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GMAT9600-无代写-Assignment 2
时间：2023-11-03
GMAT9600 Lab Assignment 2 Page 1
GMAT9600 Lab Assignment 2
Monitoring the 2009 Victorian Bushfires with
Optical Satellite Remote Sensing
DISCLAIMER
Satellite imagery provided for this assignment is for teaching GMAT9600 and hence should not be used for
any other purpose. Students should delete the satellite imagery from their storage as soon as the assignment
is submitted.
1. Background
On Saturday 7th February 2009, the worst bushfires in Australia’s history occurred in Victoria. It lasted for
weeks and 173 people were reported dead. The serious brushfires also destroyed at least 1834 homes,
leaving estimated 7500 people homeless.
Since the area of the bushfires were extremely large, almost the entire Victoria had been impacted. It was
very difficult for traditional monitoring methods to locate regions that had the most serious situation and to
discover new fire spots. In contrast, the spaceborne remote sensing methods which provide large coverage
imagery can easily overcome the problem. Based on this consideration, the GEOS group of UNSW utilised
data from China’s HJ satellite constellation (Environmental Monitoring and Disaster Mitigation) to extract
the bushfire fronts, assisting the corresponding departments of the Victorian government in the emergency
response.
The purpose of this assignment is to use a subset of the same dataset used for this event by GEOS and try to
identify and visualise the locations of bushfires. Comparison to other optical remote sensing data is also
required in order to make a clear sense of what kind of dataset is the best for bushfire identification.
GMAT9600 Lab Assignment 2 Page 2
2. HJ Satellites
China’s HJ satellite constellation is a spaceborne Earth observation system. It is composed of three small
satellites. Two of them are optical satellites (HJ-1A and HJ-1B) which were launched on 6th September 2008,
and the other one is a Radar satellite. The detailed information of HJ-1A and HJ-1B is listed in Table 1.
Table 1. Parameters of HJ-1A and HJ-1B
Satellite Sensor Band ID
Bandwidth
(µm)
Spatial Resolution
(m) Swath Width (km)
Revisit Time
(day)
HJ-1A CCD Camera
1 0.43-0.52 30
360 (single camera)，700 (double
cameras) 4
2 0.52-0.60 30
3 0.63-0.69 30
4 0.76-0.90 30
HJ-1B
CCD Camera
1 0.43-0.52 30
360 (single camera), 700 (double
cameras) 4
2 0.52-0.60 30
3 0.63-0.69 30
4 0.76-0.90 30
Infrared
Camera
5 0.75-1.10
150
720 4
6 1.55-1.75
7 3.50-3.90
8 10.5-12.5 300
In the area of optical remote sensing, bands (or channels) of a sensor normally have individual names and
can be used for relevant applications. The channel names and the major targeted applications for HJ-1A and
HJ-1B are listed in Table 2.
Table 2. Channel information of HJ-1A and HJ-1B
Band range (µm) Channel Name Applications
0.43-0.52 Blue Waterbody detection
0.52-0.60 Green Vegetation coverage
0.63-0.69 Red Land features
0.76-0.90 Near Infrared Soil humidity, water boundary and vegetation
0.75-1.10 Near Infrared Water boundary, farmland and land features
1.55-1.75 Shortwave Infrared Soil classification, cloud and snow area
3.50-3.90 Mid Infrared Radiation from high temperature objects, feature identification at night
10.5-12.5 Thermal Radiation from objects with normal temperature, feature identification at night
By using images from a certain band of HJ satellites or combining some bands, the bushfires could be
observed.
3. Description of the Experimental Imagery
GMAT9600 Lab Assignment 2 Page 3
To identify the bushfires that started on 7th February 2009, a group of HJ-1B data acquired a day later on 8th
February 2009 was used. Data from both the CCD camera and the infrared camera will be provided.
The last number of the file names indicates the band ID of the HJ data. For example, “HJ1B-CCD2-400-
166-20090208-L20000065990-2-M.tif” is the image file for CCD band 2 and “HJ1B-IRS-398-168-
20090208-L20000065593-1-M.tif” is from Infrared band 1 which is the 5th band according to Table 1.
Meanwhile, in order to show the advantages of using HJ data to identify bushfires, data from MODIS
satellite which was acquired on the same day (8th February 2009) will be provided for comparison. MODIS
is a multi-spectrum optical satellite sensor. It provides images from 36 bands. In this experiment, only seven
bands are useful and their detailed information is given in Table 3. For introductions of other bands, please
refer to http://modis.gsfc.nasa.gov/about/specifications.php.
