ECEn 568 Microwave Remote Sensing Data Analysis Assignment
For the data analysis assignment, you will conduct an original research project using
an actual satellite microwave data set and write a journal-style paper to report
your results. In conjunction with the instructor select a data set and project.
Several are suggested below. You are strongly encouraged to develop you own research problem.
It is expected that your project will take 40-60 hours of work at the minimium
to do the data analysis and write up your paper. You will have to become familiar
with the particular microwave sensor and how it works, the data set, how to read and analyze
the data, and then conduct an original analysis of the data. You will be expected to
make a short (15 min) oral presentation describing the results of your experiement.
The goal of this assignment is to give you some experience at looking at a
new (and initially unfamiliar) problem. To "really" work the problem in detail
will require more time than we can spend in this little assignment. As a result,
you can really only begin the project. However, enjoy the experience. Try to
make as much progress as you can.
Remember: the key result is the writeup.
Excellent work may be submitted to a conference such as IGARSS or a journal
such as TGARS or GRSL. One of these research projects could become the foundation of
a good Master's Thesis. Both of these have happened in previous classes.
The following is a list of potential research projects; however, I am open
to your suggestions and I encourage you to develop an original project.
If you have a pet research project you would like to use,
see me. In any case, I must approve your selected project.
Note: sample data sets and reader software are only available to students
currently enrolled in the course at BYU.
OSCAT
The Indian OceanSat-2 scatterometer (OSCAT) is a spaceborne scatterometer launched in 2009 and operated through the start of 2014.. It is very similar to SeaWinds. This similarity can be exploited to extend the climate record started by SeaWinds, but this requires dealing with the differences in the two sensors. Key differences include the local-time-of-day of the observations and the observation incidence angles. BYU has
produced an extensive set of images of the land and ice regions of the earth as part of the Scatterometer Climate Record Pathfinder project.
Software, documentation, and data for BYU products is available via from the Scatterometer
Climate Record Pathfinder (URL https://www.scp.byu.edu).
Assignment:
Select one (1) analyze OSCAT data to evaluate the wind measurement accuracy against
either bouys or subjective analyses, (2) analyze the effectiveness of OSCAT
data for measuring landcover characteristics such as canopy density, rain detection, etc.
(3) cross-calibrate data from OSCAT and SeaWinds to study time-of-day effects over land or ice. (4) study
a time series of SeaWindsa + OSCAT backscatter images to evaluate seasonal and/or long term changes in some area
of Earth. (5) use scattering theory to "explain" the backscatter features seen in SeaWinds backscatter
images, including the temporal evolution.
Data and code:
Software, documentation,
and data for BYU products is available via from the Scatterometer
Climate Record Pathfinder (URL https://www.scp.byu.edu) and from Dr. Long.
ASCAT
The European Space Agency (ESA) has flown a number of C-band scatterometers, including 3 Advanced Scatterometers (ASCATs). BYU has produced an extensive set of images of the land and ice regions of the earth as part of the Scatterometer Climate Record Pathfinder project. Software, documentation, and data for BYU products is available via from the Scatterometer Climate Record Pathfinder (URL https://www.scp.byu.edu). Assignment: Select one (1) analyze ASCAT data to evaluate the wind measurement accuracy against either bouys or subjective analyses, (2) analyze the effectiveness of ASCAT data for measuring landcover characteristics such as canopy density, rain detection, etc. (3) cross-calibrate data from ASCAT and other sensors. (4) study a time series of ASCAT backscatter images to evaluate seasonal and/or long term changes in some area of Earth. (5) use scattering theory to "explain" the backscatter features seen in SeaWinds backscatter images, including the temporal evolution.
Data and code:
Software, documentation, and data for BYU products is available via from the Scatterometer
Climate Record Pathfinder (URL https://www.scp.byu.edu) and from Dr. Long.
SeaWinds
SeaWinds is a spaceborne scatterometer launched aboard QuikSCAT in 1999, with second one launched in Dec. 2002 aboard
ADEOS-2. While ADEOS-2 operated for only 10 months, over 10 years of QuikSCAT data was been collected,
an enormous data set of Ku-band sigma-0 measurements
over the Earth's surface at two incidence angles and a variety of azimuth angles.
During the so-called "tandem mission".,when both SeaWinds instruments were operating, it is possible
to resolve daily diurnal cycles.
While originally designed to measure winds over the
ocean, SeaWinds data has also been successfully use for land and ice observations. BYU has
produced an extensive set of images of the land and ice regions of the earth as part of the
Scatterometer Climate Record Pathfinder project.
