Lalitesh Katragadda: Making maps to fight disaster, build economies

36,813 views ใƒป 2010-01-13

TED


ืื ื ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ืœืžื˜ื” ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ.

ืžืชืจื’ื: Shaike Katz ืžื‘ืงืจ: Sigal Tifferet
00:16
In 2008, Cyclone Nargis devastated Myanmar.
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ื‘ 2008, ืกื•ืคืช ื”ืฆื™ืงืœื•ืŸ ื ืจื’ื™ืก ื”ืจืกื” ืืช ืžื™ื™ืื ืžืจ.
00:21
Millions of people were in severe need of help.
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ืžื™ืœื™ื•ื ื™ ืื ืฉื™ื ื ื–ืงืงื• ืœืขื–ืจื” ื‘ื“ื—ื™ืคื•ืช.
00:25
The U.N. wanted to rush people and supplies to the area.
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ื”ืื•"ื ืจืฆื” ืœื”ื‘ื™ื ืื ืฉื™ื ื•ืืกืคืงื” ืœืื™ื–ื•ืจ.
00:29
But there were no maps, no maps of roads,
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ืื‘ืœ ืœื ื”ื™ื• ืžืคื•ืช, ืœื ืžืคื•ืช ื“ืจื›ื™ื,
00:32
no maps showing hospitals, no way for help to reach the cyclone victims.
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ืœื ืžืคื•ืช ืฉืžืจืื•ืช ื‘ืชื™ ื—ื•ืœื™ื, ืœื ื”ื™ืชื” ื“ืจืš ืœืขื–ืจื” ืœื”ื’ื™ืข ืœื ืคื’ืขื™ ื”ืฆื™ืงืœื•ืŸ.
00:37
When we look at a map of Los Angeles or London,
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ื›ืฉืื ื—ื ื• ืžืกืชื›ืœื™ื ื‘ืžืคื” ืฉืœ ืœื•ืก ืื ื’'ืœืก, ืื• ืœื•ื ื“ื•ืŸ
00:40
it is hard to believe
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ืงืฉื” ืœื”ืืžื™ืŸ
00:43
that as of 2005, only 15 percent of the world
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ืฉื ื›ื•ืŸ ืœ 2005 ืจืง 15 ืื—ื•ื– ืžื”ืขื•ืœื
00:46
was mapped to a geo-codable level of detail.
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ืžื•ืคื” ืœืจืžืช ืคื™ืจื•ื˜ ื”ืžืืคืฉืจืช ืงื™ื“ื•ื“ ื’ื™ืื•ื’ืจืคื™ (ืงืจื™ื ืข"ื™ ืžื—ืฉื‘)
00:49
The U.N. ran headfirst into a problem
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ื”ืื•"ื ื”ืชืคืจืฅ ืœืชื•ืš ื‘ืขื™ื™ื”
00:52
that the majority of the world's populous faces:
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ืฉืจื•ื‘ ืื•ื›ืœื•ืกื™ื™ืช ื”ืขื•ืœื ืขื•ืžื“ืช ื‘ืคื ื™ื”:
00:54
not having detailed maps.
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ื—ื•ืกืจ ื‘ืžืคื•ืช ืžืคื•ืจื˜ื•ืช.
00:56
But help was coming.
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ืื‘ืœ ื”ืขื–ืจื” ื”ื™ืชื” ื‘ื“ืจืš.
00:58
At Google, 40 volunteers
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ื‘ื’ื•ื’ืœ, 40 ืžืชื ื“ื‘ื™ื
01:00
used a new software
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ื”ืฉืชืžืฉื• ื‘ืชื•ื›ื ื” ื—ื“ืฉื”
01:03
to map 120,000 kilometers of roads,
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ืœืžืคื•ืช 120,000 ืงื™ืœื•ืžื˜ืจ ืฉืœ ื“ืจื›ื™ื,
01:06
3,000 hospitals, logistics and relief points.
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3000 ื‘ืชื™ ื—ื•ืœื™ื, ื•ื ืงื•ื“ื•ืช ืœื•ื’ื™ืกื˜ื™ืงื” ื•ืกื™ื•ืข.
01:09
And it took them four days.
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ื•ื–ื” ืœืงื— ืœื”ื ืืจื‘ืขื” ื™ืžื™ื.
01:11
The new software they used? Google Mapmaker.
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ื”ืชื›ื•ื ื” ื”ื—ื“ืฉื” ื‘ื” ื”ื ื”ืฉืชืžืฉื•? Mapmaker ืฉืœ ื’ื•ื’ืœ.
01:14
Google Mapmaker is a technology that empowers each of us
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Mapmaker ืฉืœ ื’ื•ื’ืœ ื”ื•ื ื˜ื›ื ื•ืœื•ื’ื™ื” ืฉืžืืคืฉืจืช ืœื›ืœ ืื—ื“ ืžืืชื ื•
01:17
to map what we know locally.
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ืœืžืคื•ืช ืžื” ืฉืื ื—ื ื• ืžื›ื™ืจื™ื ืžืงื•ืžื™ืช.
01:20
People have used this software
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ืื ืฉื™ื ื”ืฉืชืžืฉื• ื‘ืชื•ื›ื ื” ื”ื–ื•
01:22
to map everything from roads to rivers,
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ืœืžืคื•ืช ื›ืœ ื“ื‘ืจ ืžื“ืจื›ื™ื ืขื“ ื ื”ืจื•ืช,
01:24
from schools to local businesses,
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ืžื‘ืชื™ ืกืคืจ ืขื“ ื‘ืชื™ ืขืกืง ืžืงื•ืžื™ื™ื,
01:27
and video stores to the corner store.
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ื•ืžื—ื ื•ื™ื•ืช ื•ื•ื™ื“ืื• ืœืคื™ืฆื•ืฆื™ื”.
