Remote Sensing C

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Remote Sensing C

Post by pikachu4919 »

2022 Question Marathon Thread for Remote Sensing C.

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Re: Remote Sensing C

Post by gz839918 »

Let's get this marathon started!
  1. What is the most abundant greenhouse gas in total?

  2. What is the most abundant greenhouse gas released from human activity?

  3. What is the difference between active and passive sensing?
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Re: Remote Sensing C

Post by AstroClarinet »

gz839918 wrote: October 2nd, 2021, 8:24 am Let's get this marathon started!
  1. What is the most abundant greenhouse gas in total?

  2. What is the most abundant greenhouse gas released from human activity?

  3. What is the difference between active and passive sensing?
1. Water vapor
2. Carbon dioxide
3. Active sensing is when a satellite produces radiation of its own and detects that radiation once it's reflected/backscattered. Passive sensing is when a sensor detects radiation that hasn't been produced by the satellite and has been reflected/scattered/emitted by the objects it's sensing.
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Re: Remote Sensing C

Post by gz839918 »

Great, your turn!
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Re: Remote Sensing C

Post by AstroClarinet »

1. What is albedo? How does it impact the amount of energy that enters the Earth system?
2. Why don't greenhouse gases affect incoming sunlight & outgoing radiation from Earth's surface equally?
3. OCO-2 and Aura are part of what satellite constellation? What type of orbit do satellites in this satellite constellation have, and why is this type of orbit useful for remote sensing?
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Re: Remote Sensing C

Post by RiverWalker88 »

AstroClarinet wrote: October 9th, 2021, 4:43 pm 1. What is albedo? How does it impact the amount of energy that enters the Earth system?
2. Why don't greenhouse gases affect incoming sunlight & outgoing radiation from Earth's surface equally?
3. OCO-2 and Aura are part of what satellite constellation? What type of orbit do satellites in this satellite constellation have, and why is this type of orbit useful for remote sensing?
I feel the need to comment on the four month delay, but I have no idea what to say.
ONE. Albedo is the fraction of incoming energy that is reflected by a surface. The albedo of the Earth is the amount of energy that is reflected back out into spaaaaaace, and thus not entering the Earth system.
TWO. Incoming sunlight mainly enters the earth at wavelengths that are not reflected by greenhouse gases. However, the energy emitted off of Earth, which is a significantly cooler body than the sun, is reflected back to the surface by greenhouse gases. iirc.
THREE. The A-Train  8-) . They are in a sun-synchronous orbit, an orbit where satellites exactly match the rotation of the earth and will always be in the light (or dark, if they are on the other side). A big advantage of this orbit is for optical passive sensors, that measure reflected sunlight, so that they can collect data at all times.  see here
Next question:

Instructions
This question is best done on a computer, with two browser windows open running split-screen. It is the most efficient way I could think of to make this work.

Open the following link in both windows (or, if you are just using one, open it in the one window).
https://worldview.earthdata.nasa.gov/?v ... 3A00%3A00Z

On the left-hand bar, there are three data sets, Precipitation Total (NLDAS), Soil Moisture (NLDAS), and Vegetation Index (Aqua/MODIS). To toggle these on and off, click the eye icon. They are layered onto the image in the order they are listed (so if you turn "Precipitation Total" off, you will be able to see "Soil Moisture" underneath).

We are observing the Gila National Forest in New Mexico (if you turn everything except vegetation off, it is the big green area north of Deming, west of Truth of Consequences.

To change the time, click the left or right-hand arrows at the bottom of the image, or enter a different year in over the previous one. For this question we are only looking at the month of August, so leave the day and month August 17th.

Part I
  1. How might we detect soil moisture using remote sensing?
  2. Start in 2003, and compare soil moisture to vegetation index (the easiest way is to have one in one window, the other in the other window). Tick the time forward on both until 2019. Does there appear to be a connection between soil moisture and vegetation index? If so, what is it?
  3. Now do the same for precipitation total and vegetation index. Does there appear to be a connection between precipitation total and vegetation index? If so, what is it?
  4. Do the trends you observed or did not observe above make sense? Why or why not?
Part II
MODIS Vegetation Index data only goes back to 2003. Starting at 2019, tick the clock back one year at a time until 1979 (where the NLDAS data stops) for both Precipitation Total and Soil Moisture. Based on this information, answer the following.
  1. Based on trends you observed above, in which year was the forest likely healthiest (there are several acceptable years)?
  2. In which year would we expect to see the fewest high-NDVI areas of the forest if it were observed (again, several acceptable years)? Why?
  3. As you cycle through, write down the years where you would expect the forest health to be really good. Observe if there appear to be more of these in the past, closer to the present, or are they pretty evenly-distributed. Now do the same with particularly bad years.
    Based on your observations, are there any conclusions that we can draw about the climate around this area of New Mexico over time? Why or why not?
I may have gone a little overboard... sorry...
Last edited by RiverWalker88 on May 15th, 2022, 6:35 pm, edited 1 time in total.
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Re: Remote Sensing C

Post by RiverWalker88 »

Aight, looks like I halted the channel. New question:

Below are two images taken by the GOES-16 ABI. The top is in the red band, the bottom is in the blue band.
GOES-16redbandrockies.jpg
GOES-16redbandrockies.jpg (345.65 KiB) Viewed 2960 times
GOES-16bluebandrockies.jpg
GOES-16bluebandrockies.jpg (245.59 KiB) Viewed 2960 times
  1. What does ABI stand for?
  2. Why is the red image clearer than the blue image?
  3. Which of these images is better for resolving surface features?
  4. In order to create a true-color optical image of the Earth, we need three colors from the visible portion of the electromagnetic spectrum. GOES-16 only has two, red and blue. What other color is needed to make a true-color image?
  5. Another band has similar properties to the missing visible band that can be used instead to generate approximately true-color images. What is this band? You can specify the name of this band as it applies to the GOES-16 data, or specify the region of the electromagnetic spectrum.
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Re: Remote Sensing C

Post by RiverWalker88 »

I shall post another question. Hopefully this one can restart the marathon.

Describe how a LiDAR altimeter would work. Is this passive or active remote sensing?
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Re: Remote Sensing C

Post by AstroClarinet »

RiverWalker88 wrote: March 21st, 2022, 1:17 pm I shall post another question. Hopefully this one can restart the marathon.

Describe how a LiDAR altimeter would work. Is this passive or active remote sensing?
Your wish has been granted.
LiDAR altimeters work by sending a laser beam to a distant surface below the remote sensing platform and timing how long it takes for it to return. Since we know the speed of light, we can then determine how far above that surface the remote sensing platform is. Using independent knowledge of how far above sea level the remote sensing platform is, we can determine the altitude of that surface. As the altimeter emits a laser beam and collects the backscattered light, this counts as active remote sensing.
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Re: Remote Sensing C

Post by RiverWalker88 »

AstroClarinet wrote: April 2nd, 2022, 9:59 am
RiverWalker88 wrote: March 21st, 2022, 1:17 pm I shall post another question. Hopefully this one can restart the marathon.

Describe how a LiDAR altimeter would work. Is this passive or active remote sensing?
Your wish has been granted.
LiDAR altimeters work by sending a laser beam to a distant surface below the remote sensing platform and timing how long it takes for it to return. Since we know the speed of light, we can then determine how far above that surface the remote sensing platform is. Using independent knowledge of how far above sea level the remote sensing platform is, we can determine the altitude of that surface. As the altimeter emits a laser beam and collects the backscattered light, this counts as active remote sensing.
Indeed. Your turn.
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