welcome everybody to this new picks for
the webinar my name is Oliver King I'm
co-founder of peaceful day and today's
topic is ground control points so let's
start with the agenda the topic the few
topics we're going to discuss today is
we're going to start first with an
introduction to the ground control
points just to define what they are and
why actually we are needing them and
actually go a bit more in critical
detail both for the J reference part and
the accuracy then we'll go a step by
step and I'm going to show you in picks
for the mapper how to insert ground
control points the most efficient way of
course then we'll discuss about the how
to assess the accuracy of these control
points that we just inserted both in the
quality report as well as also the rate
cloud will answer then a question which
has been asked very very often about how
many GCP do you do you need and where do
you place them in your project and will
give many answers to actually these
questions we'll also go over the most
common errors that we are supporting has
been seeing with with the users of
Pete's body map on which problems they
encounter when related to ground control
points I also talked about a feature
which has been introduced in the version
1.1 of Peaks body mapper which is about
the tolerance of the geo tags and gun
control points and conclude with an
alternative way of adding one control
points in this body mapper all right
so let's start with the simple question
what's a Guang control point in most
cases a ground control point is
basically a marking on the ground
measured by your high-precision GPS then
you acquire you imagery using your UAV
or you drone of this area where you
marked on the ground this GCP and just
before processing you include the
measurement you did with your GPS inside
of the project to enhance the Douro
famines drill reference mints and their
accuracy however it's a bit more broad
than that you can actually also use any
type of feature which is easy to
recognize on the ground such as a
building edge or roof and the only thing
is it has to be significantly
recognizable in the images because as
you can see in this example it's very
easy to see it on the left when you take
it from the ground but at 100 meter or
altitude from from the drone it looks a
bit more differently so I would advise
to choose something with very high
contrast now why would we actually use
ground control points why why actually
would we actually add ground control
points to a project I would say there's
there's mostly two reasons for it reason
number one is about providing a great
deal reference meant to your project and
reason number two is about improving the
relative accuracy of your project so
let's go first talk about reason number
one your reference picks for the mapper
is able to reconstruct to calibrate a
project fully just from the images only
without any information about geo geo
location or GCP or anything however if
you just take images without geo tags
and recipient but in the software you
will get a 3d model which is relatively
correct so if you take the
portions that will be correct but
measuring in it will be wrong
mostly because from images only you
cannot get the scale the orientation and
the position of your project these are
unknown
what pics valdine mapper is going to do
for you is going to position it around a
value 0 it's going to orient it in some
way but it doesn't know if it has to be
upside-down or if it has to look on the
right on the side so it may very well
happen that's just as in this picture
you get your project upside down and it
doesn't know if it's one centimetre or
one kilometer project however this is
usually not happening because you are
including geo tags in your project if
you have geo tags then your 3d model the
position of the camera is trying to fit
is going to try to fit during the
processing this geo tags and this will
give the proper geo referencing meaning
the scale position and orientation of
the project well this would be good if
your geo tags would be perfect but in
most of the projects you're going to
process especially in the UAV world this
is not going to be correct because your
GPS tag the Geo tag that you assigned to
the images will actually have a lot of
error on there its error because on one
side it's very far away from the
distance you want to measure the the
position of the cameras in addition it's
very tricky to correctly synchronize the
time where the GPS fires and where the
camera actually takes the picture to
synchronize the exact timing if you take
a few milliseconds of mistakes if you
fly fast this is going to make
centimeters of mistake but in addition
the most global error that you will have
there is that you're very likely your
UAV or human aircraft is not going to
have a high-precision GPS on it it's
going to
consumer grade GPS a consumer-grade GPS
has two type of noise it has inaccuracy
of around 1 meter which the software has
not too many trouble to compensate for
because we can model and incorporate
this noise to make a very good
measurement from that but the most
problematic is that there is a global
shift of around 5 meters this global
shift is basically shifting your auto
mosaic and your dsm your point cloud in
some random direction of around 5 meters
and this is due to atmospheric condition
in the in around the earth which
deviates a bit the GPS signal and with
consumer-grade gps you don't have a way
to correct that so now that's actually
the real reason of introducing run
control point is that it's much easier
to use a high quality GPS surveying tool
on the ground than in the air and the
good news is that you only need three
measurements on the ground to define the
whole transformation between the
relative space and the real world these
three measurements we'll do on the
ground will define the scale meters or
feet will define the orientation to put
properly things correctly and we'll
define also the position so that's
really where the GCP are useful so that
was really for the g reference spot
where this is really the most important
