With the help of heat vulnerability web maps and local data and statistics, I analyze the effects of "urban heat islands" in Las Vegas and how they affect water conservation efforts within the city.
Data Science and Water Conservation: How Analytics Can Smarten Up Our Water System
1. D A T A S C I E N C E A N D W A T E R
C O N S E R V A T I O N : H O W A N A L Y T I C S C A N
S M A R T E N U P O U R W A T E R S Y S T E M
P R E S E N T E D B Y : J A R E D B I L B E R R Y
2.
3.
4. So why is “Big Data” so
important, and why
should our community
be so curious about it?
5.
6. Data represents
trends, breaks down
patterns, and
explains habits
amongst the world's
populations.
It can be tailored to
study financial habits
of a certain factor of
society
Also, it demonstrates
psychological and
cultural aspects like
how to make a
certain economic or
financial decision.
7.
8. S O U T H E R N
N E V A D A H A S
R E L I E D
H E A V I L Y O N
D A T A T O
T A C K L E O N E
O F I T S
B I G G E S T
I S S U E S -
W A T E R
9. Grass
Desert landscaping / Xeriscape
Grass
Xeriscape
79.2
21.9
0
20
30
Study of conversion to
Xeriscape in single-
family homes =
The lawn uses 79
gallons per square foot
and the
Xeriscape uses 21.9
per square foot
(savings of nearly 57
gallons per square
foot). Data Scientists
use studies like this to
help create initiatives
like the WSL Rebate
Program!
Means annual use for each unit
Gallons per sq ft per year
Grass vs. Xeriscape
Study
13. Heat islands are urbanized areas
that experience higher
temperatures than outlying areas.
Heat Island Effect:
14.
15. Infrastructure – Rising temperatures increase demand of not
only infrastructure improvement projects (road damage,
maintenance, ect), but energy demand can result in issues
with power outages during summer months.
Economic Productivity – workers are less likely to work as
much during excessively hot conditions, and tourism can also
be affected due to weather conditions. (The Las Vegas Strip is
a perfect example of the Heat Island Effect).
Public Health – African Americans have higher rates of high
blood pressure, diabetes and obesity, which can directly be
affected by hotter weather.
16.
17. Cities MIN MED MAX
NLV 25,000 57,000 125,000
LV 18,000 52,000 146,000
HEND 22,000 70,000 125,000
RENO 19,000 59,000 135,000
25,000
18,000
22,000
19,000
57,000
52,000
70,000
59,000
125,000
146,000
125,000
135,000
0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000
NLV
LV
HEND
RENO
INCOME DISTRIBUTION
MAX MED MIN
From here, we can take
a data set explaining the inc-
ome distribution of Nevada
residents and turn it into a graph.
As we can see, every single person
in the minimum income category
is either near or below the poverty level for Las Vegas.
21. 0
47,589.00
14,519.00
32,750.00
17,330.00
30,469.00
19,669.00
21,047.00
22,267.00
34,803.00
31,891.00
34,034.00
27,072.00
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
0 2 4 6 8 10 12 14
Per
5
thousand
Dollars
($)
Median household income in the hottest Las Vegas
neighborhoods
Linear (Series1)
0
24,845.31
36,668.28
18,590.80
14,233.54
13,871.34
21,096.10
13,951.55
10,620.60
8,270.39
22,076.04
11,996.03
17,050.48
0
5000
10000
15000
20000
25000
30000
35000
40000
0 2 4 6 8 10 12 14
Population Density (Sq mi)
Linear (Series1)
Not only are the hottest neighborhoods some of the poorest, but they are also the densest.
These areas consist primarily of minority groups with many speaking English as a second language.
Average Income:
27,786.67
22. 0
40,721
150,833
187750
139545
66818
111293
142140
87404
143553
79196
116908
250001
0
50000
100000
150000
200000
250000
300000
0 2 4 6 8 10 12 14
Per
Thousand
Dollars
($) Median Household Income (Coolest neighborhoods)
1154
3835
6062
1577
4852
2900
62
2456 2377
2768
1702
749
0
1000
2000
3000
4000
5000
6000
7000
0 2 4 6 8 10 12 14
Population Density (Sq mi)
Average income:
126,347
In addition to being cooler overall, these neighborhoods show high economic growth and are spaced apart in a
way that reduces the affect of Vegas heat. Also, more parks, ponds and springs are in these areas.
23. What are the findings?
-Dense, low-income neighborhoods tend to have hotter
Overall temperatures per square mile.
-The “Heat Island Effect” doesn’t just affect
these areas, it can cause a ripple effect –
making the entire valley hotter.