Two forms of data are available: (1) JPL-produced data files containing wind measurements
and (2) BYU-produced backscatter imagery. Data and software for the former
is available from the JPL
Physical Oceanography Distributed Active Archive center. Software, documentation,
and data for BYU products is available via from the Scatterometer
Climate Record Pathfinder (URL https://www.scp.byu.edu).
Assignment:
Select one (1) analyze SeaWinds L2B wind data to evaluate the wind measurement accuracy against
either bouys or subjective analyses, (2) analyze the effectiveness of SeaWinds
data for measuring landcover characteristics such as canopy density, rain detection, etc.
(3) use tandem mission data to study time-of-day effects over land or ice. (4) study
a time series of backscatter images to evaluate seasonal and/or long term changes in some area
of Earth. (5) use scattering theory to "explain" the backscatter features seen in SeaWinds backscatter
images, including the temporal evolution. (6) use seasonal histograms of backscatter over
sea ice in the Arctic to identify and map multi-year sea ice.
Data and code:
Two forms of data are available: (1) JPL-produced data files containing sigma-0
and wind measurements and (2) BYU-produced imagry. Data and software for the former
is available through Dr. Long and from the JPL
Physical Oceanography Distributed Active Archive center. Software, documentation,
and data for BYU products is available via from the Scatterometer
Climate Record Pathfinder (URL https://www.scp.byu.edu).
NSCAT
The NASA Scatterometer (NSCAT) is a spaceborne
scatterometer which flew for 9 months during 1996-97. It collected a huge data
set of Ku-band sigma-0 measurements over the Earth's surface at dual polarization over a wide range of incidence angles.
While originally designed to measure winds over the ocean, it has also been successfully used for
land and ice observations. Two forms of data are available: (1) JPL-produced data files containing sigma-0
and wind measurements and (2) BYU-produced imagry. Data and software for the former
is available through Dr. Long and from the JPL
Physical Oceanography Distributed Active Archive center. Software, documentation,
and data for BYU products is available via from the Scatterometer
Climate Record Pathfinder (URL https://www.scp.byu.edu).
Assignment:
Either (1) analyze NSCAT data to evaluate the wind measurement accuracy against
either bous or subjective analyses or (2) analyze the effectiveness of NSCAT data
for measuring landcover characteristics such as canopy density, etc.
Data and code:
Two forms of data are available: (1) JPL-produced data files containing sigma-0
and wind measurements and (2) BYU-produced imagry. Software for the former is
available with hardcopy documentation from Dr. Long. Software,
documentation, and sample data for the latter is available via MERS
web site. Land Image data is available from the Scatterometer
Climate Record Pathfinder (URL https://www.scp.byu.edu).
YINSAR
SAR technology is becoming increasing important. BYU has developed a compact,
low cost interferometric SAR known as YINSAR (see the MERS
web site). YINSAR has been used extensively for landslide
and archeological research.
Assignment:
(1) Analyze the topographic accuracy of YINSAR data or (2) develop methods for visualizing landlide flow
Data and code:
See the instructor.
SIR-C/X-SAR
SIR-C/X-SAR are spaceborne SAR systems which fly aboard the space shuttle. Hundreds
of SAR scenes have been collected.
Assignment:
Demonstrate the use of SAR imagery in land cover analysis, mapping, and time series
analysis.
Data and code:
We have a set of CD-roms of processed SIR-C/X-SAR data obtain from NASA. Data
is also available for download directly from JPL. An on-line catalog and documentation
are available at the NASA SIRC Radar web
site. You can use JPL's coverage map to determine the particular data take,
image, and CD-rom number (e.g. SIRC_FL1_51). We currently have the following CD-roms:
SIR-C Flight 1: SIRC_FL1_01 through SIRC_FL1_55
SIR-C Flight 2: SIRC_FL2_01 through SIRC_FL2_46
X-SAR Flight 1: SRX_FL1_001 through SRX_FL1_049
We also have SIRC_ED02, an educational CD.
See Dr. Long about obtaining access to the CDs. They have to be checked out
and returned. Data is also available on line from JPL. Alternately, you can
analyze some of the SAR data collected by BYU SAR systems.
SSM/I, SSMIS, or AMSR
Passive microwave radiometers such as the Special Sensor Microwave/Imager (SSM/I)
or the Advanced Microwave Sensor Radiometer (AMSR) are used primarily for atmospheric
and ocean surface observation. However, they can also be used for land and ice
studies.
