Google Earth Engine

What is Google Earth Engine?

Google Earth Engine (GEE) is a powerful web-platform for cloud-based processing of remote sensing data on large scales. It brings together the world’s satellite imagery — trillions of scientific measurements dating back almost 40 years — and makes it available online with tools for scientists, independent researchers, and nations to mine this massive warehouse of data to detect changes, map trends and quantify differences on the Earth’s surface. Applications include: detecting deforestation, classifying land cover, estimating forest biomass and carbon, and mapping the world’s roadless areas. The advantage lies in its remarkable computation speed, as processing is outsourced to Google servers. The platform provides a variety of constantly updated data sets, so no download of raw imagery is required. One of GEE’s tools, the Earth Engine Code Editor, is a web-based integrated development environment which facilitates developing complex geospatial workflows.

Gorelick et al. (2017) write in the 2017 Remote Sensing of the Environment article:

Google Earth Engine is a cloud-based platform for planetary-scale geospatial analysis that brings Google’s massive computational capabilities to bear on a variety of high-impact societal issues including deforestation, drought, disaster, disease, food security, water management, climate monitoring and environmental protection.

Gorelick et al. (2017)

Let’s Begin with GEE Tutorials:

Beginner

  1. What is Google Earth Engine?
  2. Getting Started with GEE.
  3. Uploading Shapefiles/Geotiffs in Assets.
  4. Generate Histogram in Google Earth Engine.
  5. Add Title and Legends
  6. Add Two Charts
  7. Add Grid Lines to your map- (Study Area: Canada)
  8. Create a Chart to show Landsat 8 TOA Spectra at three points near Mumbai City

Intermediate

  1. Write a code to Download 30m DEM for any country.
  2. Calculate Annual Time Series NDVI – (Study Area: Nigeria)
  3. Develop a Harmonic Model: Original vs Fitted NDVI values
  4. Using Landsat Images to calculate NDVI – (Study Area: India)
  5. Using 2001 MODIS Land Cover Type Yearly Global 500m Data to Determine the Land-Cover Analysis (Study Area: Mexico)

Advanced

  1. Share your work via Earth Engine App
  2. Calculating and Exporting Annual 90th Percentile NDVI for years 1985-2019 – (Study Area: Turkey)
  3. Land Cover Mapping – (Study Area: Dubai)
  4. Determining the Land Cover Change between 1999 and 2018- (Study Area: Mumbai)

Time-lapse / Animation

  1. Animate 30m Landsat images generated 90th percentile Annual NDVI from 1999 to 2018 (Study Area: South America)
  2. Animate the NDVI derived from MODIS 16-Day Global 250-m through the year using Google Earth Engine.

Land Use and Land Cover Mapping

  1. Land Cover Mapping – (Study Area: Dubai)
  2. Determining the Land Cover Change between 1999 and 2018- (Study Area: Mumbai)

Others

  1. Determine the long-term changes in the Ganga River Basin, India
  2. High Resolution Long-Term Mapping of Koshi Basin, Nepal.
  3. Night Light Maps – (Study Area: South Asia)
  4. Determining Forest Cover using Hansen Global Forest Change Data- (Study Area: Malaysia)

 Some useful Google Earth Engine tutorials can be found here:


Some useful guides for Google Earth engine can be found here:

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