Satellite Image classification Random Forest Machine Leaning (ML) in Google Earth Engine, part: 1

7 days of online training on Master Google Earth Engine for Remote Sensing & GIS analysis for beginners to advanced course contents: • New batch: Class Start...
Registration is open for a new batch of 7 days of Complete Google Earth Engine for Remote Sensing & GIS Analysis online training for Beginners to Advanced levels.
These classes will teach you all the necessary things to start using GEE for your remote sensing analysis. We mainly focus on these people who don't know any programming language and Earth Engine function. We cover LULC mapping, Air quality, Monitoring, Time series analysis, Calculating any Indices, Supervised Classification, Machine Learning Methods, and more.
Class Start: 19th April, 2024
Admission Last Date:18th April, 2024 ( 1st 10 registered people get a 50% discount)
Total Class: 7 days (Friday and Saturday in Week)
Class Duration: 3 hours (Each day), Time: 9:00 P.M to 12:00 A.M (GMT +6)
For registration contact this WhatsApp number: [phone] or Email: [e-mail]
1st day:
Introduction to GES
How to use GEE JavaScript and Python API
Learn the basic principles of JavaScript syntax and python
Client vs. Server object on GEE
How you get the server to execute your code?
Importing Raster and Vector Data: Local storage & GEE Dataset
Filtering Attribute Table
2nd day:
Filtering and Displaying Satellite Images: Landsat , Sentinel
Satellite Composite
Band combinations
Export Satellite Imagery: Landsat , Sentinel and Modis
Import, Filter, Reduce, Clip and display Raster data in GEE
Time series Chart of NDVI using GEE readymade dataset
Export Any Shapefile
3rd day:
Calculating Any Indices from Satellite Images using Landsat and Sentinel
Filtering and Displaying Satellite Images: Sentinel-2 and Monitoring NDWI , NDVI
Extract water body using Thresholding
NDVI , NDWI , SAVI and all indices Time series Chart using Landsat and Sentinel
Export Any Shapefile from GEE
How to add Gradient Legend and Title on GEE
NDWI Calculated from Modis and Landsat data
4th day:
How to remove cloud and Haze from satellite imagery- Landsat and Sentinel
Visualization (DEM) of Hill shade and Slope Map in GEE using NASA SRTM and Aster
Land surface temperature (LST) Monitoring from Landsat satellite imagery and Modis
How to calculated Average , Maximum, Minimum NDVI any specific region
GEE: How to make monthly Evapotranspiration
5th day:
Air Quality Monitoring: all parameters
How to Download Air Quality Parameters Time series data in CSV format using GEE
Air Quality Monitoring Time Series chart
Air Quality Monitoring: How to calculate total emission of nitrogen-oxide or any gases in GEE using sentinel-5
ArcMap software: How to make research paper map using GEE & ArcMap software
6th day:
Introduction to Machine Learning in Google Earth Engine
How to make LULC Map using Machine Learning: Supervised and Unsupervised algorithm
Random forest, CART, SVM, Minimum distance classifier to make LULC
How to Check LULC accuracy assessment using Google Earth Engine. (Kappa, Producers & Consumers
accuracy)
Calculate LULC classes Area
How to add Legend in LULC Map
How to Export LULC and make a research paper LULC map using ArcMap
7th day:
Land-Use and Land-Cover Change Detection using Google Earth Engine
NDVI change detection using Google Earth Engine
Class-wise LULC change detection in ONE layer using Google Earth Engine
Hyperparameter Tuning for improving the accuracy of your machine-learning model
Online Training Benefits:
Course Certificate (After submitting all Assignments)
Materials (Slide, PDF)
Practice Code (All codes provide)
Recorded Class (All class recorded video provided)
Lifetime teaching support
Join Our Community:
Join the Telegram group: t.me/gisandrem...
How to Calculate Erosion & Accretion of a River for different time period using ArcGIS - part: 1: www.youtube.co...
ML full palylist: • Machine Learning
🛑 How to download satellite imagery and use it for LULC with Machine Learning using Python full playlist: • LULC Python Machine le...
Google Earth Engine: 15 days Advanced online training syllabus: • Registration is open f...
Online training on the R package for interacting with the Google Earth Engine syllabus: • rgee: An R package for...

[@gisrsinstitute]

Bit 3 and 4

[@butthussain5881]

Thank you sir

[@butthussain5881]

First of all Thank you so much sir for nice explaination in the early videos on cloud masking, but dear sir, i have a query regarding cloud and cloud shadow bit masking, is it 5,3 or have to choose 3and 4 as bits as shown in properties because 5 is showing snow there, so plz kindly correct me here?

[@gisrsinstitute]

Bit 3 and 4

[@nurahmedalmuktadir3136]

could u please upload part 2

[@connor505050]

seconded