Assignment: (choose one)
(a) Analyze the spatial/temporal distribution of rain from SSM/I or AMSR data
over either ocean or rainforest regions. (b) Evaluate the utility of image data
for sea ice or vegetation classification.
Data and code:
You can also order data from the National Snow and Ice Data Center (NSIDC) at https://nsidc.org/.
This site has additional documentation and information. SSM/I and AMSR-E
data has been processed into images here at BYU. See the instructor for details.
TRMM-PR
The Tropical Rain Mapping Mission (TRMM)
carries both a multi-channel radiometer and a Ku-band precipitation radar (PR)
designed to measure rain over the tropics. The PR has a 4 km spatial resolution
and 250 m vertical resolution while the TRMM radiometer has variable resolution.
Assignment: (choose one)
(a) Analyze the spatial/temoporal distribution of rain from TRMM data and the
relationship between rain and the surface backscatter over tropical rainforest
regions. (b) Compare collocated TRMM radiometer and PR data over tropical rainforest
regions with and without rain.
Data and code:
TRMM has a lot of data products all available from NASA at https://eospso.nasa.gov/missions/spaceborne-imaging-radar-c
YSCAT
YSCAT
is a BYU-developed ultra-wideband tower-mounted scatterometer which was deployed
for 6 months on a rsearch tower in Lake Ontario and 6 months on an oil platform
in the Gulf of Mexico. YSCAT collected a time-series of sigma-0 measurements versus
environmental parameters.
Assignment:
Either (a) analyze the summary sigma-0 data set to develop a broad band model
function relating vector wind and sigma-0; (b) analyze the sensitivity of sigma-0
to wave parameters including wave slope; or (c) analyze the complete YSCAT data
set for wind speed slope sensivity.
Data and code:
Original source code for processing the raw YSCAT data is availabe from Dr. Long.
ZSCAT
ZSCAT is a pair of small CW scatterometer systems which were deployed along side
YSCAT.
One was mounted at nadir while the other operated at 10 deg incidence.
Data and code:
Original source code for processing the raw ZSCAT data is available from Dr. Long.
Assignment:
Analyze ZSCAT data to demonstrate the senstivity of sigma-0 to the directional
wave spectrum.
Multisensor Analyses
Some of the most interesting recent work in microwave remote sensing comes from
sensor fusion (using multiple sensors).
Assignment: (choose one)
(a) Collocate (in time and space) SeaWinds and TRMM PR data over tropical rain
forests and evaluate the effects of rain on the measurements. (b) Compare collocated
TRMM radiometer and SSM/I data over land regions. (c) Compare collocated TRMM
PR and SeaWinds data over land regions.
Other Options
Think of something interesting and propose it to the instructor.
Report and Presntation Grading Rubbics
ECEn 568 Radar and Communications
Fall 2020 Sample Oral Presentation Evaluation Form
Presentor's Name: _______________________
Presentation Title: ________________________
Evaluator's name: ________________________
Evaluations (1=Poor, 3=Average,5=Excellent):
Overall clarity of presentation: _____
Was presentations clear and easy to follow?
Organization: _____
Was presentation logically and well organized?
Technical Detail: ______
Did presentation have an appropriate level of technical detail? Was it is complete?
Presentor's preparation: _____
Did presentor appear to be well prepared?
Presentor's Level of Understanding: _____
Did presentor appear to understand the material being presented?
Question Answering: _____
Did presentor answer questions well?
Overall Presentation Evaluation: ______
How did you like the overall report?
Total (summed) score: (of 35)
Opinion: (1=disagree strongly, 3=neutral, 5=agree strongly)
The presentation was interesting to me: ______
I liked the presentation: _____
I like the presenter: _____
I liked the subject material: ______
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ECEn 568 Radar and Communication
Fall 2020 Sample Report Evaluation Form
Author's Name: ________________
Evaluator's Name: ______________________
Evaluation scores (1=Poor, 3=Average,5=Excellent):
Clarity of presentation: ______
Is text clear and easy to follow?
Technical detail: _____
Does text have an appropriate level of technical detail? Is is complete?
Depth: ______
Does the text present the material in adequate depth?
English, Grammar, Spelling, etc.: ______
Is text free from English, grammar, and spelling errors and properly formatted?
Organization and Outline: ______
Is the text logically and well organized? Do conclusions logically follow?
Figures, Graphics: ______
Are figures and graphics clear and attractive?
Overall Presentation Evaluation: _____
How did you like the overall report?
Total (sum) score: (of 35) ______
Last revised: Aug. 2022