Table 3. Band Information of MODIS Data
Band ID Subset Data ID Band Name in Subset Bandwidth (µm) Spatial Resolution (m) Primary Use
1
subsetdata 4
Band_1 0.620 – 0.670
250 Land/Cloud/Aerosols
Boundaries 2 Band_2 0.841 – 0.876
3
subsetdata 7
Band_1 0.459 – 0.479
500 Land/Cloud/Aerosols
Properties
4 Band_2 0.545 – 0.565
5 Band_3 1.230 – 1.250
6 Band_4 1.628 – 1.652
7 Band_5 2.105 – 2.155
In this experiment, the key analysing method is to observe images from each band of HJ-1B and to colour-
code multiple bands to make the bushfire areas distinct. Therefore, choosing appropriate bands is very
important here. Please refer to Table 1 to Table 3 for data selection.
GMAT9600 Lab Assignment 2 Page 4
4. Guidelines for Data Processing
Students will use ArcGIS software to process the data. The two major components of the software are
ArcMap and ArcCatalog. To launch ArcMap, go to “Start >> Programs >> ArcGIS >> ArcMap 10”. In the
same menu, the shortcut of “ArcCatalog 10” can be found as well. Or you can find the ArcCatalog from the
toolbar (Shown in Fig 1). The workspace of ArcMap and ArcCatalog are shown in Fig 1 and Fig 2
respectively.
If you use your own PC without ArcMap, you can access ArcMap by “myaccessunsw” (shown in Fig 3 and
4) and find the ArcCatalog in the toolbar.
Fig 1. The Window of ArcMap Software
Fig 2. The Window of ArcCatalog Software
GMAT9600 Lab Assignment 2 Page 5
Fig 3. myAccess search result in the browser
Fig 4. ArcMap logo in the App store of “myaccessunsw”
ArcMap is a workspace for viewing and processing image data. To start image analysis, the first step is to
set the coordinate system so that the data with geo-coordinate information can be displayed correctly. Right
click “Layers” in the left sub-window of ArcMap and then select “Properties”. A dialog as shown in Fig 5
will pop out and select “Coordinate System”. The “Coordinate System” tab can be set to either the WGS
1984 coordinate system or its projection “WGS 1984 UTM Zone 55S”. WGS 1984 can be found in
GMAT9600 Lab Assignment 2 Page 6
“Geographic Coordinate Systems >> World” and WGS 1984 UTM Zone 55S is in “Projected Coordinate
Systems >> UTM >> WGS 1984 >> Southern Hemisphere”.
Fig 5. Setting Coordinate Systems of a Workspace
To add data into ArcMap, go to ArcCatalog. Browse the “Location” to find data in corresponding folders.
Make sure that each data has been assigned to a correct coordinate system. It can be found by right clicking
the data and then selecting “Properties” in the menu. An example Properties window is given in Fig 6. In
this window, detailed information of the data can be found, including the data size in “Columns and Rows”,
GMAT9600 Lab Assignment 2 Page 7
the spatial resolution in “Cellsize (X, Y)” and the coordinate information in “Spatial Reference”. If the
information of provided data is correct, simply drag it from ArcCatalog to ArcMap to display.
Fig 6. “Properties” Window of a Data
Once a data has been added to ArcMap, you can tick on or off the checkbox on the left to enable or disable
the display. It is very useful while comparing multiple images for the same location. You can also zoom in
or zoom out an image by the magnifier icons in the toolbar to see the details or the overview.
After several bands of a dataset are added to ArcMap, you can implement the colour composition. It is a
useful tool for highlighting certain ground features. Click the red box button in the toolbar to enable the
ArcMap toolbox. Go to “Data Management Tools >> Raster >> Raster Processing”, and then click the
“Composite Bands” tag. If Raster tool cannot be found or does not work, please click “Customize >>
Extensions >> Spatial Analyst” first to enable the Raster tool (Shown in Fig 7).
After select “Data Management Tools >> Raster >> Raster Processing >> Composite Bands”, the toolbox of
“Composite Bands” shown as Fig 8 will pop up.
GMAT9600 Lab Assignment 2 Page 8
Fig 7. Extensions check tool
Select “Input Rasters” for colour composition and then adjust the orders of selected bands. The first raster
(top to bottom) will be represented in Red colour and the second shown as Green with the third one Blue.
