
Figure 1: Consequences of human activity on urban development and natural resources
Year |
Las Vegas City |
Residential North |
1984 |
0,240437503 |
0,151226618 |
1985 |
0,264341069 |
0,157865360 |
1986 |
0,271480118 |
0,155998180 |
1987 |
0,289065099 |
0,169213765 |
1988 |
0,282803632 |
0,210600120 |
1989 |
0,286535270 |
0,213982186 |
1991 |
0,303956828 |
0,219973707 |
1991 |
0,298541690 |
0,225406972 |
1992 |
0,301994751 |
0,214975264 |
1993 |
0,293683986 |
0,208605453 |
1994 |
0,304328745 |
0,221313177 |
1995 |
0,298240329 |
0,212630331 |
1996 |
0,309779114 |
0,222464495 |
1997 |
0,284870821 |
0,225816809 |
1998 |
0,291493024 |
0,223026329 |
1999 |
0,296067339 |
0,238731572 |
2000 |
0,304491317 |
0,246826836 |
2001 |
0,311488540 |
0,254509105 |
2002 |
0,314104190 |
0,259835794 |
2003 |
0,299101833 |
0,263285485 |
2004 |
0,299139369 |
0,249477866 |
2005 |
0,296761075 |
0,237934169 |
2006 |
0,305053585 |
0,250044464 |
2007 |
0,301298833 |
0,256201407 |
2008 |
0,314321877 |
0,261825498 |
Table 1: The quantization error in the SOM output (SOM-QE) as a function of the image year and geographic ROI
Fit Parameter |
Las Vegas City |
Residential North |
Slope (b1) |
1,554 |
40,331 |
Intercept (b0) |
-28,077 |
-78,286 |
r2 |
0,4776 |
0,7995 |
Table 2: Goodness of the linear fits to SOM-QE distributions for each geographical ROI
Linear Regression |
Las Vegas City |
Residential North |
t |
88,98 |
33,45 |
df |
(1, 24) |
(1, 24) |
p |
<.001 |
<.001 |
Table 3: Linear regression statistics with Studentʹs t, degrees of freedom (df) and probability limits (p) for each geographical ROI
Year |
Visitors (in millions) |
Population (in K) |
1984 |
12,8000 |
191,0000 |
1985 |
14,2000 |
197,0000 |
1986 |
15,2000 |
204,0000 |
1987 |
16,2000 |
226,0000 |
1988 |
17,2000 |
240,0000 |
1989 |
18,1000 |
266,0000 |
1991 |
20,9000 |
276,0000 |
1991 |
21,3000 |
298,0000 |
1992 |
21,9000 |
310,0000 |
1993 |
23,5000 |
330,0000 |
1994 |
28,2000 |
352,0000 |
1995 |
29,0000 |
374,0000 |
1996 |
29,6000 |
406,0000 |
1997 |
30,4000 |
423,0000 |
1998 |
30,6000 |
448,0000 |
1999 |
33,8000 |
466,0000 |
2000 |
35,8000 |
483,0000 |
2001 |
35,0000 |
506,0000 |
2002 |
35,0000 |
521,0000 |
2003 |
35,5000 |
535,0000 |
2004 |
37,3000 |
560,0000 |
2005 |
38,6000 |
576,0000 |
2006 |
38,3000 |
592,0000 |
2007 |
37,5000 |
603,0000 |
2008 |
39,5000 |
608,0000 |
Table 4: Visitor and population statistics for Greater Las Vegas across the years of the study period
Fit Parameter |
Visitors |
Population |
Slope (b1) |
1,1828 |
19,0723 |
Intercept (b0) |
-2,333 |
-3766 |
r2 |
0,9657 |
0,9955 |
Table 5: Goodness of the linear fits to visitor and population statistics
Linear Regression |
Visitors |
Population |
t |
15,70 |
14,20 |
df |
(1, 24) |
(1, 24) |
p |
<.001 |
<.001 |
Table 6: Linear regression statistics with Studentʹs t, degrees of freedom (df) and probability limits (p) for visitor and population statistics
|
SOM-QE Residential North vs Population |
SOM-QE Las Vegas City vs Visitors |
R |
15,70 |
14,20 |
df |
(1, 24) |
(1, 24) |
p |
<.001 |
<.001 |
Table 7: Correlation statistics with Pearson coefficients R and the associated df and probability limits p
Figure 1: Consequences of human activity on urban development and natural resources
Figure 2: SOM [33] prototype with sixteen model neurons in a fully connected functional architecture
Figure 3: Satellite image examples showing the residential North of Las Vegas in 1984 and 2008
Figure 4: Linear fits to SOM-QE trends as a function of the image year and ROI
Figure 5: Linear fits to visitor (top) and population (bottom) statistics for Greater Las Vegas
Figure 6: Correlations between SOM-QE and population (top) and visitor (bottom) statistics
Figure 7: Economic growth vs water availability (University of Nevadaʹs Center for Gaming Research Annual Statistics and US Department of Interiorʹs Bureau of Reclamation Hoover Dam Control Room statistics for the years 1984-2008)
Tables at a glance
Figures at a glance