TED2018
Will Marshall: The mission to create a searchable database of Earth's surface
威爾馬歇爾: 建立可供搜尋地表資訊資料庫的任務
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如果你能用搜尋網路的方式來搜尋地球表面，會如何？威爾馬歇爾和他在星球實驗室的團隊用世界最大的衛星艦隊來為整個地球每天拍攝影像。現在，他們要開始進行一個新計畫：用人工智慧來將地球上每個時間點的所有物體做索引——讓地球上的船隻、樹木、房子、任何東西都可以被搜尋到，就像你用 Google 搜尋一樣。他們的遠景是，這個資料庫能夠成為全球大量物體改變的紀錄。「你看不到，就無法改善。」馬歇爾說：「我們的工具能讓大家看到這些改變，並採取行動。」
Will Marshall - Space scientist
At Planet, Will Marshall leads overall strategy for commercializing new geospatial data and analytics that are disrupting agriculture, mapping, energy, the environment and other vertical markets. Full bio
At Planet, Will Marshall leads overall strategy for commercializing new geospatial data and analytics that are disrupting agriculture, mapping, energy, the environment and other vertical markets. Full bio
Double-click the English transcript below to play the video.
00:12
Four years ago, here at TED,
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四年前，在這個 TED 會場，
00:15
I announced Planet's Mission 1:
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我宣佈了《星球任務一號》：
00:17
to launch a fleet of satellites
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我們發射了一支衛星艦隊，
00:19
that would image
the entire Earth, every day,
the entire Earth, every day,
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用來拍攝地球每天的影像，
00:22
and to democratize access to it.
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並讓大眾能取得這些資訊。
00:25
The problem we were trying
to solve was simple.
to solve was simple.
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我們要解決的問題很簡單。
00:27
Satellite imagery you find online is old,
typically years old,
typically years old,
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你在網路上看到的衛星影像
是舊的，通常是幾年前的，
是舊的，通常是幾年前的，
00:30
yet human activity was happening
on days and weeks and months,
on days and weeks and months,
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但人類的活動卻是每天、
每週、每月都在發生，
每週、每月都在發生，
00:34
and you can't fix what you can't see.
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你看不到，就無法改善。
00:37
We wanted to give people the tools
to see that change and take action.
to see that change and take action.
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我們想要提供一些工具，
幫大家看到改變並採取行動。
幫大家看到改變並採取行動。
00:40
The beautiful Blue Marble image,
taken by the Apollo 17 astronauts in 1972
taken by the Apollo 17 astronauts in 1972
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這張美麗的藍色彈珠照片是 1972 年
阿波羅 17 號的太空人所拍攝的，
阿波羅 17 號的太空人所拍攝的，
00:45
had helped humanity become aware
that we're on a fragile planet.
that we're on a fragile planet.
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這張照片讓人類明白到，
我們居住的星球是很脆弱的。
我們居住的星球是很脆弱的。
00:49
And we wanted to take it
to the next level,
to the next level,
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我們還想要更上一層樓，
00:51
to give people the tools
to take action, to take care of it.
to take action, to take care of it.
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提供工具，讓大家能
採取行動，關心地球。
採取行動，關心地球。
00:55
Well, after many
Apollo projects of our own,
Apollo projects of our own,
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在我們執行了許多阿波羅計畫、
00:59
launching the largest fleet
of satellites in human history,
of satellites in human history,
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發射了人類史上
最大的一支衛星艦隊後，
最大的一支衛星艦隊後，
01:03
we have reached our target.
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我們終於達成了目標。
01:06
Today, Planet images
the entire Earth, every single day.
the entire Earth, every single day.
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現在，《星球任務》每天
都能為整個地球拍攝影像。
都能為整個地球拍攝影像。
01:09
Mission accomplished.
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任務完成。
01:11
(Applause)
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（掌聲）
01:13
Thank you.
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謝謝。
01:15
It's taken 21 rocket launches --
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總共花了 21 次的火箭發射——
01:19
this animation makes it look
really simple -- it was not.
really simple -- it was not.
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這動畫使這任務看似簡單，
但其實不然。
但其實不然。
01:25
And we now have
over 200 satellites in orbit,
over 200 satellites in orbit,
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現在軌道上的衛星超過 200 個，
01:28
downlinking their data to 31 ground
stations we built around the planet.
stations we built around the planet.
