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Grant support

This research was funded by the Spanish Economy and Competitiveness Ministry (MINECO) and the European Agricultural Funds for Rural Development. Reference: AGL2013-49047-C2-1-R, AGL2016-77282-C33-R and the Fundacion Seneca, Agencia de Ciencia y Tecnologia of the Region of Murcia under the Excellence Group Program 19895/GERM/15. Victor Blanco acknowledges the research initiation grant received from the Technical University of Cartagena (UPCT).

Analysis of institutional authors

Blanco, VCorresponding Author
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Article

Potential of UAS-Based Remote Sensing for Estimating Tree Water Status and Yield in Sweet Cherry Trees

Publicated to:Remote Sensing. 12 (15): 2359- - 2020-08-01 12(15), DOI: 10.3390/rs12152359

Authors: Blanco, Victor; Jose Blaya-Ros, Pedro; Castillo, Cristina; Soto-Valles, Fulgencio; Torres-Sanchez, Roque; Domingo, Rafael

Affiliations

Complejo Espinardo, Londonderry Maps, Parque Cientif Murcia, Ctra Madrid,Km 388, E-30100 Espinardo, Spain - Author
Univ Politecn Cartagena UPCT, Dept Automat Ingn Elect & Tecnol Elect, Campus Muralla S-N, E-30202 Cartagena, Spain - Author
Univ Politecn Cartagena UPCT, Dept Ingn Agronam, Paseo Alfonso XIII 48, E-30203 Cartagena, Spain - Author

Abstract

The present work aims to assess the usefulness of five vegetation indices (VI) derived from multispectral UAS imagery to capture the effects of deficit irrigation on the canopy structure of sweet cherry trees (Prunus aviumL.) in southeastern Spain. Three irrigation treatments were assayed, a control treatment and two regulated deficit irrigation treatments. Four airborne flights were carried out during two consecutive seasons; to compare the results of the remote sensing VI, the conventional and continuous water status indicators commonly used to manage sweet cherry tree irrigation were measured, including midday stem water potential (psi(s)) and maximum daily shrinkage (MDS). Simple regression between individual VIs and psi(s)or MDS found stronger relationships in postharvest than in preharvest. Thus, the normalized difference vegetation index (NDVI), resulted in the strongest relationship with psi(s)(r(2)= 0.67) and MDS (r(2)= 0.45), followed by the normalized difference red edge (NDRE). The sensitivity analysis identified the optimal soil adjusted vegetation index (OSAVI) as the VI with the highest coefficient of variation in postharvest and the difference vegetation index (DVI) in preharvest. A new index is proposed, the transformed red range vegetation index (TRRVI), which was the only VI able to statistically identify a slight water deficit applied in preharvest. The combination of the VIs studied was used in two machine learning models, decision tree and artificial neural networks, to estimate the extra labor needed for harvesting and the sweet cherry yield.

Keywords
Artificial neuronal networkDecision treeDeficit irrigationDviIndicatorsManagementMultispectral imageryNdreNdviOsaviPredictionQualitySoilStressVariabilityVegetationWater deficit

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Remote Sensing due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2020, it was in position 27/200, thus managing to position itself as a Q1 (Primer Cuartil), in the category Geosciences, Multidisciplinary.

From a relative perspective, and based on the normalized impact indicator calculated from World Citations provided by WoS (ESI, Clarivate), it yields a value for the citation normalization relative to the expected citation rate of: 1.41. This 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: 5.55 (source consulted: Dimensions Apr 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-04-26, the following number of citations:

  • WoS: 25
  • Scopus: 29
  • Google Scholar: 29
  • OpenCitations: 21
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 2025-04-26:

  • 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: 76.
  • 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: 74 (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: 1.85.
  • The number of mentions on the social network X (formerly Twitter): 2 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
Leadership analysis of institutional authors

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 (BLANCO MONTOYA, VICTOR) .

the author responsible for correspondence tasks has been BLANCO MONTOYA, VICTOR.