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Article has an altmetric score of 5

Grant support

This work was supported by the Spanish Directorate General for Scientific and Technical Research: [grant number CGL2013-46387-C2-2-R].

Analysis of institutional authors

Manzanera, Jose A.Corresponding AuthorGarcia-Abril, AntonioAuthorPascual, CristinaAuthorTejera, RosarioAuthorMartin-Fernandez, SusanaAuthor

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June 9, 2019
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Fusion of airborne LiDAR and multispectral sensors reveals synergic capabilities in forest structure characterization

Publicated to:Giscience & Remote Sensing. 53 (6): 723-738 - 2016-11-01 53(6), DOI: 10.1080/15481603.2016.1231605

Authors: Manzanera, Jose A.; Garcia-Abril, Antonio; Pascual, Cristina; Tejera, Rosario; Martin-Fernandez, Susana; Tokola, Timo; Valbuena, Ruben;

Affiliations

Univ Eastern Finland, Fac Sci & Forestry, Joensuu, Finland - Author
Univ Politecn Madrid, Coll Forestry & Nat Environm, Res Grp SILVANET, Ciudad Univ, E-28040 Madrid, Spain - Author

Abstract

Forest stand structure is an important concept for ecology and planning in sustainable forest management. In this article, we consider that the incorporation of complementary multispectral information from optical sensors to Light Detection and Ranging (LiDAR) may be advantageous, especially through data fusion by back-projecting the LiDAR points onto the multispectral image. A multivariate data set of both LiDAR and multispectral metrics was related with a multivariate data set of stand structural variables measured in a Scots pine forest through canonical correlation analysis (CCA). Four statistically significant pairs of canonical variables were found, which explained 83.0% accumulated variance. The first pair of canonical variables related indicators of stand development, i.e. height and volume, with LiDAR height metrics. CCA also found attributes describing stand density to be related to LiDAR and spectral variables determining canopy coverage. Other canonical variables pertained to Lorenz curve-derived attributes, which are measures of within-stand tree size variability and heterogeneity, able to discriminate even-sized from uneven-sized stands. The most relevant result was to find that metrics derived from the multispectral sensor showed significant explanatory potential for the prediction of these structural attributes. Therefore, we concluded that metrics derived from the optical sensor have potential for complementing the information from the LiDAR sensor in describing structural properties of forest stands. We recommend the use of back-projecting for jointly exploiting the synergies of both sensors using similar types of metrics as they are customary in forestry applications of LiDAR.

Keywords

AccuracyAirborne laser scanningCanopy structureData fusionDiscrete-return lidarDiversityForest structural typesHeightImageryMultispectral imageryNavigation satellite systemsPacific-northwestPinus-radiataStand structure

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Giscience & Remote Sensing due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2016, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Earth and Planetary Sciences (Miscellaneous).

From a relative perspective, and based on the normalized impact indicator calculated from World Citations from Scopus Elsevier, it yields a value for the Field-Weighted Citation Impact from the Scopus agency: 1.26, which indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: ESI Nov 14, 2024)

This information is reinforced by other indicators of the same type, which, although dynamic over time and dependent on the set of average global citations at the time of their calculation, consistently position the work at some point among the top 50% most cited in its field:

  • Field Citation Ratio (FCR) from Dimensions: 6.44 (source consulted: Dimensions Jul 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-07-06, the following number of citations:

  • WoS: 24
  • Scopus: 35

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-06:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 46.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 47 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 4.05.
  • The number of mentions on the social network X (formerly Twitter): 5 (Altmetric).

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Finland.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (MANZANERA DE LA VEGA, JOSE ANTONIO) .

the author responsible for correspondence tasks has been MANZANERA DE LA VEGA, JOSE ANTONIO.