In this webinar, we will address the challenge of land use and land cover classification using remote sensing satellite images.
Based on Sentinel-2 satellite images provided within the scope of the Earth observation program Copernicus, Damian will share his experience with using state-of-the-art Convolutional Neural Network (CNNs) on different spectral bands. He will share how deep learning led to a novel dataset with an overall classification accuracy of 98.57%. This classification system will open the gate for a number of Earth observation applications, and can be used for detecting land use or land cover changes as well as assisting in improving geographical maps.
In this webinar, you’ll learn:
- How Deep Learning opens the gate for several new Earth observation applications
- How you can use publicly available datasets for land use and land cover analysis
- How the developed classification model can be used for detecting land use or land cover