now I was also mentioning at the
beginning that it's not just about your
reference mint it's also about accuracy
and potentially adding GCP is also able
to improve the accuracy of certain type
of projects so let's have a closer look
where it's useful and why it's less
useful
if you have a perfect project with a lot
of overlap good quality images lots of
visual contents the the whole project is
going to calibrate using the visual
content in if there is very a lot of
visual content lots of matches there
will be very little error introduced by
matching the images and you will have a
very very good relative project even if
it was two thousand images long and
there's the error that is introduced by
mismatches it's going to be so small
that it's not going to be you're not
going to be able to measure it so in the
good case in this case adding GCP will
not improve the accuracy because their
accuracy Oh is already as good as it can
become however this is not always the
case and sometimes you have sometimes
just in little parts of your project you
have areas which have less overlap or
less visual content and less matches in
this case when you have very little of
these matches you may introduce it may
introduce some error this error is very
little but the issue is that it may
accumulate and if it happens in the
middle of the project so that would be a
side view of your of your calibration if
it happens in the middle just half a
degree of error it may propagate and
then lead to actually very high errors
at the end of the project of potentially
several meters the good news is that by
introducing GCP it helps you to
potentially fix this error accumulation
error and in this in a project where
basically you had an error accumulation
happening in the middle if you
introduced GCP either on both ends to
fix the system or in the middle to avoid
this error accumulation to happen you
can fix this error accumulation and have
a really nice project overall
now one last thing before going into how
to insert them in the software it's just
a small discussion about measuring the
accuracy of your project so as you can
have guessed by now when you include GCP
this DCP will be used to make sure that
the when you do the reconstruction the
model will fit as closely as possible to
this point which means basically that we
minimize the error in this location so
if you look at the dsm at this area
obviously the error will be close to
zero and measuring to have a global
sense of the project the error it may be
not very fair because it may very well
at this area at zero but then it gets
crazy in other places if the matches
were not good enough so a good way to
measure the accuracy of your project is
to use something slightly different that
we introduced also in peace for the
mapper is checkpoint so checkpoints is
basically the same as a groan control
point is also something that you have to
mark on the ground measure with a
geodesic GPS and click in the images but
if you label it as being a checkpoint
the software will not take it an account
Nader for the geo reference nor the
optimization and at this spot you will
be able to get very fair assessment of
the accuracy of your project we're going
to show that just a bit later in more
details so let's go for the demo on how
to introduce one control point in a
project clips
so in this project I have about 43
images taken at about 150 meters
altitude with a can on exes camera and
with an overlap of about 70% frontal and
50% on the side there's a lot of visual
content this is a very easy project and
in this project just before taking the
images with my UAV I collected on the
ground ground control points so what I
did basically is that I went on the
ground with a spray can of spray and I
made a pattern you are basically free to
make any type of pattern as long as you
can identify it well and precisely in
the images something with a high
contrast and the sharp edge is usually
preferable because it's easier to click
with high precision later on a good
practice is also to take the ground
control points to take pictures of them
while on the ground and it makes it much
easier to to later on know which point
is which while I did this mark on the
ground I also used GPS a high precision
GPS device to make measurements in the
National coordinate system so this was
done in Switzerland so I'm using the CH
1903 plus that room and coordinate
system the format of the file which you
need to create to be able to enter it in
picks for the mapper is very simple you
start with the name you can give any
random name to your ground control
points then the x value the y value and
the altitude for that value you create
one line for ground control points and
save it in a simple ASCII file okay
so let's create a project to use um I'm
going to quickly create a new project a
quick going to - it will be not test I'm
going to include my 43 images next the
geo tags are already inside of the
images so I don't have to do anything
special next finish and now I'm able to
see the geo tags on the satellite maps
and this project is ready to get
processed and the easiest is first to
process to pre-process it without any
growing control point information to do
so you click on local processing and you
uncheck point cloud and suffocation and
DSM in automatic generation these are
not needed for making a pre-processing
it will just make things faster by
unchecking them and then you click start
just to save a bit time I've already
done this project right there and this
is the status of the project you'll see
just after the I need to restart it
just after the processing of the first
step without ground control points okay
this is the view of the Red Cloud
showing the geo-located reconstruction
using the Geo tags only so once you have
done this step it's everything becomes
much easier to just introduce one
control points and now I'm going to show
you how first you need to open using the
icon there on the top the guang control
point editor with this editor the first
thing you have to do is select the
coordinate system of your ground control