Therefore, if the RGB colours are assigned with images from Red, Green and Blue bands, a result called
true-colour image can be obtained. Otherwise, the composed data are named false-colour images.
Fig 8. Composite Bands Toolbox
GMAT9600 Lab Assignment 2 Page 9
5. Lab report and Quiz Student Name: ID:
NOTE: use your own results when you answer the following questions in your report for the lab
assignment
a. Add all HJ and MODIS data into ArcMap and compare the difference between them. Refer to the
“Raster Dataset Properties” for detailed information.
Questions: The CCD images of HJ-1B were taken at the same time of its infrared images. Why their
spatial coverage is not the same? Why the coverage of infrared images is larger?
b. Produce true colour images for both HJ CCD data and MODIS images.
Questions: What is the band combination of true colour images for HJ and MODIS? What is the key
problem of identifying bushfires from these images directly?
c. Try to find out bushfires by observing each band of HJ data or combining different bands for true-colour
and false-colour results.
Questions: How can you identify the bushfires? What is the principle of your method?
GMAT9600 Lab Assignment 2 Page 10
GMAT9600 Lab Assignment 2 Page 11
6. Group Arrangement:
The Computer Lab in the Civil Engineering Building Lab 201 will be used for the assignment. There will be
enough computers in the lab for every student. Each student will be allocated with one computer. It is
important that each student has to complete the assignment by himself/herself.
7. Rules for submitting the Lab Reports and Assignments
• The lab reports and assignments need to be submitted by email. (For the student in GMAT9600, email to
GMAT9600@geos.org.au)
• Only one file per assignment in Word format.
• Name your file as "StudentID-YourLastName-CoureID-assignment.doc". (For example: z3012345-
Charlton-GMAT9600- assignment1.doc).
• Your email must have your name, student ID and the assignment name in the subject.
• Do NOT send multiple submissions for the same assignment. If you have to re-submit, you need to
request permission from the course convenor.
• NOTE: Failing to submit the file with correct format and/or naming convention will result in
deduction of 1 mark.
8. Performance Evaluation:
It is important for each student to complete activities and answer questions given in Section 5 and show
them to the lab supervisor. The following marks will be given by the lab:
• Activity “a” and related quiz (5 marks)
• Activity “b” and related quiz (8 marks)
• Activity “c” and related quiz (12 marks)
GMAT9600 Lab Assignment 2
Monitoring the 2009 Victorian Bushfires with
Optical Satellite Remote Sensing
DISCLAIMER
Satellite imagery provided for this assignment is for teaching GMAT9600 and hence should not be used for
any other purpose. Students should delete the satellite imagery from their storage as soon as the assignment
is submitted.
1. Background
On Saturday 7th February 2009, the worst bushfires in Australia’s history occurred in Victoria. It lasted for
weeks and 173 people were reported dead. The serious brushfires also destroyed at least 1834 homes,
leaving estimated 7500 people homeless.
Since the area of the bushfires were extremely large, almost the entire Victoria had been impacted. It was
very difficult for traditional monitoring methods to locate regions that had the most serious situation and to
discover new fire spots. In contrast, the spaceborne remote sensing methods which provide large coverage
imagery can easily overcome the problem. Based on this consideration, the GEOS group of UNSW utilised
data from China’s HJ satellite constellation (Environmental Monitoring and Disaster Mitigation) to extract
the bushfire fronts, assisting the corresponding departments of the Victorian government in the emergency
response.
The purpose of this assignment is to use a subset of the same dataset used for this event by GEOS and try to
identify and visualise the locations of bushfires. Comparison to other optical remote sensing data is also
required in order to make a clear sense of what kind of dataset is the best for bushfire identification.
GMAT9600 Lab Assignment 2 Page 2
2. HJ Satellites
China’s HJ satellite constellation is a spaceborne Earth observation system. It is composed of three small
satellites. Two of them are optical satellites (HJ-1A and HJ-1B) which were launched on 6th September 2008,
and the other one is a Radar satellite. The detailed information of HJ-1A and HJ-1B is listed in Table 1.
