The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The urban impervious surface has been recognized as a key quantifiable indicator in assessing urbanization and its environmental impacts. Adopting deep learning technologies, this study proposes an approach of three-dimensional convolutional neural networks (3D CNNs) to extract impervious surfaces from the WorldView-2 and airborne LiDAR datasets. The influences of different 3D CNN parameters on impervious...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.