01:30
Maps matter.
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ืžืคื•ืช ื”ืŸ ื—ืฉื•ื‘ื•ืช.
01:32
Nobel Prize nominee Hernando De Soto
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ื”ืžื•ืขืžื“ ืœืคืจืก ื ื•ื‘ืœ ื”ืจื ื ื“ื• ื“ื” ืกื•ื˜ื•
01:34
recognized that the key to economic liftoff
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ื–ื™ื”ื” ืฉื”ืžืคืชื— ืœื”ืžืจืื” ื›ืœื›ืœื™ืช
01:36
for most developing countries
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ืขื‘ื•ืจ ืจื•ื‘ ื”ืžื“ื™ื ื•ืช ื”ืžืชืคืชื—ื•ืช
01:38
is to tap the vast amounts of uncapitalized land.
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ื”ื•ื ื ื™ืฆื•ืœ ื›ืžื•ื™ื•ืช ื”ืงืจืงืข ื”ืœื ืžื ื•ืฆืœื•ืช.
01:41
For example, a trillion dollars
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ืœื“ื•ื’ืžื”,
01:44
of real estate remains uncapitalized in India alone.
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ืจืง ื‘ื”ื•ื“ื• ื™ืฉ ื˜ืจื™ืœื™ื•ืŸ ื“ื•ืœืจ ืฉืœ ื ื“ืœ"ืŸ ืœื ืžื ื•ืฆืœ.
01:47
In the last year alone,
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ื‘ืฉื ื” ื”ืื—ืจื•ื ื” ื‘ืœื‘ื“,
01:49
thousands of users in 170 countries
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ืืœืคื™ ืžืฉืชืžืฉื™ื ื‘ 170 ืืจืฆื•ืช
01:53
have mapped millions of pieces of information,
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ืžื™ืคื• ืžื™ืœื™ื•ื ื™ ืคื™ืกื•ืช ืžื™ื“ืข,
01:56
and created a map of a level of detail never thought viable.
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ื•ื™ืฆืจื• ืžืคื” ื‘ืจืžืช ืคื™ืจื•ื˜ ืฉืžืขื•ืœื ืœื ื ื—ืฉื‘ื” ืืคืฉืจื™ืช.
01:59
And this was made possible by
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ื•ื–ื” ื”ืชืืคืฉืจ ื‘ืืžืฆืขื•ืช
02:01
the power of passionate users everywhere.
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ื”ื›ื— ืฉืœ ืžืฉืชืžืฉื™ื ื ืœื”ื‘ื™ื ื‘ื›ืœ ืžืงื•ื.
02:05
Let's look at some of the maps
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ื‘ื•ืื• ื ืกืชื›ืœ ื‘ื—ืœืง ืžื”ืคื•ืช
02:08
being created by users right now.
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ืฉื ื•ืฆืจื•ืช ืขืœ ื™ื“ื™ ืžืฉืชืžืฉื™ื ืžืžืฉ ืขื›ืฉื™ื•.
02:11
So, as we speak, people are mapping the world
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ืื–, ืชื•ืš ื›ื“ื™ ืฉืื ื—ื ื• ืžื“ื‘ืจื™ื ืื ืฉื™ื ืžืžืคื™ื ืืช ื”ืขื•ืœื
02:13
in these 170 countries.
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ื‘ 170 ื”ืืจืฆื•ืช ื”ืืœื”.
02:15
You can see Bridget in Africa who just mapped a road in Senegal.
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ืืชื ืจื•ืื™ื ืืช ื‘ืจื™ื“ื’'ื˜ ื‘ืืคืจื™ืงื” ืฉื”ืจื’ืข ืžื™ืคืชื” ื“ืจืš ื‘ืกื ื’ืœ.
02:21
And, closer to home, Chalua, an N.G. road in Bangalore.
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ื•ืงืจื•ื‘ ื™ื•ืชืจ ืœื‘ื™ืช, ืฆ'ืืœื•ืื”, ื›ื‘ื™ืฉ ื‘ื‘ื ื’ืœื•ืจ.
02:26
This is the result of computational geometry,
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ื–ื•ื”ื™ ืชื•ืฆืื” ืฉืœ ื’ื™ืื•ืžื˜ืจื™ื” ื—ื™ืฉื•ื‘ื™ืช,
02:29
gesture recognition, and machine learning.
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ื–ื™ื”ื•ื™ ื—ื™ื•ื•ื™ื™ื, ื•ืœืžื™ื“ื” ืข"ื™ ืžื›ื•ื ื”.
02:32
This is a victory of thousands of users,
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ื–ื”ื• ื ืฆื—ื•ืŸ ืฉืœ ืืœืคื™ ืžืฉืชืžืฉื™ื,
02:34
in hundreds of cities,
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ื‘ืžืื•ืช ืขืจื™ื,
02:36
one user, one edit at a time.
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ืžืฉืชืžืฉ ืื—ื“ ื•ืขืจื™ื›ื” ืื—ืช ื›ืœ ืคืขื.
02:38
This is an invitation to the 70 percent
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ื–ื•ื”ื™ ื”ื–ืžื ื” ืœืฉื‘ืขื™ื ื”ืื—ื•ื–ื™ื
02:42
of our unmapped planet.
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ืฉืœ ื›ื•ื›ื‘ื ื• ื”ืœื ืžืžื•ืคื”.
02:44
Welcome to the new world.
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ื‘ืจื•ื›ื™ื ื”ื‘ืื™ื ืœืขื•ืœื ื”ื—ื“ืฉ.
02:46
(Applause)
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(ืžื—ื™ืื•ืช ื›ืคื™ื™ื)
ืขืœ ืืชืจ ื–ื”

