Homework: Remote Sensing for Monitoring Land Degradation and Sustainable Cities SDGs
This homework includes questions from the lectures and exercises from all sessions of this webinar. Some questions refer to portions of the exercise that can be best answered as you are completing the steps. Thus, it may be best to record your answers on a sheet of paper or elsewhere before submitting them here. You will not be able to save you answers and come back to complete this form at a later time.

To receive a certificate of completion, you must have attended both live sessions and complete this homework by August 6, 2019. Once you submit the homework, you will receive an email with a copy of your responses.

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Session 1 Lecture Questions
1. The Sustainable Development Goals (SDGs) hope to balance which dimensions of sustainable development? *
2. What is the SDG Target 15.3? *
3. What three sub-indicators are used for SDG Indicator 15.3.1? *
Session 1 Exercise Questions
Please refer to the Trends.Earth "Compute Sub-Indicators" exercise to answer the following questions.
4. What country did you select to run your analysis? *
5. What are the default years in the toolbox for countries to report their baseline on SDG 15.3.1 Land Degradation? *
6. What productivity layer did you select? *
7. Trends.Earth can be run at which geographic level? *
Session 2 Lecture Questions
8. Name two limitations to using global datasets for land cover mapping. *
9. Name two benefits of using local datasets for land cover mapping. *
10. Describe any local data you might have or data you would like to acquire for land cover mapping. *
Session 2 Exercise Questions
Please refer to the Trends.Earth "Using Custom Land Cover Data" exercise to answer the following questions.
11. How many land cover classes were in the custom land cover dataset from Uganda (not including no data classes)? *
12. What are the limitations of using global datasets? *
13. How do users of Trends.Earth benefit from uploading custom datasets for analysis? *
14. What are the issues with using custom data? *
15. Describe what your final indicator map looks like using custom data. Does anything look different than you expected? *
Session 3 Lecture Questions
16. What is the SDG Target 11.3? *
17. What datasets are needed for reporting SDG Indicator 11.3.1? *
18. Which datasets were used to create the time series of impervious surface area for the Trends.Earth SDG 11.3.1. tool? *
Session 3 Exercise Questions
After you have completed the "Urban Change SDG 11.3.1"  exercise, navigate to an urban area of your choice. Test different parameters until you find an ideal fit for your city.  The following questions refer to your own area of interest.
19. What was your urban area of interest (please be descriptive, city name and country or provide latitude/longitude if it is a smaller urban area). *
20. What were the best parameters for your urban area of interest? Please indicate the values for: (1) impervious surface index, (2) nighttime lights, and (3) water frequency. *
21. What was the trend in urban and land consumption rates for your area of interest? Please indicate (1) increasing, (2) decreasing, or (3) stable/no change *
22. How do you interpret the results? Were you surprised with the extent or trend in change of urban consumption over time? *
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