CERTIFICATE OF COMPLETION – FANTASHA FARIA

This is to certify that Fantasha Faria successfully completed the hands-on virtual workshop on GIS & Remote Sensing Using Google Earth Engine.

Taught by: Sadhan Verma, CEO and Data Science Instructor at NBICT LAB’s e-Learning Platform.
Course Content Duration: 36 Hours.
Learner’s Email Address: fariahassan125@gmail.com
Codes He/she learned: https://code.earthengine.google.com/?accept_repo=users/sadhanhstu/NBICT_LAB

Course Contents He/she Completed:

1. Introduction to GIS
   1. What is GIS?
   2. What does GIS do?
   3. How is GIS used?
2. Introduction to Remote Sensing
   1. What is remote sensing?
   2. Types of remote sensing
   3. What is remote sensing used for?
3. Introduction to Google Earth Engine (GEE)
   1. What is Google Earth Engine?
   2. How to create an account in Google Earth Engine
   3. How to create a new project in GEE
4. JavaScript Basics in GEE (Part-1)
   1. Write your first JavaScript statement
   2. How to write a comment in JS
   3. Shortcut to run a script
   4. Shortcut to write a comment
   5. Variables in JS
   6. Lists in JS
   7. Dictionaries in JS
   8. Writing a JS statement in multiple lines
   9. Saving the codes
5. JavaScript Basics in GEE (Part-2)
   1. Functions in JavaScript
   2. What is a function?
   3. How do you write a function?
   4. How to get the link to a code snapshot
   5. How to find a dataset
   6. How to find a code snippet
   7. How to use the Inspect tab
   8. How to center a map in the area of interest
6. Filtering Image Collections
   1. How to import a dataset using the GEE’s search box
   2. Changing an imported variable name
   3. Date Filters: Collecting images in a year of interest
   4. Location Filters: Finding images collected over a region of interest
   5. Metadata Filter: Finding images with less cloud cover
   6. Applying all the filters in a single line
7. Visualizing the Filtered Images on the Map
   1. How to visualize the filtered images on the map
   2. Working with the visualization parameters
   3. Configuring the settings in the code
8. Selecting Administrative Regions
   1. Adding the polygon layer all over the world
   2. Selecting a country
   3. Selecting a state/Division
   4. Selecting a county/District
   5. Selecting multiple regions
   6. Adding a color to the selected regions
   7. Giving a name to the selected regions
9. Importing Data
   1. Obtaining a shapefile from an official source
   2. Downloading the required shapefile
   3. Uploading the required shapefile in GEE
   4. Investigating the Tasks Tab
   5. Investigating the uploads from the Assets Tab
   6. Importing an asset into the script
   7. Adding the urban layer to the map
   8. Selecting a target city for feature collection
   9. Selecting features on specific conditions
10. Clipping Images
    1. Importing the Sentinel-2 dataset
    2. Importing the Global Human Settlement Urban Centers dataset
    3. Filtering a specific urban area
    4. Setting the geometry of the selected urban area
    5. Filtering the Sentinel-2 images for the selected urban area
    6. Setting the visParams to the filtered area
    7. Clipping the filtered images for the selected urban area
11. Exporting Data
    1. Selecting the bands we want to export
    2. How to autocomplete the functions
    3. Exporting an image to the drive using the GeoTIFF format
12. Earth Engine Objects (Part-1)
    1. Creating a list for a sequence of numbers
    2. Manipulating the items of the list using Earth Engine Objects
    3. Working with dates
13. Earth Engine Objects (Part-2)
    1. Working with dates
    2. Computing the date 5 weeks from ‘date’
    3. Computing the date 6 months before the ‘startDate’
    4. Printing the current date
    5. Filtering the images of a selected location for the last month
    6. Visualizing the filtered images
14. NDVI Calculation
    1. What is NDVI?
    2. Importing the datasets
    3. Filtering the target location/geometry
    4. Filtering the Sentinel-2 dataset
    5. Calculating the NDVI
15. MNDWI and SAVI Calculation
    1. What is MNDWI?
    2. Calculating the MNDWI
    3. What is SAVI?
    4. Calculating SAVI
16. NDBI Calculation
    1. What is NDBI?
    2. Calculating the NDBI
17. Computation on ImageCollections
    1. Importing the data
    2. Selecting an admin1 region
    3. Writing a function that computes NDVI for an image and adds it as a band
    4. Visualizing the images using a nice NDVI Palette (colorbrewer2.org)
18. Computation on ImageCollections (Part-2)
    1. Importing the data
    2. Selecting an admin1 region
    3. Building a function that calculates both the NDVI and the NDWI indices
    4. Returning an image with 2 new bands added to the original image
    5. Mapping the function over the collection
    6. Displaying a map of NDWI for the region
    7. Select the ‘ndwi’ band and clip it before displaying
    8. Using a color palette from colorbrewer2.org
19. Cloud Masking (Part-1)
    1. Why is cloud masking essential?
    2. Sorting the image collection
    3. Picking the most cloudy image
    4. Collecting a function for cloud masking
    5. Visualizing the cloud masking layer
20. Cloud Masking (Part-2)
    1. Making the environment ready (Instructor’s repository)
    2. Why is cloud masking essential?
    3. Cloud masking using Cloud Score+ S2_HARMONIZED V1
    4. Collecting a function for cloud masking
    5. Visualizing the latest cloud masking layer
21. Reducers in GEE (Part-1)
    1. Computing statistics on a list
    2. Using a reducer to compute average values
    3. Applying a reducer on an image collection
    4. Calculating the mean of the bands of a selected geometry
22. Reducers in GEE (Part-2)
    1. Calculating the mean of a particular band using the reducer
23. Time Series Charts in GEE (Part-1)
    1. Selecting and importing the geometry
    2. Importing the Sentinel-2 images
    3. Applying date and bound filters
    4. Applying cloud masking
    5. Calculating NDVI
24. Time Series Charts in GEE (Part-2)
    1. Creating an NDVI chart
    2. Improving the chart
    3. Exporting the chart
25. Unsupervised Classification – Clustering (Part-1)
    1. Making the environment ready
    2. Selecting the region of interest
    3. Loading Sentinel images
    4. Filtering the images
    5. Clipping the images
    6. Displaying the image collection
26. Unsupervised Classification – Clustering (Part-2)
    1. Making the environment ready (Download Codes)
    2. Adjusting the zoom level of the clipped image
    3. Creating the training dataset
    4. Instantiate the clusterer and train it
    5. Clustering the input using the trained clusterer
    6. Displaying the clusters with random colors
27. Land Cover Classification – Random Forest (Part-1)
    1. Understanding supervised classification
    2. Feature collection from a roi to train the data
    3. Implementing the code in an ROI
28. Land Cover Classification – Random Forest (Part-2)
    1. Exploring USGS Landsat 9 Level 2, Collection 2, Tier 1
    2. Breaking down the codes
    3. Explanation of the scaling factors
    4. Visualizing the Landsat image on the map
29. Land Cover Classification – Random Forest (Part-3)
    1. Preparing training data for a supervised classification
    2. Merging multiple feature collections into a single collection
    3. Selecting the relevant spectral bands
    4. Extracting the pixel values for the selected bands
    5. Splitting the dataset into the training set and the test set
    6. Performing the land cover classification using a random forest classifier
30. LST DOY Time Series Plot
    1. Selecting the geometry
    2. Importing the LST data
    3. Scaling the data
    4. Displaying LST annual variation