Google App Engine Python Training Day 2

Aug 13, 2024

Google App Engine Python Program - Day 2 Notes

Overview

  • Course focused on learning Google App Engine platform using the Python API.
  • This is the second day of the online training program.

Key Topics Covered

1. Importing Shape Files

  • How to import shape files in Google App Engine using Python API.
  • Two types of shape files to use:
    • Google App Engine datasets (e.g., international boundaries).
    • Local storage shape files created on your computer.
    • Required file extensions: .shp, .shx, .prj, .dbf.

2. Creating NDVI Map

  • Introduction to the Normalized Difference Vegetation Index (NDVI).
  • Steps to create NDVI maps using Google App Engine:
    1. Import Shape File: Use shape files for specific regions.
    2. Install Necessary Packages:
      • Install geemap package using pip install geemap.
      • Import ee (Earth Engine package) which is pre-installed.
    3. Authenticate: Generate and use verification code to authenticate the account.

3. Using MODIS Data for NDVI

  • How to use MODIS data to create NDVI maps.
  • Find MODIS NDVI datasets in Google Earth Engine catalog:
    • Example dataset: 16-day 250 m resolution NDVI data.

4. Filtering Data

  • Filtering dataset for specific conditions (e.g., year 2021).
  • Use functions like filterDate and select to work with datasets.

5. Statistical Analysis

  • Using the reduce function to calculate average NDVI.
  • Clipping the NDVI map to show results for specific regions.

6. Visualization

  • Adding visualization parameters to make NDVI maps interpretable.
  • Example of visualizing NDVI results on a map.

7. Working with Different Countries

  • Ability to filter datasets by country names (e.g., Bangladesh, India, Pakistan).
  • Accessing country boundary shape files using table IDs.

8. Uploading Custom Shape Files

  • Steps to upload custom shape files to Google App Engine.
  • Create shape files using software like ArcMap and uploading required files.

9. Discussion on Future Classes

  • Upcoming lessons on Landsat and Sentinel imagery for NDVI creation.
  • Introduction to vegetation health index (VHI) and other remote sensing analyses.

Conclusion

  • Questions and doubts were invited from students.
  • Emphasis on understanding the processes and methodology for remote sensing analysis using Google App Engine.