Round 1

Round 1 questions are listed below. Round 2 question is posted here.

Question 1: Quantifying Forest Loss

Datasets:

1. Hansen Global Forest Change v1.5 (2000-2017)

2. WDPA: World Database on Protected Areas (polygons)

Use the above 2 datasets to compute the forest loss in the 'Anamalai Tiger Reserve'. Answer following questions based on the analysis. Include a link to the EE script that supports your answers.

What was the total forest loss (in hectares)?
Which year experienced the highest forest loss?

Starter script: https://code.earthengine.google.co.in/fb755aa1a0a49705f48db4dc8c9a2383

Solution: https://code.earthengine.google.co.in/4e62bb7d8d7d148e053c69cf66d04f72

Question 2: Estimating Land Surface Temperature

Datasets:

1. MOD11A2.006 Terra Land Surface Temperature and Emissivity 8-Day Global 1km

Using the MODIS Terra LST product, estimate the min/max daytime and nighttime surface temperature at the given location in the year 2017.

Answer following questions based on your analysis. Include a link to the EE script that supports your answers.

What was the highest daytime land surface temperature?
What was the lowest night land surface temperature?

Starter script: https://code.earthengine.google.co.in/f58afe9463eb94bc010491edcc173b7f

Solution: https://code.earthengine.google.co.in/5ae388489354072465efa0bda0de7f1d

Question 3: Estimating Precipitation

Datasets:

CHIRPS Daily: Climate Hazards Group InfraRed Precipitation with Station Data (version 2.0 final)

Using the CHIRPS Daily dataset, estimate the average cumulative rainfall over the given region in 2018.

Answer following question based on your analysis. Include a link to the EE script that supports your answers.

What is the average cumulative rainfall over the region in 2018?

Starter script: https://code.earthengine.google.co.in/c914d7e87b22483c8f5a3c7b08afc993

Solution: https://code.earthengine.google.co.in/97887dd9461aa0ccc537bad40f35af3a

Question 4: Image Segmentation

Dataset:

Sentinel-2 MSI: MultiSpectral Instrument, Level-1C

Compute Modified Normalized Difference Water Index (MNDWI) from the given image and use Otsu's method of segmentation (https://medium.com/google-earth/otsus-method-for-image-segmentation-f5c48f405e), determine threshold and segment the image.

Answer following questions based on your analysis. Include a link to the EE script that supports your answers.

What is the optimal MNDWI threshold for the given image?

Starter script: https://code.earthengine.google.co.in/82a3d8e7a3a6e3245f3049651d55ec35

Solution: https://code.earthengine.google.co.in/67980c0cea5a027ca632ec3cccb15742

Report abuse