Table 1. Parameters of HJ-1A and HJ-1B
Satellite Sensor Band ID
Bandwidth
(µm)
Spatial Resolution
(m) Swath Width (km)
Revisit Time
(day)
HJ-1A CCD Camera
1 0.43-0.52 30
360 (single camera)，700 (double
cameras) 4
2 0.52-0.60 30
3 0.63-0.69 30
4 0.76-0.90 30
HJ-1B
CCD Camera
1 0.43-0.52 30
360 (single camera), 700 (double
cameras) 4
2 0.52-0.60 30
3 0.63-0.69 30
4 0.76-0.90 30
Infrared
Camera
5 0.75-1.10
150
720 4
6 1.55-1.75
7 3.50-3.90
8 10.5-12.5 300
In the area of optical remote sensing, bands (or channels) of a sensor normally have individual names and
can be used for relevant applications. The channel names and the major targeted applications for HJ-1A and
HJ-1B are listed in Table 2.
Table 2. Channel information of HJ-1A and HJ-1B
Band range (µm) Channel Name Applications
0.43-0.52 Blue Waterbody detection
0.52-0.60 Green Vegetation coverage
0.63-0.69 Red Land features
0.76-0.90 Near Infrared Soil humidity, water boundary and vegetation
0.75-1.10 Near Infrared Water boundary, farmland and land features
1.55-1.75 Shortwave Infrared Soil classification, cloud and snow area
3.50-3.90 Mid Infrared Radiation from high temperature objects, feature identification at night
10.5-12.5 Thermal Radiation from objects with normal temperature, feature identification at night
By using images from a certain band of HJ satellites or combining some bands, the bushfires could be
observed.
3. Description of the Experimental Imagery
GMAT9600 Lab Assignment 2 Page 3
To identify the bushfires that started on 7th February 2009, a group of HJ-1B data acquired a day later on 8th
February 2009 was used. Data from both the CCD camera and the infrared camera will be provided.
The last number of the file names indicates the band ID of the HJ data. For example, “HJ1B-CCD2-400-
166-20090208-L20000065990-2-M.tif” is the image file for CCD band 2 and “HJ1B-IRS-398-168-
20090208-L20000065593-1-M.tif” is from Infrared band 1 which is the 5th band according to Table 1.
Meanwhile, in order to show the advantages of using HJ data to identify bushfires, data from MODIS
satellite which was acquired on the same day (8th February 2009) will be provided for comparison. MODIS
is a multi-spectrum optical satellite sensor. It provides images from 36 bands. In this experiment, only seven
bands are useful and their detailed information is given in Table 3. For introductions of other bands, please
refer to http://modis.gsfc.nasa.gov/about/specifications.php.
Table 3. Band Information of MODIS Data
Band ID Subset Data ID Band Name in Subset Bandwidth (µm) Spatial Resolution (m) Primary Use
1
subsetdata 4
Band_1 0.620 – 0.670
250 Land/Cloud/Aerosols
Boundaries 2 Band_2 0.841 – 0.876
3
subsetdata 7
Band_1 0.459 – 0.479
500 Land/Cloud/Aerosols
Properties
4 Band_2 0.545 – 0.565
5 Band_3 1.230 – 1.250
6 Band_4 1.628 – 1.652
7 Band_5 2.105 – 2.155
In this experiment, the key analysing method is to observe images from each band of HJ-1B and to colour-
code multiple bands to make the bushfire areas distinct. Therefore, choosing appropriate bands is very
important here. Please refer to Table 1 to Table 3 for data selection.
GMAT9600 Lab Assignment 2 Page 4
4. Guidelines for Data Processing
Students will use ArcGIS software to process the data. The two major components of the software are
ArcMap and ArcCatalog. To launch ArcMap, go to “Start >> Programs >> ArcGIS >> ArcMap 10”. In the
same menu, the shortcut of “ArcCatalog 10” can be found as well. Or you can find the ArcCatalog from the
toolbar (Shown in Fig 1). The workspace of ArcMap and ArcCatalog are shown in Fig 1 and Fig 2
respectively.
If you use your own PC without ArcMap, you can access ArcMap by “myaccessunsw” (shown in Fig 3 and
4) and find the ArcCatalog in the toolbar.
Fig 1. The Window of ArcMap Software
Fig 2. The Window of ArcCatalog Software
GMAT9600 Lab Assignment 2 Page 5
Fig 3. myAccess search result in the browser
Fig 4. ArcMap logo in the App store of “myaccessunsw”
ArcMap is a workspace for viewing and processing image data. To start image analysis, the first step is to
set the coordinate system so that the data with geo-coordinate information can be displayed correctly. Right
click “Layers” in the left sub-window of ArcMap and then select “Properties”. A dialog as shown in Fig 5
will pop out and select “Coordinate System”. The “Coordinate System” tab can be set to either the WGS
1984 coordinate system or its projection “WGS 1984 UTM Zone 55S”. WGS 1984 can be found in
GMAT9600 Lab Assignment 2 Page 6
“Geographic Coordinate Systems >> World” and WGS 1984 UTM Zone 55S is in “Projected Coordinate
Systems >> UTM >> WGS 1984 >> Southern Hemisphere”.
