How to Create 3D Maps using QGIS скачать в хорошем качестве

How to Create 3D Maps using QGIS

A tutorial about how to create 3D Maps using QGIS? Join our upcoming online live training program starting on 21st February, 2026, where you will gain hands-on experience in using cloud-based geospatial processing with Google Earth Engine, seamlessly connected with desktop GIS platforms. Registration is now open for the 38th Batch of 7-days comprehensive online live training on Google Earth Engine (GEE) for Remote Sensing and GIS Analysis using JavaScript and Python APIs integration with QGIS and ArcGIS pro, 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: 21st February, 2026 Admission Deadline: 20th February, 2026 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: https://www.studyhacksgeospatial.com/... For Registration, Contact this Email: rmijanur10266@gmail.com Or WhatsApp 24/7: +8801780942798 #QGIS #terrain #maps #mapping #geospatial #geospatialdata #googleearthengine #GeoAI