| Title |
Seamless integration of above- and under-canopy unmanned aerial vehicle laser scanning for forest investigation
|
|---|---|
| Published in |
Forest Ecosystems, February 2021
|
| DOI | 10.1186/s40663-021-00290-3 |
| Authors |
Yunsheng Wang, Antero Kukko, Eric Hyyppä, Teemu Hakala, Jiri Pyörälä, Matti Lehtomäki, Aimad El Issaoui, Xiaowei Yu, Harri Kaartinen, Xinlian Liang, Juha Hyyppä |
X Demographics
The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Finland | 3 | 23% |
| Belgium | 1 | 8% |
| Unknown | 9 | 69% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 54% |
| Scientists | 5 | 38% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 24% |
| Student > Master | 7 | 14% |
| Researcher | 5 | 10% |
| Student > Bachelor | 3 | 6% |
| Professor | 2 | 4% |
| Other | 3 | 6% |
| Unknown | 18 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 9 | 18% |
| Environmental Science | 7 | 14% |
| Agricultural and Biological Sciences | 4 | 8% |
| Earth and Planetary Sciences | 3 | 6% |
| Computer Science | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 26 | 52% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 March 2024.
All research outputs
#4,465,635
of 25,837,817 outputs
Outputs from Forest Ecosystems
#49
of 379 outputs
Outputs of similar age
#117,381
of 540,167 outputs
Outputs of similar age from Forest Ecosystems
#4
of 18 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 379 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 540,167 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.