PICAXE will not start collecting data
or triggering the cameras.
J2 and J3 are Camera Ports. Two
modified cameras (wires soldered to
their shutter buttons) plug into these
ports. The PICAXE triggers the
cameras to take pictures regularly
during a mission by using the HIGH
RL2 controls power to the
temperature sensor (U5). The LM335
generates heat, and I’ve noticed its
temperature is greater than the air
temperature at high altitudes (where
there’s very little air). This relay is an
experiment to see if shutting down
the LM335 between readings will
improve its accuracy in near vacuum
There are eight photometer
circuits in the flight computer, of
which two are shown in the
schematic. Table 1 shows the
recommended resistors for each
color of LED. Be warned, however,
that your mileage may vary
depending on the intensity and
sensitivity of the LEDs you select.
Use the PICAXE’s READADC and
READADC10 commands to digitize
the output from the LEDs. Which
command you use depends on the
LED and its current output.
Experiment with this before
trying to collect data on a near space
It’s not near space season quite
yet, so I’ve been testing the
BalloonSat Photometer on my patio.
The two graphs in Figures 4 and 5
are the results of letting the
photometer record data for several
hours during the morning.
Because each LED responds
differently to light intensity, I divided
each LED reading by the average of
all that LED’s readings. This
normalizes the curves to an extent
and makes it easier to compare them
to one another.
The thing to notice in Figure 4 is
not that the sky became brighter as
the sun rose higher (as expected),
but that it shows that clouds passed
over the sun twice; first at between
10:00 and 10: 30, and again at 11:00
to 11: 30. The second cloud had a
larger impact on sky brightness than
More importantly, you’ll notice
that the 940 nm IR intensity lagged
behind the 890 nm IR intensity
during the second cloud passage.
The next chart looks just at the ratio
of 940 nm to 890 nm IR intensities.
Notice the large drop of 940 nm
IR compared to 890 nm IR between
11: 20 and 11: 40 AM. Most likely, this
happened because of the water
vapor contained within the cloud.
Therefore, it appears that sunlight
was shining through more water
vapor in the cloud during this time
because more 940 nm IR was
absorbed than 890 nm IR. I don’t
know of a better way to detect water
vapor in clouds than this.
Interestingly enough, this data
was collected in mid-December
when I would think most clouds are
water ice and not water droplets. I
wish I were better prepared for this
result because I would have
photographed the cloud in long-wave
infrared to see if this cloud was
significantly warmer compared to
The BalloonSat photometer flight
12 April 2017
FIGURE 4. This is photometer data collected from
8: 30 AM to 12: 20 PM.
FIGURE 5. Now we’re looking at just the two
infrared wavelengths. As mentioned by Mr.
Mims, water vapor absorbs 940 nm IR more than
it absorbs 890 nm IR.
IR 940 nm 100K
IR 890 nm 100K
Red 660 nm 1M
Orange 620nm 1M
Yellow 590 nm 1M
Green 500 nm 1M
Blue 470 nm 10M
Violet/UV 400 nm 10M
I’d like to thank Forrest Mims for
helping me to understand how LED
photometers work. He has always
been a great encouragement for
amateur scientists everywhere.