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向我們建立在地面的
31 站下傳資料。
31 站下傳資料。
01:32
In total, we get 1.5 million 29-megapixel
images of the Earth down each day.
images of the Earth down each day.
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我們每天總共下傳 150 萬張
29 百萬畫素的地球影像。
29 百萬畫素的地球影像。
01:38
And on any one location
of the Earth's surface,
of the Earth's surface,
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在地球表面的任何一個地點，
01:41
we now have on average
more than 500 images.
more than 500 images.
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現在平均有超過 500 張影像。
01:44
A deep stack of data,
documenting immense change.
documenting immense change.
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非常大量的資料，
記錄著巨大的改變。
記錄著巨大的改變。
01:49
And lots of people are using this imagery.
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而且有許多人正在使用這些影像。
01:51
Agricultural companies are using it
to improve farmers' crop yields.
to improve farmers' crop yields.
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農業公司用它們來改善
農夫的作物產量。
農夫的作物產量。
01:57
Consumer-mapping companies are using it
to improve the maps you find online.
to improve the maps you find online.
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消費者製圖公司用它們
來改善你在線上看到的地圖。
來改善你在線上看到的地圖。
02:01
Governments are using it
for border security
for border security
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政府把它們用在邊境安全上，
02:03
or helping with disaster response
after floods and fires and earthquakes.
after floods and fires and earthquakes.
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或對洪水、火災、地震
提供災難應變的幫助。
提供災難應變的幫助。
還有很多非政府組織使用它們。
02:08
And lots of NGOs are using it.
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02:09
So, for tracking
and stopping deforestation.
and stopping deforestation.
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比如，可以追蹤和阻止森林砍伐。
02:13
Or helping to find the refugees
fleeing Myanmar.
fleeing Myanmar.
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或是協助找到逃離緬甸的難民。
02:16
Or to track all the activities
in the ongoing crisis in Syria,
in the ongoing crisis in Syria,
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或是追蹤所有敘利亞
正在發生的危機行動，
正在發生的危機行動，
02:21
holding all sides accountable.
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記錄各方的責任。
02:24
And today, I'm pleased
to announce Planet stories.
to announce Planet stories.
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今天，我很高興能來發佈
星球實驗室的故事。
星球實驗室的故事。
02:28
Anyone can go online to planet.com
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大家都可以上網造訪 planet.com，
02:30
open an account and see
all of our imagery online.
all of our imagery online.
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開一個帳戶，在線上
看我們所有的影像。
看我們所有的影像。
02:34
It's a bit like Google Earth,
except it's up-to-date imagery,
except it's up-to-date imagery,
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它有點像是 Google Earth，
只差在它是最新的影像，
只差在它是最新的影像，
02:37
and you can see back through time.
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且你還能回頭看過去的影像。
02:41
You can compare any two days
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你可以比較任何兩個日期，
02:42
and see the dramatic changes
that happen around our planet.
that happen around our planet.
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看看我們的星球上發生的巨大改變。
02:46
Or you can create a time lapse
through the 500 images that we have
through the 500 images that we have
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或是你也可以用我們的
500 張影像來做縮時影片，
500 張影像來做縮時影片，
02:50
and see that change
dramatically over time.
dramatically over time.
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看看隨著時間發生了
什麼巨大的改變。
什麼巨大的改變。
02:54
And you can share these over social media.
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你還可以把它們分享到社交媒體上。
02:57
It's pretty cool.
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它相當酷。
02:58
(Applause)
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（掌聲）
03:00
Thank you.
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謝謝。
03:02
We initially created this tool
for news journalists,
for news journalists,
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我們最初創造這項工具，
是為了新聞記者，
是為了新聞記者，
03:04
who wanted to get unbiased information
about world events.
about world events.
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對於全球的事件，
他們想取得無偏見的資訊。
他們想取得無偏見的資訊。
03:07
But now we've opened it up
for anyone to use,
for anyone to use,
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但現在我們已經開放給大家使用，
03:09
for nonprofit or personal uses.
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可做非營利使用或個人使用。
03:12
And we hope it will give people the tools
to find and see the changes on the planet
to find and see the changes on the planet
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我們希望這項工具能協助大家
找到並發現地球上的改變，
找到並發現地球上的改變，
03:17
and take action.