ืืชืจ ื–ื” ื™ืฆื™ื’ ื‘ืคื ื™ื›ื ืกืจื˜ื•ื ื™ YouTube ื”ืžื•ืขื™ืœื™ื ืœืœื™ืžื•ื“ ืื ื’ืœื™ืช. ืชื•ื›ืœื• ืœืจืื•ืช ืฉื™ืขื•ืจื™ ืื ื’ืœื™ืช ื”ืžื•ืขื‘ืจื™ื ืขืœ ื™ื“ื™ ืžื•ืจื™ื ืžื”ืฉื•ืจื” ื”ืจืืฉื•ื ื” ืžืจื—ื‘ื™ ื”ืขื•ืœื. ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ื”ืžื•ืฆื’ื•ืช ื‘ื›ืœ ื“ืฃ ื•ื™ื“ืื• ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ ืžืฉื. ื”ื›ืชื•ื‘ื™ื•ืช ื’ื•ืœืœื•ืช ื‘ืกื ื›ืจื•ืŸ ืขื ื”ืคืขืœืช ื”ื•ื•ื™ื“ืื•. ืื ื™ืฉ ืœืš ื”ืขืจื•ืช ืื• ื‘ืงืฉื•ืช, ืื ื ืฆื•ืจ ืื™ืชื ื• ืงืฉืจ ื‘ืืžืฆืขื•ืช ื˜ื•ืคืก ื™ืฆื™ืจืช ืงืฉืจ ื–ื”.

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