points as I mentioned before I'm using
the National Swiss coordinate system
which is ch 19:03 plus if your coding
system is not is not in this list you
can use either the East PSG number or
even for a very specific project readon
PRG file ok you can note by the way that
before it was longitude latitude and now
it become X&Y as it detected that it's a
planner coordinate system then I'm going
to click on import ground control points
I'm going to browse for the file that I
was just showing just before with the
con control point name and the
coordinates the software detected the
ground control points and I just need to
press ok and it includes them all in the
project this interface is can be used to
introduce ground control points but I'm
going to show you introducing them to
the rate cloud which is much faster and
much more efficient
so for now we're going to just to press
ok to close the one control point editor
window you can see now that something
changed in my project there are some
blue crosses inside of the project these
are the ground control points that I
just inserted however they are not at
the right spot they are shifted of a few
meters it can be easily seen that they
are not exactly in the right position
this is because what you're seeing there
is the shift of the GPS which was
included inside of the UAV which is a
consumer-grade GPS so now a very
efficient way to annotate to mark my
images to make sure that we include this
control point for the processing is to
simply click on this blue cross or to
select it in the list on the left end is
going to display me the position of this
of the geodesic measured GPS position
now as the error that was in the first
GPS of the geotag gps was very little
only a few meters it's very easy to find
back where was the ground control point
it was just next to it a few meters away
what you need to do as a first step is
to click to mark the ground control
points in the first image then you need
to do it for certain one and click very
important then to click on apply if you
click if you don't click on apply it's
the software is not going to record your
changes by clicking on two images
you basically now linked you
triangulated the two images and created
a 3d point this 3d point is going to get
reprojection cross in the images for
more information about the rejection
I would advise to check the webinar of
about the Rae cloud that we did last
month and now this con control point
will be used during the processing
however there is often the question on
how many images do I need to click well
this can be answered easily by looking
at the the rate cloud editor if you zoom
on all the ground control on the
reprojection error which is the green
cross this green cross should be exactly
on the same location for each of the
images if it's not it means that you
didn't click in enough images and you
need to add some more measurements this
is what going to do for instance here I
can see that I'm two pixel away so I'm
going to add in this image one more
measurement by adding a measurement it
shifts in all the images the Green Cross
closer to where it should be
by doing that in additional image I can
see that now my Green Cross is in the
same corner of all the images which
pretty much means that it's a ID'd end
of measurements in my images you can
also notice that there is a yellow
circle around it this yellow circle is
related to the confidence of the marking
I'm doing right now
let's take an example in this one
control point the image is very very
blurry because it was the UAV bus was
flying quite fast and it was a bit on
the on the border there
and maybe I'm going to just take a break
to answer a few questions which are
asked to the audience so somebody is
asking about if choosing the corner is a
requirement or just a preference no this
is totally arbitrary in my case I
decided that when I did my measurement
with my GPS stick I actually took the
corner of my of my square that I painted
if I would have done a cross I could
have done it in the middle so this is
just because when I did the measurement
with my GPS I always set my GPS tick on
one of the corner
okay so back to this yellow circle in
the case which I'm not very confident
about making a measurement in this image
and you can zoom out a bit and do the
measurement on the lower zoom level by
doing the measurements on a doll lower
zoom level you will see that the yellow
circle will be much bigger and if the
yellow circle is much bigger it
basically tells that this measurement
will be taken with less importance than
the one you did at a very close
zoom level yes so somebody's asking if
you should always choose the same corner
and it did I did select the same corner
everywhere it looks different just
because the images are rotated so in
this example it's the top upper top
corner this was in bottom right but just
because the image rotated but it's the
same corner in every images okay once
I've done enough measurements I click on
apply' and now I introduce this one
control points with high confidence
somebody is asking if it would make
sense to actually take the ground
control points in the middle of the
square I did well if you look at the how
easy is it to spot with the middle
actually it's very hard because the
images are not of the sharpest quality
sometimes selecting a corner is more
precise than trying to set a middle
position which is hard to spot so now
I'm going to do it this type of
operation in a few other ground control
point so this is another one okay I know
I remember this was the corner I
selected click click click I
apply a zoom I look in all the
additional images if the ground country
the reprojection is at the correct area
yes it is okay I can help a bit this one
is very blurry some less confidence so i
zoom out a bit before making the
measurement okay click apply and in this
project I have eight GCP so what I'm
going to do is I'm going to choose five
as being GCP and three of them I'm going
to label them as a checkpoint to allow
me to assess the accuracy within a fair
