Your First Earth Engine Script

Learn to write your first Google Earth Engine script step by step.

What You’ll Learn

Basic Earth Engine initialization
Loading your first image
Displaying image information
Understanding Earth Engine objects
Simple operations and calculations

Prerequisites

Authenticated Earth Engine account
Python environment with Earth Engine API
Basic Python programming knowledge

Step 1: Initialize Earth Engine

Every Earth Engine script starts with initialization:

import ee

# Initialize Earth Engine
ee.Initialize(project='your-project-id')

print("Earth Engine initialized successfully!")

What’s happening here?

Import the Earth Engine Python API
Initialize connection to Google’s servers
Authenticate your access to the platform

Step 2: Load Your First Image

Let’s load a satellite image:

# Load a Landsat 8 image
image = ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_044034_20140318')

print("Image loaded:", image)

Understanding the image ID:

LANDSAT/LC08/C02/T1_L2 - Dataset collection
LC08_044034_20140318 - Specific image identifier
Contains path, row, and date information

Step 3: Explore Image Properties

Get information about your image:

# Get image information
image_info = image.getInfo()

print("Image type:", image_info['type'])
print("Image ID:", image_info['id'])
print("Number of bands:", len(image_info['bands']))

Common image properties:

# Get specific properties
print("Acquisition date:", image.get('DATE_ACQUIRED').getInfo())
print("Cloud cover:", image.get('CLOUD_COVER').getInfo())
print("Sun elevation:", image.get('SUN_ELEVATION').getInfo())

Step 4: Work with Image Bands

Explore the spectral bands:

# Get band names
band_names = image.bandNames()
print("Available bands:", band_names.getInfo())

# Select specific bands
rgb_bands = image.select(['SR_B4', 'SR_B3', 'SR_B2'])
nir_band = image.select('SR_B5')

print("RGB bands selected")
print("Near-infrared band selected")

Step 5: Simple Calculations

Perform basic mathematical operations:

# Calculate NDVI (vegetation index)
ndvi = image.normalizedDifference(['SR_B5', 'SR_B4'])
ndvi = ndvi.rename('NDVI')

print("NDVI calculated")

# Get NDVI statistics
geometry = ee.Geometry.Point([-122.4, 37.8])  # San Francisco

ndvi_stats = ndvi.reduceRegion(
    reducer=ee.Reducer.mean(),
    geometry=geometry.buffer(1000),  # 1km buffer
    scale=30
)

print("Average NDVI:", ndvi_stats.getInfo())

Complete First Script

Here’s your complete first Earth Engine script:

"""
My First Earth Engine Script
============================

This script demonstrates basic Earth Engine operations:
- Initialize Earth Engine
- Load a satellite image
- Explore image properties
- Calculate a vegetation index
- Extract statistics
"""

import ee

def main():
    # Step 1: Initialize Earth Engine
    try:
        ee.Initialize(project='your-project-id')
        print("✓ Earth Engine initialized successfully!")
    except Exception as e:
        print(f"✗ Initialization failed: {e}")
        return

    # Step 2: Load image
    image = ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_044034_20140318')
    print("✓ Image loaded")

    # Step 3: Get image information
    print(f"✓ Image date: {image.get('DATE_ACQUIRED').getInfo()}")
    print(f"✓ Cloud cover: {image.get('CLOUD_COVER').getInfo()}%")

    # Step 4: Calculate NDVI
    ndvi = image.normalizedDifference(['SR_B5', 'SR_B4']).rename('NDVI')
    print("✓ NDVI calculated")

    # Step 5: Get statistics
    point = ee.Geometry.Point([-122.4, 37.8])
    stats = ndvi.reduceRegion(
        reducer=ee.Reducer.mean(),
        geometry=point.buffer(1000),
        scale=30
    )

    print(f"✓ Average NDVI: {stats.getInfo()['NDVI']:.3f}")
    print("🎉 First script completed successfully!")

if __name__ == "__main__":
    main()

Understanding the Results

NDVI Values: * -1 to 0: Water, bare soil, rock * 0 to 0.3: Sparse vegetation, urban areas * 0.3 to 0.7: Moderate to dense vegetation * 0.7 to 1: Very dense vegetation

Next Steps: * Try different images and locations * Experiment with other spectral indices * Learn about image collections * Explore visualization options

Common Issues and Solutions

Authentication Error

Error: Please authorize access to your Earth Engine account

Solution: Run ee.Authenticate() first

Project Not Found

Error: Project not found or not registered

Solution: Check your project ID and ensure it’s registered with Earth Engine

Network Timeout

Error: Connection timeout

Solution: Check internet connection and try again

What You’ve Learned

✅ Earth Engine Basics * How to initialize Earth Engine * Loading and exploring satellite images * Understanding image properties and metadata

✅ Core Concepts * Earth Engine objects (Image, Geometry) * Server-side vs client-side operations * Getting information with .getInfo()

✅ Simple Analysis * Calculating spectral indices * Extracting regional statistics * Basic mathematical operations

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