📢 Registration is now open for the 35th Batch of 7-day comprehensive online live training on Google Earth Engine (GEE) for Remote Sensing and GIS Analysis using JavaScript and Python APIs, tailored for beginners to advanced learners. Designed specifically for non-coders, this course empowers you with advanced geospatial skills—no prior programming knowledge is required! 📡🛰️
These classes will teach you all the necessary things to start using GEE for your remote sensing analysis. We primarily focus on individuals who are unfamiliar with programming languages and the Earth Engine function. We cover LULC mapping, Change detection Analysis, Air quality Monitoring, Time series analysis, calculating any Indices, Supervised Classification, Unsupervised Classification, Machine Learning Methods, NDVI change detection, and more.
📅 Class Start: 14th November 2025 ⏳ Admission Deadline: 13th November 2025 🎉 Special Offer: First 10 registrants get 50% off – Book your seat now!
Class Schedule: Duration: 7 days (Fridays & Saturdays in a week) Time: 9:00 PM – 1:00 AM (GMT +6) Language: English
Online Training Benefits Ø * Course Certificate (After submitting all Assignments) Ø * Materials (Slide, PDF) Ø * Practice Code (All codes provide) Ø * Recorded Class (All classes recorded video provided) Ø * Lifetime teaching support
🚀 What Will You Be Able to Do After Completing the Training 1) Perform advanced remote sensing analysis using Landsat, Sentinel, and MODIS datasets. 2) Build NDVI, NDWI, SAVI, and other vegetation index time series and perform change detection. 3) Monitor floods, air pollution, LST, evapotranspiration, and more with Google Earth Engine. 4) Create and export custom maps, charts, and geospatial reports for academic and real-world projects. 5) Apply Machine Learning algorithms (Random Forest, SVM, CART) for LULC classification and accuracy assessment. 6) Combine GEE outputs with GIS software (like ArcMap) for creating publishable research maps. 7) Download and visualize air quality data, LULC changes, and NDVI trends in CSV, KML, and other formats. 8 ) Confidently conduct end-to-end geospatial research and project work—even with zero prior coding experience!
Study Hacks-Institute of GIS & Remote Sensing
Tutorial about Estimating Land Surface Temperature, Urban Heat Island using Landsat | Google Earth Engine Tutorial
Tutorial link: youtube.com/live/xfznFz3CJmY?si=5u4KdFxT5E-ewYo_
📢 Registration is now open for the 35th Batch of 7-day comprehensive online live training on Google Earth Engine (GEE) for Remote Sensing and GIS Analysis using JavaScript and Python APIs, tailored for beginners to advanced learners. Designed specifically for non-coders, this course empowers you with advanced geospatial skills—no prior programming knowledge is required! 📡🛰️
These classes will teach you all the necessary things to start using GEE for your remote sensing analysis. We primarily focus on individuals who are unfamiliar with programming languages and the Earth Engine function. We cover LULC mapping, Change detection Analysis, Air quality Monitoring, Time series analysis, calculating any Indices, Supervised Classification, Unsupervised Classification, Machine Learning Methods, NDVI change detection, and more.
📅 Class Start: 14th November 2025
⏳ Admission Deadline: 13th November 2025
🎉 Special Offer: First 10 registrants get 50% off – Book your seat now!
Class Schedule:
Duration: 7 days (Fridays & Saturdays in a week)
Time: 9:00 PM – 1:00 AM (GMT +6)
Language: English
Online Training Benefits
Ø * Course Certificate (After submitting all Assignments)
Ø * Materials (Slide, PDF)
Ø * Practice Code (All codes provide)
Ø * Recorded Class (All classes recorded video provided)
Ø * Lifetime teaching support
🚀 What Will You Be Able to Do After Completing the Training
1) Perform advanced remote sensing analysis using Landsat, Sentinel, and MODIS datasets.
2) Build NDVI, NDWI, SAVI, and other vegetation index time series and perform change detection.
3) Monitor floods, air pollution, LST, evapotranspiration, and more with Google Earth Engine.
4) Create and export custom maps, charts, and geospatial reports for academic and real-world projects.
5) Apply Machine Learning algorithms (Random Forest, SVM, CART) for LULC classification and accuracy assessment.
6) Combine GEE outputs with GIS software (like ArcMap) for creating publishable research maps.
7) Download and visualize air quality data, LULC changes, and NDVI trends in CSV, KML, and other formats.
8 ) Confidently conduct end-to-end geospatial research and project work—even with zero prior coding experience!
For more information about registration, visit our website: www.studyhacksgeospatial.com/google-earth-engine/
For Registration, Contact this Email: rmijanur10266@gmail.com
Or WhatsApp 24/7: +8801780942798 or wa.me/8801780942798
🔗 Stay Connected
🔹 Telegram Group: t.me/gisandremotesenginglearningGEE
🔹 YouTube Channel: youtube.com/@gisrsinstitute
🔹 Instagram: www.instagram.com/geospatial_analysis_learning/
🔹 Twitter: x.com/GISRSStudyHacks
🔹 Facebook Page: www.facebook.com/gisrsinstitute/
#LandSurfaceTemperature #UrbanHeatIsland #Landsat #GoogleEarthEngine #RemoteSensing #ClimateChange #EnvironmentalScience #DataAnalysis #GeospatialAnalysis #SustainableCities
2 weeks ago | [YT] | 13