Youtor
Supervised Image Classification of Sentinel2A Imagery in Google Earth Engine Part 1
>> YOUR LINK HERE: ___ http://youtube.com/watch?v=Uk5ViI7eB7U
In this tutorial, we will learn how to perform supervised image classification of Sentinel-2 imagery using Google Earth Engine. Sentinel-2 is a satellite mission from the European Space Agency that provides high-resolution optical images of the Earth's surface, which can be used for various applications such as land cover mapping, vegetation monitoring, and urban planning. • ------------------------------------------------------------------------------------ • Supervised image classification is a machine learning technique that allows us to automatically classify pixels in an image into different land cover classes based on training data. In this tutorial, we will use a random forest classifier to classify Sentinel-2 imagery into four land cover classes: water, urban, vegetation, and barren. • ----------------------------------------------------------------------------------- • Link to downloading code: https://drive.google.com/file/d/1sDVt... • ----------------------------------------------------------------------------------- • Supervised Image Classification of Sentinel-2A Imagery in GEE - Part 1 Video Link: • • Supervised Image Classification of Se... • Supervised Image Classification of Sentinel-2A Imagery in GEE - Part 2 Video Link: • • Supervised Image Classification of Se... • ---------------------------------------------------------------------------------- • Join this channel to get access to perks: • / @terraspatial • #sentinel2 #googleearthengine #remotesensing #imageclassification #supervisedlearning #machinelearning #LandCoverMapping #VegetationMonitoring #UrbanPlanning #RandomForestClassifier #JavaScriptAPI #StepByStepTutorial #DataPreprocessing #TrainingSamples #FeatureCollection #Tutorial #ESA #EuropeanSpaceAgency #OpenData #EarthObservation #DataScience #GIS #Geospatial #dataanalysis #LULC #supervisedclassification
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