September 1, 2025 • 7 mins
Graham Butcher explains what spectoral reflectance means in relation to grass measuring.
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Speaker 1 (00:12):
Graham Butcher fun consultant, joins us in studio once again. Graham,
good afternoon, and Andy, I'm very good.
Speaker 2 (00:18):
Thank you.
Speaker 1 (00:19):
Now it's the start of the September cycle. From your perspective,
how things been in the lead up?
Speaker 2 (00:24):
Oh, excellent winter. Couldn't have asked for more. Actually it
was quite warm and relatively dry. But are we kicking
the tail a few hard frost later on? It's been
reasonably wet, I suppose the last few days. So just
to remind us that it's we're just getting out of winter.
Speaker 1 (00:40):
Specteral reflectance is there topic today?
Speaker 2 (00:43):
Yes, very interesting topic. I decided to sit down and
learn as much as I could about it yesterday, which
is not a long time. But this is all about
measuring grass from space now sort of. As we all know,
grass absorbs red and blue light for photosynthusis not green.
That's why it's green because it reflects green. If it
(01:04):
absorbed green, all grass would be red and blue, which
would be pretty unusual. So anyway, healthy grass scored has
a very low red and blue reflectance. It's absorbing it,
it's not reflecting it. Hence it's green and has a
very high green reflectance. Obviously, that's why it's green. What
(01:27):
space telemetry does, it actually measures the reflectance of the grass,
and from a farm management point of view, I mean,
if you can measure it successfully from space, it's very
quick so that you can cover big areas very quickly,
so you know, it's got a lot of things going
for it. Once they do the measurements of the reflectance
(01:49):
of the grass, measuring different wavelengths in the red and
blue sector, there's a whole lot of not a whole lot.
I've come across four different algorithms they can use that
they put the measurements into those algorithms, and the termin
not only herbage mass, but a few other things like
crew proteins and whatever you as well. But we're just
focusing on herbridge mass at the moment. I tried to
(02:11):
find some studies on comparing satellite measurements with grass with
the more traditional methods like herbige analysis cut and measured
dry matter. So I found a Swiss study that was
published in twenty twenty. Now that's five years ago, which
is a relatively long time in the science of space technology,
I suppose. But they measured they had six farms in Switzerland,
(02:36):
three plots per farm, they had two plots that were grazed,
one that was cut for silage, and they used their
measurements done an island to compare to work out just
how many kilograms of draymata there was there. So the
result of all that at the end of the day
(02:58):
was there was a ninety nine point seven percent era
absolute era, which is pretty large and from a farm
management point of view wouldn't actually work. So just reading
through the paper, one of the issues was that the
IRIS calibration didn't suit Swiss farming techniques. The Swiss farms
(03:19):
had multi multi species pastures and they were generally running
at higher covers, and what the Irish calibration was about.
The IRIS calibration peaked at about twenty four hundred k's
and it was seventy five percent grass and the rest
was clover. So not a very good calibration, but a
very high era. So the real critical point with spectral
(03:44):
reflectants and getting a decent or inaccurate if you like,
cover on New Zealand farms is that the calibration has
got to be spot on. It's got to be relevant
to the pasture species we have, probably relevant to the
latitudes we have. Calibration is absolutely critical, and I'm not
one hundred percent sure that the calibrations have been where
(04:07):
they should be at the moment. For measuring in New Zealand,
once we get to get an accurate measure of the
grass from space, we need good calibrations. So that's ground proving,
if you like. So anyone who's using satellite telemetry to
measure their grass should probably well not probably should should
(04:28):
actually try and ground prove as much as they can
that it's relevant to their farm. Otherwise they could run
into a whole lot of issues. And the Swiss one, remember,
had a nearly hundred percent error in the measurements, so
but their calibration, they agreed in the paper, wasn't actually
one hundred percent, So calibration is critical. A couple of
other things. There's an issue called structure or saturation reflectance
(04:54):
right now. That's all about when grass is growing, it
keeps absorbing the red and the blue blue bands and
reflects green. It keeps going, keeps going, keeps growing, and
it absorbs the maximum amount of light that it can,
but it's still keeping growing. So if you're measuring the
reflectants at high herbage masses, you're probably underestimating the pasture cover. Now,
(05:18):
in the Swiss study, they found that looking at the
red and blue bands that at around thirteen hundred k's
of dry matter, the herbidge mass actually tailed off and
in some cases went to zero. But the grass still
kept growing because the reflectants reached minimum. But the grass
keep growing because it was still absorbing the light kept growing,
but it wasn't the satellites couldn't pick up that difference.
