Lesson 3 of 5 · Gaofen
Gaofen: choose observations that answer a ground question
8 minute lesson · 3 checks along the way
Your goal for this lessonCompare optical and radar observations, and interpret image scale without confusing it with certainty.
In this lesson 3 sections · 3 checks
Using archive links & definitions
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Read & understand
Start with the application
Gaofen is associated with China’s High-Resolution Earth Observation System. Gaofen-1, cataloged as Gao Fen 1-01, launched in 2013 and was an early milestone in building that system. CNSA describes applications including environmental protection, land-resource monitoring and disaster reduction. The useful result is not merely a detailed picture: it is information that can help answer a defined question about a place at a relevant time.
A team mapping a flood might ask which roads cross newly inundated ground. Another team might study seasonal vegetation change. These tasks can require different observation times, wavelengths and processing. The family name alone does not tell the analyst which instrument produced a file. A good starting point is the spacecraft, sensor, acquisition time and product description attached to the actual observation.
Check 1 of 3
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Read & understand
Use complementary kinds of measurement
Gaofen-1 carries an optical wide-field imaging system. Research on its imagery discusses clouds and cloud shadows, which can obscure or confuse the view of the surface. Gaofen-3, cataloged as Gao Fen 3, supplies synthetic-aperture radar observations. Radar measures returned microwave signals rather than producing an ordinary visible-light photograph. Brightness depends on the interaction of the signal with the surface and viewing geometry.
Optical and radar products can complement one another, but combining them is not simply placing two equally colored pictures on top of each other. Research using Gaofen-3 data highlights the problem of aligning observations from different sensors. Compare dates, map coordinates and scale before interpreting a mismatch as real change. A dark patch in radar and a dark patch in an optical image need not represent the same physical cause.
A pixel has two ground dimensions
Original teaching diagram. FICTIONAL GRID. One pixel: 10 m × 10 m. Area per pixel: 100 m². COUNTED PATCH. 12 pixels × 100 m². Total area: 1,200 m². Increasing display size does not create finer measured ground detail.
Open full-size diagram in a new tab: A pixel has two ground dimensionsCheck 2 of 3
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Read & understand
Read scale before identifying an object
In a fictional mapping product, each square pixel represents 10 metres by 10 metres on the ground. One pixel therefore covers 100 square metres. A patch of 12 such pixels covers 1,200 square metres if all twelve belong to the feature being counted. The example uses invented dimensions rather than quoting the performance of any Gaofen instrument or imaging mode.
A narrow road smaller than a pixel can contribute to the recorded signal without being cleanly resolved as a separate shape. Making the display larger does not recover detail the measurement never recorded. To assess a proposed road closure, combine a suitably timed observation with its uncertainty and other relevant information. Gaofen’s different observing approaches are most useful when the analyst connects measurement choices with a practical question, rather than assuming that the sharpest-looking image answers everything.
Check 3 of 3
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Put it together
Your lesson progress
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Explore further · Optional
Go to the source
Explore the evidence behind this lesson. These optional readings and videos open in a new tab.
- Read: CNSA: High-Resolution Earth Observation SystemSupports Gaofen-1’s 2013 milestone and application areas. The old future-tense 2020 forecast is not a current status statement.
- Read: Li and colleagues: clouds in Gaofen-1 imageryOriginal research abstract identifies the WFV optical instrument and cloud/shadow problem. The reported validation accuracy is not generalized to every scene.
- Read: Huang and colleagues: Gaofen-3 radar and optical data fusionOriginal dataset research abstract identifies Gaofen-3 SAR observations and the difficulty of aligning different sensor products.