You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
Chapter title |
Hyperspectral and LiDAR Data for the Prediction via Machine Learning of Tree Species, Volume and Biomass: A Contribution for Updating Forest Management Plans
|
---|---|
Chapter number | 17 |
Book title |
Geomatics for Green and Digital Transition
|
Published by |
Springer, Cham, January 2022
|
DOI | 10.1007/978-3-031-17439-1_17 |
Book ISBNs |
978-3-03-117438-4, 978-3-03-117439-1
|
Authors |
Michelini, Daniele, Dalponte, Michele, Carriero, Angelo, Kutchartt, Erico, Pappalardo, Salvatore Eugenio, De Marchi, Massimo, Pirotti, Francesco |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 8 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Unspecified | 1 | 13% |
Professor | 1 | 13% |
Professor > Associate Professor | 1 | 13% |
Researcher | 1 | 13% |
Unknown | 4 | 50% |
Readers by discipline | Count | As % |
---|---|---|
Unspecified | 1 | 13% |
Environmental Science | 1 | 13% |
Agricultural and Biological Sciences | 1 | 13% |
Earth and Planetary Sciences | 1 | 13% |
Unknown | 4 | 50% |