Canny Edge Detector in Google Earth Engine | Detect Edges in Palm Jumeirah

#googleearthengine, #palm_jumeirah, #edge_detection, #canny_edge_detector, #gis, #remotesensing
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Code at the end
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Master Edge Detection with the Canny Edge Detector in Google Earth Engine

Welcome to GIS & RS Made Easy, your ultimate channel for learning GIS and remote sensing techniques! In this tutorial, we’ll introduce you to the Canny Edge Detector in Google Earth Engine, a powerful method used to detect edges within satellite imagery. We’ll demonstrate how to apply the Canny Edge Detection algorithm to detect the edges of the Palm Jumeirah, one of the most iconic man-made islands in the world.

What You’ll Learn in This Video
1️⃣ Introduction to the Canny Edge Detection

Understand the Canny Edge Detection algorithm and how it is used to detect sharp edges in raster images.
Learn how edge detection can help identify boundaries in satellite imagery.
2️⃣ Setting Up Google Earth Engine

A quick guide on how to set up and access Google Earth Engine (GEE), and how to import satellite images for analysis.
3️⃣ Detecting Edges in Palm Jumeirah

Step-by-step instructions on how to apply the Canny Edge Detector to detect the distinct edges of Palm Jumeirah.
Explore the parameters that control edge detection sensitivity and how to fine-tune them for better results.
4️⃣ Visualizing the Results

Learn how to visualize and interpret the edges detected in the image.
Enhance the output by styling the results to highlight the significant features, such as the outline of the Palm Jumeirah.
5️⃣ Applications of Edge Detection in GIS

Urban Planning: Detect building structures, roads, and other man-made features.
Land Use Analysis: Identify boundaries and assess land development over time.
Environmental Studies: Detect natural features and boundaries for further analysis.
Why Use the Canny Edge Detector in Google Earth Engine?
✅ Accurate Edge Detection: Detects sharp transitions in image intensity, making it ideal for identifying natural and man-made features.
✅ Quick and Efficient: Perform edge detection on large satellite images with Google Earth Engine’s powerful cloud-based platform.
✅ Fine-Tuneable Parameters: Adjust the sensitivity of edge detection to get the most accurate results based on your study area.
✅ Visualize and Analyze: Use the results to analyze urban development, land use, or natural features with clear edge delineation.

Who Is This Video For?
📍 GIS Enthusiasts and Professionals interested in edge detection and image processing techniques.
📍 Urban Planners looking to analyze urban features and land boundaries.
📍 Remote Sensing Students and Researchers needing to perform edge detection on satellite imagery.
📍 Developers and Analysts who want to leverage Google Earth Engine for spatial analysis.

Keywords
Canny Edge Detector, Google Earth Engine, Edge Detection, Palm Jumeirah, GIS Analysis, Remote Sensing, Image Processing, Satellite Imagery, Urban Planning GIS, GIS & RS Made Easy

Search Terms
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🚀 Start Detecting Edges in Satellite Imagery Today!
By the end of this tutorial, you’ll have a solid understanding of how to use the Canny Edge Detector in Google Earth Engine to detect sharp boundaries and edges in satellite images like those of Palm Jumeirah.

📢 Subscribe to GIS & RS Made Easy
For more tutorials on GIS tools and remote sensing techniques, subscribe to our channel and join the community. Let us know in the comments how you plan to use edge detection in your own projects!

👉 Let’s make GIS tools easy and accessible for everyone!

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Code
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var geometry =
/* color: #0b4a8b */
/* shown: false */
ee.Geometry.Polygon(
[[[55.089398991078, 25.11406816116389],
[55.13986743590222, 25.090129089386224],
[55.17454303404675, 25.131941683802594],
[55.12836612364636, 25.147637142323088]]]);
// Load sentinel image
var image = ee.ImageCollection("COPERNICUS/S2_SR_HARMONIZED")
.filterBounds(geometry)
.filterDate('2023-01-01','2023-12-31')
.median()
.clip(geometry);
//Compute NDVI

// Detect edges
var canny = ee.Algorithms.CannyEdgeDetector(ndvi, 0.5);

// Mask the image with itself to get rid of areas with no edges.