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

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Presentation transcript:

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

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)

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.

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

Datasets  Primary  CBP Apprehension Data  Group size, location and time  Aggregate by year ( )  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

Software VersionDeveloperWebsite ArcGIS 10.2ESRI

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

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

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

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.

Sample Results 2011

A closer look…

And closer….

Conclusions  Visual correlation performed for every fire noted from  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.

Questions?