1. Evaluating Remote Sensing DataOr
How to Avoid
Making Great Discoveries by Misinterpreting Data
Richard Kleidman
ARSET-AQ
Applied Remote Sensing Education and Training
A project of NASA Applied Sciences

2. It may take a few seconds to really get the idea behind this comic strip. Interpreting data can be a tricky business.

3. AOD at 550 nm Area Average Plot Giovanni MODIS Daily Instance
June , 2008
What are the two biggest differences between the results for these two sensors and time periods?
Terra
Daily Overpass ~ 10:30 AM local time
Aqua
Daily Overpass ~ 1:30 PM local time

4. Real or Not Real ? You Decide! A Potential Discovery!
AOD at 550 nm Area Average Plot
Giovanni MODIS Daily Instance
June , 2008
A Potential Discovery!
Real or
Not Real ?
You Decide!
What are the two biggest differences between the results for these two sensors and time periods?
Terra
Daily Overpass ~ 10:30 AM local time
Aqua
Daily Overpass ~ 1:30 PM local time

5. AOD at 550 nm Area Average Plot Giovanni MODIS Daily Instance
June , 2008
Hypothesis 1:
The differences in aerosol concentration represent a
Diurnal Cycle with different amounts of aerosol being produced
or transported afternoon and morning.
Hypothesis 2:
The differences in aerosol concentration are
either not real or not significant and
could be caused by
Sensor error
Algorithm error
Sampling error ?
What are the two biggest differences between the results for these two sensors and time periods?
Terra
Daily Overpass ~ 10:30 AM local time
Aqua
Daily Overpass ~ 1:30 PM local time

6. Possible ways to interpret these differences
Real world differences
Leads to a conclusion(s) about aerosols
Can lead to further research about aerosols
Differences due to other factors
Can lead to false conclusion about aerosols
Need to be explored and understood to avoid
similar problems in the future
- Can lead to advances in remote sensing capabilities!
These are two very broad categories. Note from the last point that even discoveries that don’t reflect real world phenomena can be useful and should not be ignored.

7. Remote Sensing Process
Energy Source or Illumination (A)
Recording of Energy by the Sensor (D) 
Transmission, Reception, and Processing (E) 
Interpretation and Analysis (F)
Radiation and the Atmosphere (B) 
Energy Source or Illumination (A) the first requirement for remote sensing is to have an energy source which illuminates or provides electromagnetic energy to the target of interest.
Radiation and the Atmosphere (B) - as the energy travels from its source to the target, it will come in contact with and interact with the atmosphere it passes through. This interaction may take place a second time as the energy travels from the target to the sensor.
 Interaction with the Target (C) - once the energy makes its way to the target through the atmosphere, it interacts with the target depending on the properties of both the target and the radiation
Application (G) - the final element of the remote sensing process is achieved when we apply the information we have been able to extract from the imagery about the target in order to better understand it, reveal some new information, or assist in solving a particular problem
Recording of Energy by the Sensor (D) - after the energy has been scattered by, or emitted from the target, we require a sensor (remote - not in contact with the target) to collect and record the electromagnetic radiation.
Transmission, Reception, and Processing (E) - the energy recorded by the sensor has to be transmitted, often in electronic form, to a receiving and processing station where the data are processed into an image (hardcopy and/or digital)
Interpretation and Analysis (F) - the processed image is interpreted, visually and/or digitally or electronically, to extract information about the target which was illuminated.
(G)
Application
 Interaction with the Target (C) 
Reference: CCRS/CCT

8. Important Factors to Understand
Analysis Tool
Giovanni – provides data in 1 degree resolution
Data Products–
Aqua and Terra Level 2 Products are from a single overpass 10 KM resolution
Aqua and Terra Level 3 Products are global composites in 1 Degree resolution
Black circles - The same region may have very different average values of AOD for this time period.
Maroon squares – There are differences in where there are no values returned for this time period.

9. Important Factors to Understand
Mid – latitude 1° x 1° is about 85 Km x 110 Km
~ Km MODIS retrievals possible
~ Km MODIS retrievals possible
Swath Nadir
Edge
Black circles - The same region may have very different average values of AOD for this time period.
Maroon squares – There are differences in where there are no values returned for this time period.

10. Important Factors to Understand
One MODIS 10 Km Retrieval
Begins life as
400
.5 km (at nadir)
pixels
And ends as
a product
composed of
12 – 120 pixels
Black circles - The same region may have very different average values of AOD for this time period.
Maroon squares – There are differences in where there are no values returned for this time period.

11. Information Necessary to Understand the Results
Data Products–
Aqua and Terra Level 2 Products are in 10 KM resolution
Aqua and Terra Level 3 Products are in 1 Degree resolution
Giovanni provides Level 3 Data in 1 Degree resolution.
Sensor Characteristics –
Aqua and Terra are identical designs
There are some small differences in sensor performance
Black circles - The same region may have very different average values of AOD for this time period.
Maroon squares – There are differences in where there are no values returned for this time period.
Algorithm Details–
Aqua and Terra use the same algorithm.

12. AOD at 550 nm Area Average Plot
June , 2008
Examining other features in this data set and using our
knowledge of the sensor and products can help us to
understand the cause of the differences in mean aerosol.
A blank (white) square has no retrievals for the entire time period.
Aqua
Terra

13. Evaluating Data Understand the sensor characteristics
Understand the product details
Understand the data visualization tools
and outputs.