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進而採取行動。
03:18
OK, so humanity now has this database
of information about the planet,
of information about the planet,
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好，所以人類現在有了
關於地球的資料庫，
關於地球的資料庫，
有隨時間改變的資訊。
03:23
changing over time.
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03:24
What's our next mission, what's Mission 2?
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我們的下一個任務，
任務二號是什麼？
任務二號是什麼？
03:26
In short, it's space plus AI.
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簡言之，是太空加上人工智慧。
03:29
What we're doing
with artificial intelligence
with artificial intelligence
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我們使用人工智慧
03:31
is finding the objects
in all the satellite images.
in all the satellite images.
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是要在所有這些
衛星影像中找到物體。
衛星影像中找到物體。
03:35
The same AI tools that are used
to find cats in videos online
to find cats in videos online
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只要使用在線上影片中找出貓咪的
人工智慧一樣的工具，
人工智慧一樣的工具，
03:39
can also be used to find
information on our pictures.
information on our pictures.
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也能被用來尋找我們照片中的資訊。
03:43
So, imagine if you can say,
this is a ship, this is a tree,
this is a ship, this is a tree,
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想像一下，如果你能分辨，
這是一艘船，這是一棵樹，
這是一艘船，這是一棵樹，
03:46
this is a car, this is a road,
this is a building, this is a truck.
this is a building, this is a truck.
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這是一台汽車，這是一條道路，
這是一棟大樓，這是一台卡車。
這是一棟大樓，這是一台卡車。
03:51
And if you could do that
for all of the millions of images
for all of the millions of images
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若對每天傳下來的數百萬張影像
03:54
coming down per day,
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都能夠這麼做，
03:55
then you basically create a database
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基本上你就能建立起一個資料庫，
03:57
of all the sizable objects
on the planet, every day.
on the planet, every day.
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內有地球上每天
所有物體的資訊，相當可觀。
所有物體的資訊，相當可觀。
03:59
And that database is searchable.
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且那個資料庫能用來搜尋。
那就是我們正在做的事。
04:02
So that's exactly what we're doing.
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這是用我們的 API
（應用程式界面）做的原型。
（應用程式界面）做的原型。
04:04
Here's a prototype, working on our API.
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04:06
This is Beijing.
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這是北京。
04:08
So, imagine if we wanted
to count the planes in the airport.
to count the planes in the airport.
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想像一下，如果我們
想要知道機場有幾架飛機。
想要知道機場有幾架飛機。
04:11
We select the airport,
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我們選擇機場，
04:13
and it finds the planes in today's image,
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它就會在今天的影像中找到飛機，
04:15
and finds the planes
in the whole stack of images before it,
in the whole stack of images before it,
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並找到在這之前
一大堆影像中的飛機，
一大堆影像中的飛機，
04:18
and then outputs this graph of all
the planes in Beijing airport over time.
the planes in Beijing airport over time.
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接著輸出這張圖，上面是
各時間點北京機場中的飛機。
各時間點北京機場中的飛機。
04:23
Of course, you could do this
for all the airports around the world.
for all the airports around the world.
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當然，你可以對地球上
所有的機場做這件事。
所有的機場做這件事。
04:27
And let's look here
in the port of Vancouver.
in the port of Vancouver.
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咱們來看看這裡，溫哥華的港口。
04:30
So, we would do the same,
but this time we would look for vessels.
but this time we would look for vessels.
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我們可以做同樣的事，
但這次是要找船隻。
但這次是要找船隻。
04:33
So, we zoom in on Vancouver,
we select the area,
we select the area,
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我們將溫哥華放大，
選擇這個區域，
選擇這個區域，
04:38
and we search for ships.
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搜尋船隻。
04:40
And it outputs where all the ships are.
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它會輸出所有船隻的位置。
04:42
Now, imagine how useful this would be
to people in coast guards
to people in coast guards
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想像一下，對於海上防衛隊，
這是多麼有用的資訊，
這是多麼有用的資訊，
04:45
who are trying to track
and stop illegal fishing.
and stop illegal fishing.
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他們的工作是要追蹤
和阻止非法捕漁。
和阻止非法捕漁。
04:48
See, legal fishing vessels
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看，合法的捕漁船隻，
04:50
transmit their locations
using AIS beacons.
using AIS beacons.