way to do so you click on your gun
control point again you make your
measurement measurement click apply you
zoom okay this lets a create so thick
let's zoom up this looks good
apply and now if you double click on the
type which is written there with a
double click you get access to a menu
this menu allows you to change from GCP
to checkpoint click apply again and you
will get the you will get
this GCP being a ground control point
beginner checkpoint so now I'm not going
to do all eight ground control points
this would take a bit more too much time
but let's imagine that I would have
clicked and marked in all major images
my 8 ground control points and applied
each of them to include this to include
this measurement now in the processing
to find the correct position of the
camera including all of that I'm going
to click on process and reoptimize this
is going to be much faster than the
first step and will basically take my
gun control point information to
geolocate and to minimize the error or
the ground roll point
gun control point so just to save time
again this is something I've already
done in this project over there and by
reprocessing you can now see that and
the error between the blue which is the
merger GPS and the green which is the
triangulated type point position is very
very close so now first how to assess
the quality of this of this ground
control point and checkpoint there are
two ways basically to to get a better
feeling about how accurate where my gun
control points measured taken accounts
and everything the first way is using
the Ray cloud editor so again after
processing you click back on the ground
control point on the
top of the imageview you get a few
numbers over there these numbers give
you some estimates and some indication
about the accuracy of these measurements
the first number is a third is a number
which basically relates the variance
between the yellow and the green cross
basically it's the projection error and
tells you how nicely did all the Ray
join together to make a 3d point this
value should rather be below 1 to get
good results the certain value you see
there is the theoretical is the
basically the covariance of the error at
the point where you did the Georgia
triangulation and it's a bit more
complex value this is really something
much more for photogrammetry but
something as an easy way to check is
that the third part is very often larger
than the two other one at least it
should be comparable the third value you
get down is the maximal orthogonal array
distance it basically tells it's going
to warn you if there is array which is
too far away from all the others if the
value is high so this should be meters
if the value is bigger than the accuracy
of your GPS it's very likely that one of
your click was not done correctly so if
this value gets very high
you should check back in your project if
one of your click was wrongly clicked or
not so let's assume that I wrongly click
one I miss level and I've wrongly sick
in one of the of the image you will
start to have extremely high value there
which will tell you very much that there
is an issue in your clicking finally you
have the error between the Green Cross
and the blue dot which
the green is a reprojection in the blue
is the GPS and the error will be
displayed in meters over there this
error is also reported inside of the
inside of the quality report so after
processing after reprocessing reoptimize
in the step 1 you get a new quality
report in this quality prod you can see
the ground control point which is to add
a label they have the error which I just
mentioned which is the treatment
distance between the GPS and the
triangulated point that you just
measured you get the reprojection error
for each of the GCT and you get both the
value the number of times that you
clicked in the images so for the GCP
number 12 i clicked in 9 different
images and the software is going to be
quite smart and is going to tell you if
one value one of your click looks really
way too crazy way too ahead is going to
try to identify it and going to remove
it from the computation in order not to
introduce error so from this one control
point we're going to compute the mean
the Sigma which is basically the
standard deviation and the root mean
square error which is a combination of
the mean and the standard deviation
I get very small error which is quite
normal basically it just means that the
software was able to include the GPS
measurements with very high accuracy but
this one mean this values there should
not be taken as a fair assessment of the
quality of your processing this you just
these values are going to let you know
if the GCP were well included in the
project but they are not going to tell
you
if your whole projects going to be
accurate for this you'd rather use
checkpoint so as you can see there's
another table which is just about the
three GCP that are labeled as
checkpoints in this table I can have a
gander on x y&z the reprojection error
how many times I clicked in the images -
to mark them and they are here I get the
mean the Sigma and the RMS error
something very nice you can see so this
project was a four centimeter per pixel
GSD and the GCP the average error and
the RMS error is basically in this in
the range of one pixel which is
extremely good for this project so I saw
going in the chat question the usual
question so how many GCPs
and where would you where would you put
them so that's a very very interesting
questions you got usually what we
recommend is to use five GCP for even
quite large project and to spread them
evenly in the in the field as I
mentioned in the intro there is really
two different cases in the case where
you have a very good overlap you have
very good image quality well in that
case there will be very little drift due
to error accumulation and the GCP are
mainly going to be used only for grf
amendments not for improving their
accuracy now where do you place them if
you place them or all side-by-side very
closely to each other you have the
likelihood that if you do a small
mistake you always do a small mistake in