(05:43):
So saturation reflectance is an issue, quite a big issue
in my book. There's ways apparently weighs around that by
measuring different wavebands and what have you. And also if
you measure height of pasture, they can correct the algorithm
by measuring the height. They can do that from space
as well, because they do a measurement on very low
(06:04):
covers or beer ground, and they can measure the height,
which is staggering really because we're talking what twenty twenty
five thirty centimeters and measuring that from five hundred ks
in space is actually I don't know how they do it,
but apparently they can.
Speaker 1 (06:18):
Okay, whether we are talking about the era of AI
or that the industry of AIP, how is that going
to affect like some measuring pasture on farm.
Speaker 2 (06:28):
How's it going to affect?
Speaker 1 (06:29):
Yeah, it's going to be another tool in the toolbox,
is it not?
Speaker 2 (06:32):
It could be providing we get a calibration right and
providing we get these areas like saturation reflectance right as well.
We've got issues with cloud cover, we've got issues with
atmospheric interference as well. So it's a growing science. It's
developing quickly. But the big issue at the moment is
your calibration.
Speaker 1 (06:49):
Right. Are you learning more about AI, for instance, when
you're talking to farmers, because farmers are embracing it more
and more by the day they are from what you're doing.
Do you think it's something we need to embrace as
an industry.
Speaker 2 (07:01):
I think these areas where AI could be probably quite important. Yes,
just a growing industry will become relevant to New Zealand farming,
no question. So the key point from that study is calibration. Calibration, calibration.
That's the important thing. And I'm not convinced that it's
up to speed at the moment.
Speaker 1 (07:22):
And the reasting to see how it pans out. Graham,
always appreciate your time, might need your rank this afternoon.
Graham Butcher fun consultant Grant McMaster is up next.
Graham Butcher fun consultant, joins us in studio once again. Graham,
good afternoon, and Andy, I'm very good.
Speaker 2 (00:18):
Thank you.
Speaker 1 (00:19):
Now it's the start of the September cycle. From your perspective,
how things been in the lead up?
Speaker 2 (00:24):
Oh, excellent winter. Couldn't have asked for more. Actually it
was quite warm and relatively dry. But are we kicking
the tail a few hard frost later on? It's been
reasonably wet, I suppose the last few days. So just
to remind us that it's we're just getting out of winter.
Speaker 1 (00:40):
Specteral reflectance is there topic today?
Speaker 2 (00:43):
Yes, very interesting topic. I decided to sit down and
learn as much as I could about it yesterday, which
is not a long time. But this is all about
measuring grass from space now sort of. As we all know,
grass absorbs red and blue light for photosynthusis not green.
That's why it's green because it reflects green. If it
(01:04):
absorbed green, all grass would be red and blue, which
would be pretty unusual. So anyway, healthy grass scored has
a very low red and blue reflectance. It's absorbing it,
it's not reflecting it. Hence it's green and has a
very high green reflectance. Obviously, that's why it's green. What
(01:27):
space telemetry does, it actually measures the reflectance of the grass,
and from a farm management point of view, I mean,
if you can measure it successfully from space, it's very
quick so that you can cover big areas very quickly,
so you know, it's got a lot of things going
for it. Once they do the measurements of the reflectance
(01:49):
of the grass, measuring different wavelengths in the red and
blue sector, there's a whole lot of not a whole lot.
