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    Complete Google Earth Engine for Remote Sensing & GIS

    BY
    Udemy

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    Mode

    Online

    Fees

    ₹ 499 2899

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based

    Course and certificate fees

    Fees information
    ₹ 499  ₹2,899
    certificate availability

    Yes

    certificate providing authority

    Udemy

    The syllabus

    Introduction to Google Earth Engine (GEE)

    • What is Google Earth Engine?
    • INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools
    • Scripts For the Course

    Get Started with GEE

    • Explore the Google Earth Engine (GEE) Interface
    • Sign-up for GEE
    • Explore the Datasets in Google Earth Engine (GEE)
    • GEE Explorer for Satellite Data Analysis
    • Code Editor of GEE

    Introduction to the GEE Code Editor

    • Hello to Javascript
    • Read in Display Single-Band Raster Data
    • Read & Visualize Multi-Band Raster Data
    • Start With Image Collections
    • Visualize Vector Data
    • More Feature Data Manipulation
    • Read in Shapefiles
    • Uploading Shapefiles Without Fusion Tables
    • Section 3 Quiz

    Common GIS Operations using Google Earth Engine (GEE)

    • Filter a Feature Collection
    • Create a Buffer Around a Feature Collection
    • Compute Zonal Statistics on Feature Data
    • Filter an Image Collection
    • Filter an Image Collection According to Path and Row
    • Filter and Apply Statistical Function on Each Band
    • Select & Display a Specific Image
    • User Defined ROI
    • Create a Categorical DEM Map
    • Deriving Topographic Products from Elevation Data
    • Section 4 Quiz

    More GIS Operations in GEE

    • Clipping a Raster Using a Feature
    • Band Arithmetic on Raster Data in GEE
    • User Defined Functions
    • More Arithmetic Operations in GEE
    • Threshold Operations on Raster Data
    • Threshold With Canny Edge Detector
    • Resampling a Raster
    • Change Raster Resolution
    • Raster to Vector Conversion
    • Vector to Raster Conversion

    Plotting and Exporting GEE Data

    • Use of Reducer Function
    • Plot Temporal Variation
    • Spectral Signatures Over Time & Space
    • Grouped Means for Two Raster Bands
    • Apply Simple Linear Regression
    • Export Raster Data
    • Export Data in CSV Format
    • Section 6 Quiz

    Working with Optical Data - Landsat

    • Principles Behind Collection of Optical Remote Sensing Data
    • Why Do We Need Pre-Processing of Landsat Data
    • Different Landsat Sensors
    • Apply Atmospheric Correction to Landsat Data
    • Pan Sharpening Landsat Images
    • More Pan-Sharpening
    • Create a Landsat Composite
    • Texture Induces Theory
    • Compute Texture Indices From an Image
    • Spectral Unmixing for Mapping
    • Unsupervised Classification- Theory
    • Unsupervised Classification-K Means Clustering
    • Supervised Classification-Theory

    Common Remote Sensing Applications

    • Read in and Visualize Socio-Economic Data
    • Hansen Forest Loss Data
    • Compute Forest Loss at Country Scale with Hansen
    • Compute Forest Loss at Sub-Country Scale with Hansen
    • Section 8 Quiz

    Miscellaneous Lectures

    • Quick Primer on Spatial Data
    • Github
    • GEE Animations
    • Upload External Data onto GEE

    Instructors

    Ms Minerva Singh

    Ms Minerva Singh
    Data Scientist
    Udemy

    Other Masters, Ph.D, M.Phil.

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