geographic patterns and profiling of illegal land border crossings d. kim rossmo quint c. thurman
TRANSCRIPT
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Geographic Patterns and Profiling of Illegal Land Border Crossings
D. Kim RossmoQuint C. Thurman
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Border Control
Geographic range Porous nature US national security Significant challenge
Rugged terrain of El Paso border
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The Illegal Border Crossing “Arms Race”
Ground sensor and UAV
Fencing and electronic gate
Trucks in Rio Grande canyon
Inner tubes along the Rio Grande
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Berlin Wall
10,315 days August 1961 to November 1989 East / West Berlin border 27 miles West Berlin border 96 miles 12-foot wall, 302 watch towers, 20 bunkers 192 deaths, 200 shooting injuries 5,000 escapes (3.4 per week)
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US Border Patrol Sectors
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Texas-MexicoBorder 1,000 miles 52% of
southern border
1,933 miles 50% federal
land
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Theoretical Perspective Criminal behavior
Bounded rationality Shaped by personal and environmental factors
Migration theory Origin (push) factors Destination (pull) factors) Distance (effort, time, money)
Cost/benefit (risk/reward) analysis framework
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Illegal Border Crossing Requirements
Trip origin Border Staging area Crossing Landing Trip destination
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Premise Identify border crossing factors
Facilitating Inhibiting
Determine features related to probability of illegal border movement Environmental Physical
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US Border Patrol Data
2001 to 2004 (4 years) 1 to 1.6 million cases annually in the US 20 to 25% of these cases are in Texas Laredo, McAllen, Del Rio, Marfa,
and El Paso Sectors
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Dependent Illegal Texas-Mexico land border crossings
Independent Physical geography Human geography
Research Variables
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Preliminary Focus Area
Del Rio Border Patrol Sector
Val Verde, Kinney, & Maverick Counties
111 Landmark Mile Markers (170 miles)
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Physical Geography
Hydrography Terrain Vegetation Temperature (day and night)
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Hydrography Types of features
Streams Rivers Lakes Reservoirs
Data sources US Census (USA) INEGI (Mexico)
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Terrain (USGS DEM) Extent
All counties Mexico overlap
Primary Output Elevation Slope Aspect Hillshade
Identification Ravines Gullies
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Vegetation Types of features
Brush Crops Parks Woods
Data sources TPWD (US) INEGI (Mexico)
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Temperature
Monthly normals Minimum Maximum
Annual normals Mean
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Human Geography Variables
Major transportation Population density Urban developments Political region Additional features
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Major Transportation Types
Airports Railroads Roads Bridges
US data sources US Census TCEQ
Mexico data sources GeoCommunity
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Population Density & Urban Development
US data 2000 US Census All counties
Mexico Data 1990 Census Mexico
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October 1, 2000 - August 17, 2004All Entries
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000V
-1
V-5
V-9
V-1
3
V-1
7
V-2
1
V-2
5
V-2
9
V-3
2
V-3
6
V-3
9
V-4
1
V-4
3
V-4
7
K-3
K-7
M-2
.5
M-6
M-0
9 A
M-1
3
M-1
7
M-2
1
M-2
5
M-2
9
M-3
3
M-3
7
M-4
1
M-4
5
Landmark Mile Marker(North to South Order)
En
trie
s
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October 1, 2000 - August 17, 2004Criminal Disposition Entries
0
10
20
30
40
50
60
70
80
90
100
V-1
V-5
V-9
V-1
3
V-1
7
V-2
1
V-2
5
V-2
9
V-3
2
V-3
6
V-3
9
V-4
1
V-4
3
V-4
7
K-3
K-7
M-2
.5
M-6
M-0
9 A
M-1
3
M-1
7
M-2
1
M-2
5
M-2
9
M-3
3
M-3
7
M-4
1
M-4
5
Landmark Mile Marker(North to South Order)
En
trie
s
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Del Rio Illegal Border Crossings
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0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
1 21 41 61 81 101
Landmarks
Cro
ss
ing
sDel Rio Illegal Border Crossings
(Cumulative %)
G = 0.64ID = 0.49
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Del Rio Sector – All Illegal Entries
2000 14,520
2001 86,974
2002 61,974
2003 53,744
2004 37,534
2000-04254,717
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All Entries
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Del Rio Sector – Criminal Entries
2000 -
2001 5
2002 129
2003 289
2004 162
2000-04 585
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Criminal Entries
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Density of Del Rio Sector Illegal Entries
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Entries by MonthAll Entries
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
Month
En
trie
s
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Entries by MonthCriminal Disposition Entries
0
10
20
30
40
50
60
70
80
Month
En
trie
s
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Entries by Day of MonthAll Entries
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31
Day of Month
En
trie
s
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Entries by Day of WeekAll Entries
30,000
32,000
34,000
36,000
38,000
40,000Sunday
Monday
Tuesday
WednesdayThursday
Friday
Saturday
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Entries by Day of WeekCriminal Disposition Entries
40
50
60
70
80
90
100
110Sunday
Monday
Tuesday
WednesdayThursday
Friday
Saturday
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Time of Entry - All Entries
4000
8000
12000
16000
0:00
1:00
2:00
3:00
4:00
5:00
6:00
7:00
8:00
9:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
18:00
19:00
20:00
21:00
22:00
23:00
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Time of Entry - Criminal Disposition Entries
0
5
10
15
20
25
30
35
40
45
500:00
1:00
2:00
3:00
4:00
5:00
6:00
7:00
8:00
9:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
18:00
19:00
20:00
21:00
22:00
23:00
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Residence Country (Excluding Mexico)
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US or Mexico State of Birth
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Gender
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Apprehension Age
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Distance to United States Urban Areas
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Distance to Mexico Urban Areas
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Slope Least Cost Path
Cost-weighted distance (higher slope = greater cost)
Cost-weighted direction (least cost direction to source)
Least cost path (to rural highway segments)
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Combined Slope Cost-Weighted Distance
Top 10 criminal disposition entry Landmark Mile Markers
Weighted by number of criminal disposition entries
323 total entries
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Slope Cost Distance Analysis
Travel across terrain values is more difficult (higher “cost”)
Border areas with low slope cost values are attractive to illegal border crossers
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Elevation Change Analysis
Border areas with higher elevation on the Mexico side are attractive to illegal border crossers
Elevation differentials allows for surveillance of US Border Patrol vehicles
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Viewshed Analysis
The viewshed (line of sight) identifies all locations visible from a given point
Areas with low viewshed values are attractive to illegal border crossers due to low detection risk
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Illegal Border Crosser Population Estimates
Official estimates: +10 to 50% Line officer estimates: +100%
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Capture-RecaptureAnalysis P
S1
S2O
P = S1S2
O
?
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Scholarly Outcomes
Illegal movements International migration Spatial displacement Natural and built factors Microlevel environmental influences
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Practical Products
US Border Patrol operations Unidentified crossing points Displacement anticipation Criminal and drug interdiction Counter-terrorism applications Training