I've come across four different algorithms they can use that
they put the measurements into those algorithms, and the termin
not only herbage mass, but a few other things like
crew proteins and whatever you as well. But we're just
focusing on herbridge mass at the moment. I tried to
(02:11):
find some studies on comparing satellite measurements with grass with
the more traditional methods like herbige analysis cut and measured
dry matter. So I found a Swiss study that was
published in twenty twenty. Now that's five years ago, which
is a relatively long time in the science of space technology,
I suppose. But they measured they had six farms in Switzerland,
(02:36):
three plots per farm, they had two plots that were grazed,
one that was cut for silage, and they used their
measurements done an island to compare to work out just
how many kilograms of draymata there was there. So the
result of all that at the end of the day
(02:58):
was there was a ninety nine point seven percent era
absolute era, which is pretty large and from a farm
management point of view wouldn't actually work. So just reading
through the paper, one of the issues was that the
IRIS calibration didn't suit Swiss farming techniques. The Swiss farms
(03:19):
had multi multi species pastures and they were generally running
at higher covers, and what the Irish calibration was about.
The IRIS calibration peaked at about twenty four hundred k's
and it was seventy five percent grass and the rest
was clover. So not a very good calibration, but a
very high era. So the real critical point with spectral
(03:44):
reflectants and getting a decent or inaccurate if you like,
cover on New Zealand farms is that the calibration has
got to be spot on. It's got to be relevant
to the pasture species we have, probably relevant to the
latitudes we have. Calibration is absolutely critical, and I'm not
one hundred percent sure that the calibrations have been where
(04:07):
they should be at the moment. For measuring in New Zealand,
once we get to get an accurate measure of the
grass from space, we need good calibrations. So that's ground proving,
if you like. So anyone who's using satellite telemetry to
measure their grass should probably well not probably should should
(04:28):
actually try and ground prove as much as they can
that it's relevant to their farm. Otherwise they could run
into a whole lot of issues. And the Swiss one, remember,
had a nearly hundred percent error in the measurements, so
but their calibration, they agreed in the paper, wasn't actually
one hundred percent, So calibration is critical. A couple of
other things. There's an issue called structure or saturation reflectance
(04:54):
right now. That's all about when grass is growing, it
keeps absorbing the red and the blue blue bands and
reflects green. It keeps going, keeps going, keeps growing, and
it absorbs the maximum amount of light that it can,
but it's still keeping growing. So if you're measuring the
reflectants at high herbage masses, you're probably underestimating the pasture cover. Now,
(05:18):
in the Swiss study, they found that looking at the
red and blue bands that at around thirteen hundred k's
of dry matter, the herbidge mass actually tailed off and
in some cases went to zero. But the grass still
kept growing because the reflectants reached minimum. But the grass
keep growing because it was still absorbing the light kept growing,
but it wasn't the satellites couldn't pick up that difference.
(05:43):
So saturation reflectance is an issue, quite a big issue
in my book. There's ways apparently weighs around that by
measuring different wavebands and what have you. And also if
you measure height of pasture, they can correct the algorithm
by measuring the height. They can do that from space
as well, because they do a measurement on very low
(06:04):
covers or beer ground, and they can measure the height,
which is staggering really because we're talking what twenty twenty
five thirty centimeters and measuring that from five hundred ks
in space is actually I don't know how they do it,
but apparently they can.
Speaker 1 (06:18):
Okay, whether we are talking about the era of AI
or that the industry of AIP, how is that going
to affect like some measuring pasture on farm.
Speaker 2 (06:28):
How's it going to affect?
Speaker 1 (06:29):
Yeah, it's going to be another tool in the toolbox,
is it not?
Speaker 2 (06:32):
It could be providing we get a calibration right and
providing we get these areas like saturation reflectance right as well.
We've got issues with cloud cover, we've got issues with
atmospheric interference as well. So it's a growing science. It's
developing quickly. But the big issue at the moment is
your calibration.
Speaker 1 (06:49):
Right. Are you learning more about AI, for instance, when
you're talking to farmers, because farmers are embracing it more
and more by the day they are from what you're doing.
Do you think it's something we need to embrace as
an industry.
Speaker 2 (07:01):
I think these areas where AI could be probably quite important. Yes,
just a growing industry will become relevant to New Zealand farming,
no question. So the key point from that study is calibration. Calibration, calibration.
That's the important thing. And I'm not convinced that it's
up to speed at the moment.
Speaker 1 (07:22):
And the reasting to see how it pans out. Graham,
always appreciate your time, might need your rank this afternoon.
Graham Butcher fun consultant Grant McMaster is up next.
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