My name is Noel Gorelick and I work for Google.
I'm one of the founders of Google Earth Engine. Back in around 2008
we were working with some people who were trying to do deforestation
mapping in Brazil. Very specifically people looking for
people trying to cut down trees that shouldn't be doing so. And the
very first idea for Google earth engine was Google trees. We would
actually make a tree counting tool, but that was the the basic impetus
was to be able to take data like the Landsat archive and count
trees, map cities and provide the ability for people to access that
data and and use it easily. And quickly turned into something much
larger. We're going to do more than count trees, right. If we gonna get
all this data were going to a lot more than that and so over the
course of literally a week, me and my partner, the first 2 people
on the team said okay we know we can do all kinds of land cover
mapping with this.
People use Earth Engine a lot for processing Landsat data but the
really nice thing about earth engine is that all the other data
sets are there and you can merge together. So it's actually somewhat
uncommon for a user to just use Landsat because it's so easy to
bring in MODIS and Sentinel and a bunch of other data sets. Most
applications sooner or later turn into handling many different kinds
of data sets along the way. Until this year Landsat was by far the
most used data set on the platform Sentinel 2 is catching up very
fast. The really nice thing is you can use them together. So almost
all Sentinel 2 users are also Landsat users.
Until that happened, being able to
combine old calibrated Landsat 5 with newly calibrated Landsat 7
both geometrically and radiometrically was questionable.
People did it, they weren't always happy with the results. And now
they're sort of a stamp of approval and a consistent calibration across
the whole archive that make that vastly easier. So I think that's
the best thing Landsat has done for their users since the data became free.
I am excited about it working. I think it's definitely the next stop
for everybody that wants to be using Landsat data. One of the
outcomes I hope is a per image land cover classification. So every
single image will have the cover classification attached to it and
that's really what users end up wanting. They just work with the
raw data because that's what they have to do but if you could just
say this is an urban pixel I think 98%, 99% of all users would be
happy with those results and not bother with the raw pixels.
The exciting thing about where the
Landsat program is going and the fact that Earth Engine gets to help
is that the 5 most advanced scientists in the world doing
remote sensing analysis can do some work and then in a few weeks,
months, maybe years, everybody else can do the same thing and that's
quite revolutionary for everybody else. The cutting edge of science
moves on at the pace it has more us always moved on but, the ability to
bring the the rest of the world along for the ride at a much more
accelerated rate is the part we're excited about. So when the Landsat
science team members who are arguably probably the best in the
world at doing this kind of analysis make breakthroughs we can
transfer those breakthroughs to the Peruvian minister of forestry and
beekeeping in a matter of weeks or months. I'm excited that 8 years
ago the things that we thought were going to be the future are in fact
the future. The future is now and and we're quite happy about it.
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