Fig 5. Setting Coordinate Systems of a Workspace
To add data into ArcMap, go to ArcCatalog. Browse the “Location” to find data in corresponding folders.
Make sure that each data has been assigned to a correct coordinate system. It can be found by right clicking
the data and then selecting “Properties” in the menu. An example Properties window is given in Fig 6. In
this window, detailed information of the data can be found, including the data size in “Columns and Rows”,
GMAT9600 Lab Assignment 2 Page 7
the spatial resolution in “Cellsize (X, Y)” and the coordinate information in “Spatial Reference”. If the
information of provided data is correct, simply drag it from ArcCatalog to ArcMap to display.
Fig 6. “Properties” Window of a Data
Once a data has been added to ArcMap, you can tick on or off the checkbox on the left to enable or disable
the display. It is very useful while comparing multiple images for the same location. You can also zoom in
or zoom out an image by the magnifier icons in the toolbar to see the details or the overview.
After several bands of a dataset are added to ArcMap, you can implement the colour composition. It is a
useful tool for highlighting certain ground features. Click the red box button in the toolbar to enable the
ArcMap toolbox. Go to “Data Management Tools >> Raster >> Raster Processing”, and then click the
“Composite Bands” tag. If Raster tool cannot be found or does not work, please click “Customize >>
Extensions >> Spatial Analyst” first to enable the Raster tool (Shown in Fig 7).
After select “Data Management Tools >> Raster >> Raster Processing >> Composite Bands”, the toolbox of
“Composite Bands” shown as Fig 8 will pop up.
GMAT9600 Lab Assignment 2 Page 8
Fig 7. Extensions check tool
Select “Input Rasters” for colour composition and then adjust the orders of selected bands. The first raster
(top to bottom) will be represented in Red colour and the second shown as Green with the third one Blue.
Therefore, if the RGB colours are assigned with images from Red, Green and Blue bands, a result called
true-colour image can be obtained. Otherwise, the composed data are named false-colour images.
Fig 8. Composite Bands Toolbox
GMAT9600 Lab Assignment 2 Page 9
5. Lab report and Quiz Student Name: ID:
NOTE: use your own results when you answer the following questions in your report for the lab
assignment
a. Add all HJ and MODIS data into ArcMap and compare the difference between them. Refer to the
“Raster Dataset Properties” for detailed information.
Questions: The CCD images of HJ-1B were taken at the same time of its infrared images. Why their
spatial coverage is not the same? Why the coverage of infrared images is larger?
b. Produce true colour images for both HJ CCD data and MODIS images.
Questions: What is the band combination of true colour images for HJ and MODIS? What is the key
problem of identifying bushfires from these images directly?
c. Try to find out bushfires by observing each band of HJ data or combining different bands for true-colour
and false-colour results.
Questions: How can you identify the bushfires? What is the principle of your method?
GMAT9600 Lab Assignment 2 Page 10
GMAT9600 Lab Assignment 2 Page 11
6. Group Arrangement:
The Computer Lab in the Civil Engineering Building Lab 201 will be used for the assignment. There will be
enough computers in the lab for every student. Each student will be allocated with one computer. It is
important that each student has to complete the assignment by himself/herself.
7. Rules for submitting the Lab Reports and Assignments
• The lab reports and assignments need to be submitted by email. (For the student in GMAT9600, email to
GMAT9600@geos.org.au)
• Only one file per assignment in Word format.
• Name your file as "StudentID-YourLastName-CoureID-assignment.doc". (For example: z3012345-
Charlton-GMAT9600- assignment1.doc).
• Your email must have your name, student ID and the assignment name in the subject.
• Do NOT send multiple submissions for the same assignment. If you have to re-submit, you need to
request permission from the course convenor.
• NOTE: Failing to submit the file with correct format and/or naming convention will result in
deduction of 1 mark.
8. Performance Evaluation:
It is important for each student to complete activities and answer questions given in Section 5 and show
them to the lab supervisor. The following marks will be given by the lab:
• Activity “a” and related quiz (5 marks)
• Activity “b” and related quiz (8 marks)
• Activity “c” and related quiz (12 marks)
