smuggling operations which occur. Soldier Basin fire seen from Nogalas Intl Airport, AZ (Images from KVOA.com)

3 The problem of wildfires  Illegal immigration and smuggling is an endemic problem along the US-Mexico border.  The flow of contraband (both human and other) through the Tucson sector in Arizona varies dependent on numerous factors within the United States and Mexico.  The desert Southwest is also highly susceptible to brush and wildfires.  It has been shown that some of these fires have been deliberately set in order to draw attention away from another portion sector.

4 Study area  Red outline is the study area. It is the lower half of the Office of Border Patrol’s Tucson Sector.

5 Datasets  Primary  CBP Apprehension Data  Group size, location and time  Aggregate by year (2009-2013)  Clipped to study area  Datum: WGS84  MODIS Thermal Anomalies & Fires  Aggregate by year  Datum: NAD1983  Monitoring Trends in Burn Severity (MTBS), National MTBS Burned Area Boundaries Dataset  Datum: NAD 1983  Background  CBP Administrative Borders, V10  BaseMap – ESRI World Topo

6 Software VersionDeveloperWebsite ArcGIS 10.2ESRI http://www.esri.com/software/arcgis

7 Pre-processing: ArcGIS Optimized Hot Spot Analysis Set for 50% Transparency Set Symbology GiBin for 3 Classes Red indicates 95% + confidence that the clustering is significant ArcGIS Repeat for each data-set GoTo Visual Comparison CBP Apprehension Data

8 MODIS- Thermal Anomalies & Fire Overview MTBS (Monitoring Trends in Burn Severity) Overview

9 Apprehensions  Seems like a (mostly) random distribution.  Need something to find the trends.

10 Optimized Hot Spot Analysis  “Given incident points, creates a map of statistically significant hot and cold spots using the Getis-Ord Gi* statistic. It evaluates the characteristics of the input feature class to produce optimal results.” (ArcGIS 10.2 Help)  Analysis, in this case, is based on apprehended group size, in addition to geographic location.  It identifies the “non-random” elements.  Non-random implies a regular route.  Note: these are the groups apprehended, not necessarily the ones who started fires.

11 Sample Results 2011

12 A closer look…

13 And closer….

14 Conclusions  Visual correlation performed for every fire noted from 2009-20012  Every notable fire within 25 NM of the border was within 1 NM of an Apprehension HotSpot.  Considering that National Park Service claims 90% of wildfires are of human origin, and that the fire locations are functionally depopulated…  It is likely that most of the wildfires in southern Arizona are caused by illegal border crossers.

15 Questions?


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