COINS Agri-Water Hackathon

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Lesson 1: Advanced technologies for in-situ data collection

8 Topics
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1 Quiz
- 9. Short Quiz: Advanced Technologies for In-Situ Data Collection
Lesson 2: Remote sensing-based vegetation mapping

8 Topics
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1 Quiz
- 9. Short Quiz: Remote Sensing-Based Vegetation Mapping
Lesson 3: Biodiversity Assesment

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Quiz 2 of 2

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9. Short Quiz: Remote Sensing-Based Vegetation Mapping

Henryk Hodam

COINS Agri-Water Hackathon
Lesson 2: Remote sensing-based vegetation mapping
9. Short Quiz: Remote Sensing-Based Vegetation Mapping

Test your knowledge of the key concepts covered in Lesson 2. This short quiz checks your understanding of remote sensing tools and methods.

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Question 1 of 5

1. Question

What is the primary operational principle that defines Passive Sensors in remote sensing, such as Landsat, MODIS, and Sentinel-2?

A. They require constant ground truthing for every measurement.
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B. They detect reflected sunlight or emitted radiation without emitting their own signal.
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C. They use LiDAR technology to measure the time of light return.
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D. They emit a radio signal and measure the back scatter (e.g., radar).
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Question 2 of 5

2. Question

Match the satellite sensor/series to its defined characteristic or primary use as described in the lesson.

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Landsat's long history and 16-day cycle provide a vital archive for long-term change detection.
Active sensor that emits its own signal (RADAR)
1-2 days Temporal resolution for daily large-scale environmental monitoring.
10 m Spatial Resolution for high-resolution agriculture and urban planning.
Requires an Airplane-based platform for operation
Primarly used for measuring atmostpheric ozone concentration

16 days Temporal Resolution for long-term land-use and deforestation studies.

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ESA's Sentinel-1

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NASA's MODIS

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ESA's Sentinel-2

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Question 3 of 5

3. Question

True or False: Because satellite remote sensing involves objective measurements and covers large areas, it entirely eliminates the need for ground truthing when validating vegetation health maps.

True
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Question 4 of 5

4. Question

The lesson highlighted that remote sensing is extremely versatile. Which two of the following distinct fields are explicitly mentioned as frequent applications? (Please select only two.)

A. Human genetics
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B. Land degradation
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C. Glaciology
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D. Socio-economic surveying
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E. Historical Archives
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Question 5 of 5

5. Question

Let’s apply what we learned about the Burkina Faso study. The research focused on measuring the time lag between the end of the drought (rainfall) and the positive NDVI anomaly (vegetation recovery). Why is measuring this specific lag time so critical? What does it truly help us predict?

A. The cost of future crop insurance payouts.
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B. Vegetation recovery timelines.
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C. The severity of socio-economic drought.
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D. The duration of meteorological drought.
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COINS Agri-Water Hackathon

9. Short Quiz: Remote Sensing-Based Vegetation Mapping

Henryk Hodam

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