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 quality of point clouds obtained by RGB-D camera-based indoor mobile mapping can be limited by local degradation because of complex scenarios such as sensor characteristics, partial occlusions, cluttered backgrounds, and complex illumination conditions. This paper presents a machine learning framework to assess the local quality of indoor mobile mapping point cloud data. In our proposed framework,...
Spatio-temporal variations of vegetation phenology, e.g. start of green-up season (SOS) and end of vegetation season (EOS), serve as important indicators of ecosystems. Routinely processed products from remotely sensed imagery, such as the normalized difference vegetation index (NDVI), can be used to map such variations. A remote sensing approach to tracing vegetation phenology was demonstrated here...
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.