the measurement of this GCP
it can have the effect of a leverage and
a small mistake there a small degree of
mistake could actually introduce quite a
large mistake on the other side of your
project for this reason it's always much
better to try as much as possible to
spread your DCP all across your your
project to avoid this leverage effect
also
I wouldn't put the ground control points
too much on the extreme side of the
project because you will have less
images to on which you can mark the
ground control points so by putting the
the ground control points a bit more
centered you have more images which see
this vcp and so you can mock them in
additional images and this is going to
also improve the accuracy so I'd like to
share this project that we did together
with a client this our 2,890 images
following multiple flights using a UAV
and the Ricoh camera with a four
centimeter GSD in this project 27 GCP
were recorded using the latest picks for
the mapper 1.1 which is going to be
released end of May
we did some experiments about the
accuracy of the different projects using
the gun control points so without any
ground control points indeed you get
something like a 4 meter in accuracy in
that direction by looking at all the
control points on the field this
basically is big is the arrow introduced
by the geotag by the GPS in accurate GPS
on the the UAV however then by using
five ground control points only five the
error on the 22 or the DCP station was
of 10 centimeter sorry so GSD means
ground something this
is the size of a pixel on the ground so
false in each pixel is four centimeter
on the ground and what's very
interesting from this table is that
there is a huge difference from using 5g
CT but then for this particular project
adding more GCP did not really improve
much the accuracy of the project because
the content the visual content was in
the overlap was so good that's the error
just from the images was already
incredibly small now this is not true
for every project on the left you would
see a project such as described before
so where you have a lot of matches in
this case yes you could use possibly
only three ground control points and
place them pretty much wherever you want
in the project however now on the right
you can see this is the same project but
this was Flo I flew this project much
later in the evening and the light
condition were was very poor and the
visual content of the image that was
also very very poor and you can see that
the the contents visual contents is so
lower in the images that and there is
potentially much more error accumulation
happening in this project another thing
you can see is basically this project
almost divided itself into two parts the
part on the top and the part on the
bottom and there's very little link
between these two parts in this case
adding more than three one control
points can really help and improve the
accuracy and is probably needed to
improve the accuracy and I would
recommend two ways of setting the one
control point in this project either by
treating the two subparts as individual
and including run control points in one
support in the other or to try to put
the ground control points in the part
with where there was very little match
to try to help the software to improve
and to avoid this
accumulation at this place now having
said that this is still not ideal if you
had the choice between adding more GCP
and taking the images with better light
condition more overlap more data you
should always go for more data and
better light condition adding GCP helps
but it's a complicated way and very
requires a lot of work to be done we're
usually adding more data would solve all
of your problem without without having
to introduce too many ground control
points I'm going to go quickly now over
the the most common errors that our
support team has been checked when when
people are using the software the first
one which is usually the most common one
is people introducing the wrong
coordinate system basically if you put
the wrong coding system then everything
is going to be difficult because the
control points will not be at the right
spot when you try to measure everything
will be wrong and usually you can detect
when this happened when you go back in
the software and you look at the map
view if you don't see the green the blue
crosses in the map view this problem
means that you did a mistake by by
either having the wrong coordinate
system or that you inverted in your file
text file the X&Y position this will
either put you back somewhere in the
water in total your wrong position or
display them all in one single dot
another type of mistake that is very
often done is bad distribution of gun
control points setting three gun control
points in the line is not sufficient to
define a 3d coordinate system and
basically you have ambiguities and maybe
the project will be tilted in one random
direction
also if you put them all in a single
corner it may happen that it shifts the
hole and you get orientation mistake in
the whole project
another type of mistake is mislabeled
GCP this you will be able to detect from
the quality report if you see too many
red points in the quality report if you
have inner creates one control points
like you're using your iPhone GPS to try
to insert one control point well if you
have geo tags then you're likely not
going to improve anything you're just
going to add more noise to the system
and this is usually going to be
difficult something also to remember is
that the images they are matching very
nicely so if you tell them to bend
towards inaccurate GPS it might make
very very weird
effects on that so I wouldn't try to use
the system with inaccurate GPS or maybe
actually you could do that with the
tolerance setting that I'm going to talk
just after this one also something which
happens is if you have GCP but these GCP
is in a location in your project which
was not able to get calibrated for some
reason because maybe it was a very
difficult area so for that you would
first need to add manual type points so