-Changing climates, lack of vegetation,
Growing populations, and concrete and
Impermeable surfaces lead to hotter neighborhoods
-Trees, solar radiation, shade structures and
“green roofs” can help prevent excessive heat
In urban areas.
24. - D A T A S E T
- S T A T I S T I C A L
M O D E L
- M A T H E M A T I C A L
D I A G R A M
- D I S P L A Y E D
C O O R D I N A T E S
O F T W O S E T S O F
D A T A
C O N G R A T S ,
Y O U G U Y S A R E
A L L D A T A
S C I E N T I S T S ! ( O
R A T L E A S T
H A V E W H A T
Y O U N E E D T O
G E T S T A R T E D
I N D A T A
S C I E N C E ! )
… S O , W H A T D O
W E D O W I T H A L
O F T H I S ?
Imagine waking up, going to wash your face, take and shower – and there’s no water. What would you do? What would be going through your mind? Most importantly, why and how did this happen? (ask audience to participate). From here, explain how Southern Nevada has had to ask itself these same questions for years. As a matter of fact, Lake Mead (currently) has lost about half of its water supply over the last 20-30 years. Think of a half full bathtub, that’s us right now.
The reason I asked these questions was to get you guys thinking about curiosity. Aren’t we all curious? We most likely don’t realize it, but curiosity has led to some of the biggest achievements in the world. Specifically, we definitely want to be curious about water and the data behind it. And without even knowing it, you guys just took a step in the direction of data science: Curiosity.
1.) Opportunities – we can find out how to invest in new ideas, and engage in new possibilities. Analytics and data science can seem a little confusing at first right? We take this data and then what, what formula do I need to know again? The fact of the matter is that data science can be engaging and easy, when we break it down. STEM (Science, Technology, Engineering and Math) are heavily pushed across the country for financial and economical reasons. But the version of math we’ll be using today (Statistics) is what companies like Google, Amazon and Facebook (and essentially every tech and financial firms) are in desperate need for. And after this presentation, the door will be opened up for all of you, all you have to do is walk through it.
A trend is a change over time - Upward or downward? We use trends to analyze the importance of projects, initiatives and resources within an economy.
Data professionals, Engineers, and Scientists are working consistently to make sure to not only maintain what we do have; but that we create new trends that can preserve our water systems for you, your children, and your children's’ children. That white line that you see in the background is the drop I spoke about earlier with Lake Mead. The line going across is something real simple – a trend.
What is Xeriscape? We analyze this data to create programs like WSL to help conserve water in the valley. Data Scientists use sets like these the analyze the effects or water use and conservation over time.
This is a map of the urban daytime temperatures throughout the united states. In other words, which states are the hottest on a consistent basis – with a heavy focus on the overall urban heat island index
Las Vegas is (on average) hotter than Los Angeles and Phoenix – two western cities with bigger populations and economies. (Phoenix has 4 + million people and LA has 10 + million people!) But why?
Vegas is getting hotter. We take this, and look at our drought situation, and we’ve got a problem. But problems are meant to solved. By people like you guys in the audience.
So what is the heat island effect? We all know that Vegas in hot, but we often don’t realize that certain areas in the city are significantly hotter than others.
We can see that Industrial, Urban and downtown areas have the highest surface temperatures on average within the Las Vegas valley. In addition to this, Suburban areas tend to have more ponds, parks and rural areas with heavy greenery. But why does this affect us, specifically?
So what now? We have our topic, and now we can start to examine data sets to figure out a solution.
What I did here, was take a data set, and plug in the average, minimum, median, and maximum neighborhoods in Nevada. From there, I turned it into a basic bar graph.
After gathering this data, I went to excel and put together a scatter plot, showing the exaggerated trends over the course of time in said communities.
So what did we just do? You guys have an inside look into how data engineering, quantitative analysis and even Machine Learning works! You guys all have the skills needed to have a head start in anything analytics related. So, what would a data scientist do with this information?
This type of refined data allows policymakers to develop responses that are targeted at the most important water problems, that can be tailored to meet needs for individualized communities. In this case, we could suggest a capital improvement project to create green infrastructure improvements into regular street upgrades. Essentially, an impact investment that provides heat reducing effects in the hottest Las Vegas neighborhoods.
Learn. Earn. Return. I think the most important thing I can tell you guys is that this presentation isn’t about me at all. It’s about the greatness in you. I just gave you the basics. You have ahead start in analytics and really any type of data, comp sci, quantitative or technical career. When I look at this crowd, I see a future to get excited about.