Скачать с ютуб Satellite Data Analysis and Machine Learning Classification with QGIS Part 1 | AI FOR GOOD WEBINARS в хорошем качестве

Satellite Data Analysis and Machine Learning Classification with QGIS Part 1 | AI FOR GOOD WEBINARS

The workshop involves two QGIS plugins: Semi-automatic Classification Plugin (SCP) and dzetsaka. SCP is used for majority of preprocessing operations such as retrieval of the Sentinel 2 imagery for an area of interest, DOS (Dark object subtraction) atmospheric correction, selection of specific bands for classification, creation of composite and computation of band algebra (i.e., Normalized Difference Vegetation Index (NDVI). The dzetsaka plugin is used to detect and classify built-up areas starting from preprocessed satellite imagery with Gaussian Mixture Model, Random Forest and K-Nearest Neighbors machine learning algorithms. Shownotes: 00:00 Introduction 09:00 Requirements to follow the workshop 10:00 QGIS Introduction 14:00 QGIS plugins 18:00 Practical - Installing plugins 23:00 Satellite Imagery 27:00 Load Auxiliary Vector Data 34:00 Practical - Application of vector 38:00 Start Using SCP plugin 42:00 SCP plugin - Image download 1:00:00 Practical - Set up data provider and download data. 1:23:00 Load previously downloaded image 1:26:00 SCP plugin - Image Preprocessing 1:29:00 Practical - Load previously download images and preprocess 1:43:00 SCP plugin - Band set 1:50:00 QGIS core - Clip raster/image 1:57:00 Practical - Create virtual raster of band set and clip it to the working area 2:08:00 SCP plugin - Band algebra 2:12:00 Acknowledgements from Prof. Maria Brovelli to assistants Website: https://aiforgood.itu.int Twitter:   / itu_aiforgood   LinkedIn Page:   / 26511907   LinkedIn Group:   / 8567748   Instagram:   / aiforgood   Facebook:   / aiforgood