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會用 AIS 信標來傳送它們的位置。
04:53
But we frequently find ships
that are not doing that.
that are not doing that.
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但我們常常會發現
沒有傳送信標的船隻。
沒有傳送信標的船隻。
04:56
The pictures don't lie.
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照片不會說謊。
04:58
And so, coast guards could use that
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所以，海上防衛隊能用那資訊，
05:00
and go and find
those illegal fishing vessels.
those illegal fishing vessels.
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去找出非法的捕漁船隻。
05:02
And soon we'll add
not just ships and planes
not just ships and planes
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不只是船和飛機，之後我們很快就會把
05:04
but all the other objects,
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其它物體加上去，
05:05
and we can output data feeds
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我們可以把資料輸出來，
05:07
of those locations
of all these objects over time
of all these objects over time
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你可以針對地點、時間區段做輸出，
05:10
that can be integrated digitally
from people's work flows.
from people's work flows.
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這些資料就可以在大家的
工作流程中做數位整合。
工作流程中做數位整合。
05:13
In time, we could get
more sophisticated browsers
more sophisticated browsers
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到時候，我們會有更精密的瀏覽器，
05:16
that people pull in
from different sources.
from different sources.
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讓大家可以納入多重來源的資料。
05:18
But ultimately, I can imagine us
abstracting out the imagery entirely
abstracting out the imagery entirely
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但最終，我可以想像
我們完全把影像抽取出來，
我們完全把影像抽取出來，
05:23
and just having a queryable
interface to the Earth.
interface to the Earth.
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並且有一個能夠查詢地球的介面。
05:26
Imagine if we could just ask,
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想像一下，若我們能問：
05:27
"Hey, how many houses
are there in Pakistan?
are there in Pakistan?
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「嘿，在巴基斯坦有多少間房子？
05:30
Give me a plot of that versus time."
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把那資料搭配時間，畫張圖給我。」
05:32
"How many trees are there in the Amazon
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「亞馬遜有多少棵樹？
05:34
and can you tell me the locations
of the trees that have been felled
of the trees that have been felled
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你能不能告訴我，從上週到這週之間
哪些位置的樹木被砍伐了？」
05:37
between this week and last week?"
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05:39
Wouldn't that be great?
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那樣不是很棒嗎？
05:40
Well, that's what
we're trying to go towards,
we're trying to go towards,
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那是我們在試圖達成的目標，
05:42
and we call it "Queryable Earth."
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我們稱它為「可查詢的地球」。
05:44
So, Planet's Mission 1 was
to image the whole planet every day
to image the whole planet every day
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所以，《星球任務一號》
是要做到每天拍攝地球影像，
是要做到每天拍攝地球影像，
05:48
and make it accessible.
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並讓這資訊能被大家取得。
05:50
Planet's Mission 2 is to index
all the objects on the planet over time
all the objects on the planet over time
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《星球任務二號》是要將地球上
各時間點的所有物體做索引，
各時間點的所有物體做索引，
05:54
and make it queryable.
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並供大家查詢。
05:56
Let me leave you with an analogy.
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最後，我跟大家做個比喻。
05:58
Google indexed what's on the internet
and made it searchable.
and made it searchable.
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Google 將網路上的東西
做了索引，並供大家搜尋。
做了索引，並供大家搜尋。
06:03
Well, we're indexing what's on the Earth
and making it searchable.
and making it searchable.
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我們則是將地球上的東西
做索引，並供大家搜尋。
做索引，並供大家搜尋。
06:06
Thank you very much.
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非常謝謝各位。
06:07
(Applause)
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（掌聲）
ABOUT THE SPEAKER
Will Marshall - Space scientistAt Planet, Will Marshall leads overall strategy for commercializing new geospatial data and analytics that are disrupting agriculture, mapping, energy, the environment and other vertical markets.
Why you should listen
Will Marshall is the co-founder and CEO of Planet. Prior to Planet, he was a Scientist at NASA/USRA where he worked on missions "LADEE" and "LCROSS," served as co-principal investigator on PhoneSat, and was the technical lead on research projects in space debris remediation.
Marshall received his PhD in Physics from the University of Oxford and his Masters in Physics with Space Science and Technology from the University of Leicester. He was a Postdoctoral Fellow at George Washington University and Harvard.
Will Marshall | Speaker | TED.com