as I explained in the previous webinar
to calibrate to get all the images to
calibrate and then only then if the
images are calibrated then the ground
control points will be taken in account
and I'm then going to talk quickly about
the tolerance as this is quite quite
important and this is a one of the new
feature of the peace 40 mapper 1.1 now
you have the possibility to set yourself
the tolerance which is basically the
expected accuracy of both the geotags
end of the ground control point
the default value for the geotag on the
software is 5 meter for XY and 10 meters
for that this is very good for a
consumer-grade gps if for some reason
you put this value and you set this
value to the tolerance to high like you
would 200 meters in XY and hundred-meter
and Z then the Geo tag will not
contribute almost at all to the
reconstruction and not help at all the
reconstruction so it's like if you are
not using geo tags if you put it too low
so you would but like one millimeter in
XY and one millimeter in Z then this
will have very strange effect too as as
you told the software to really trust
the geo tags but actually they are not
trustworthy they are very noisy the
software is going to try to match them
as much as possible and you will get
weird effects happening in the
reconstruction same for one control
point there you can basically set the
expected accuracy of your GPS if you set
a very high value then it's not going to
be taken merchant account and if you put
a value which is too low then then you
have a very big likelihood that your DCP
will not be taken in account for the
project so you have quite a good
incentive to set the right value I'm
just going to show you quickly how to do
it how to insert this value so for the
geo tags you go in image property and
there you have the list of your images
you can see by default the XY tolerance
is zero point one meter I'm going to
reduce actually I already change it
before so by default it's 10 meter it's
5 meters but I will change it you can
set it to let's say 0.5 meter you can
set it per image if you want to change
it to have very good tuning on on each
images but if you need to set
all the tolerance of the whole Colin you
click on the column then you right-click
with your mouse on the value which you
want to set everywhere and there you'll
have a small pop-up telling you that you
can replace all the values of this
column with the one which is under the
mouse there now all the values are this
one same for the vertical you could have
a 10 meters vertical tolerance you
choose the colon you right click with
the mouse and you can replace all the
values with this one immediately for the
ground control points you click on the
GCP editor now you have these two
tolerance values you basically can also
change the tolerance of this if you say
that you have very inaccurate GPS
because you basically gcd because you
collected them on Google Maps for
instance there you could put an estimate
of 10 meter tolerance and and then you
can again you select the column and you
can set that replace the value for all
the GCP
okay now just to quickly finalize this
webinar I still have a slide about
alternative way of introducing ground
control points in a fixed body mapper
there are really many ways we offer a
lot of flexibility in how you can
introduce one control points I just
showed today the most efficient way when
you have ground control points and
reasonable geotags but if you for some
reason you don't want to process first
and you want to insert one controls
before doing any processing you can
still use the ground control points
editor and you can find many articles on
our knowledge base which will show you
the alternative way of introducing
ground control points in your project
for local coordinate system for some
when you don't want to process before
doing the processing you don't want to
process before doing the marking and so
on alright so I covered a lot of of
information but this basically closed
most of the questions most of the topics
I wanted to cover about one control
points within an hour I take the
opportunity to announce that we already
planned the next webinar for next month
which is going to be about the also a
new feature that we introduced in tips
for the mapper 1.1 which is an index
calculator specialized for precision
agriculture basically it's something
that allows you to edit your auto mosaic
to generate single band and index map
like NDVI and formulas you can create
save your own formula create classes
which many things which are very useful
for precision agriculture so this is
going to be next next month's topic and
you will be very soon be able to
register it on the similar page
still we have workshops that we are
hosting in Switzerland in our offices
beginners an advanced user in Lausanne
which is going to happen in July more
information on our website as usual you
can always get a free trial of beachbody
mapper directly on our website you can
rent a month starting as low as 260 euro
per month and I'm very happy to
introduce that with but just today
last month's webinar about the rate
cloud fully downloadable on the web and
this is you can find this in mapper
adoptees 40 com this will be now that
I'm just giving now will be available
also within a week on this same mapper
peaceful calm with that I like to thank
you all very much for attending this
webinar I hope that you've learned a lot
and I'm going to leave the webinar open
for the next 30 minutes where you can
keep chatting with our support team
through the questions and you can get
the you can get directly a few questions
from that and any way our support is
always available either on the knowledge
base or by writing at support at these
40 calm so with that thank you very much
it was a pleasure to hold this webinar
again I hope you had also pleasure
watching it and while I hope seeing you
next month for next webinar so I leave
the GoToWebinar open for the next 30
minutes so you can chat with our support
team for any questions related to this
webinar thank you very much have a great
day
you