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Article

Intercomparison of UAV, Aircraft and Satellite Remote Sensing Platforms for Precision Viticulture

by
Alessandro Matese
1,*,
Piero Toscano
1,
Salvatore Filippo Di Gennaro
1,2,
Lorenzo Genesio
1,
Francesco Primo Vaccari
1,
Jacopo Primicerio
1,3,
Claudio Belli
4,
Alessandro Zaldei
1,
Roberto Bianconi
4 and
Beniamino Gioli
1
1
IBIMET CNR–Istituto di Biometeorologia, Consiglio Nazionale delle Ricerche, via G. Caproni 8, 50145 Firenze, Italy
2
DSAA-Dipartimento di Scienze Agrarie, Alimentari e Ambientali, Università di Perugia, Borgo XX Giugno 7, 06123 Perugia, Italy
3
Dipartimento di Scienze Agrarie, Forestali e Agroalimentari, Università di Torino, Via Leonardo Da Vinci 44, 10095 Grugliasco, Italy
4
Terrasystems.r.l., Via Pacinotti, 5, 01100 Viterbo, Italy
*
Author to whom correspondence should be addressed.
Remote Sens. 2015, 7(3), 2971-2990; https://doi.org/10.3390/rs70302971
Submission received: 14 November 2014 / Revised: 15 January 2015 / Accepted: 17 February 2015 / Published: 13 March 2015

Abstract

Precision Viticulture is experiencing substantial growth thanks to the availability of improved and cost-effective instruments and methodologies for data acquisition and analysis, such as Unmanned Aerial Vehicles (UAV), that demonstrated to compete with traditional acquisition platforms, such as satellite and aircraft, due to low operational costs, high operational flexibility and high spatial resolution of imagery. In order to optimize the use of these technologies for precision viticulture, their technical, scientific and economic performances need to be assessed. The aim of this work is to compare NDVI surveys performed with UAV, aircraft and satellite, to assess the capability of each platform to represent the intra-vineyard vegetation spatial variability. NDVI images of two Italian vineyards were acquired simultaneously from different multi-spectral sensors onboard the three platforms, and a spatial statistical framework was used to assess their degree of similarity. Moreover, the pros and cons of each technique were also assessed performing a cost analysis as a function of the scale of application. Results indicate that the different platforms provide comparable results in vineyards characterized by coarse vegetation gradients and large vegetation clusters. On the contrary, in more heterogeneous vineyards, low-resolution images fail in representing part of the intra-vineyard variability. The cost analysis showed that the adoption of UAV platform is advantageous for small areas and that a break-even point exists above five hectares; above such threshold, airborne and then satellite have lower imagery cost.
Keywords: precision agriculture; Unmanned Aerial Vehicle (UAV); remote sensing precision agriculture; Unmanned Aerial Vehicle (UAV); remote sensing
Graphical Abstract

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MDPI and ACS Style

Matese, A.; Toscano, P.; Di Gennaro, S.F.; Genesio, L.; Vaccari, F.P.; Primicerio, J.; Belli, C.; Zaldei, A.; Bianconi, R.; Gioli, B. Intercomparison of UAV, Aircraft and Satellite Remote Sensing Platforms for Precision Viticulture. Remote Sens. 2015, 7, 2971-2990. https://doi.org/10.3390/rs70302971

AMA Style

Matese A, Toscano P, Di Gennaro SF, Genesio L, Vaccari FP, Primicerio J, Belli C, Zaldei A, Bianconi R, Gioli B. Intercomparison of UAV, Aircraft and Satellite Remote Sensing Platforms for Precision Viticulture. Remote Sensing. 2015; 7(3):2971-2990. https://doi.org/10.3390/rs70302971

Chicago/Turabian Style

Matese, Alessandro, Piero Toscano, Salvatore Filippo Di Gennaro, Lorenzo Genesio, Francesco Primo Vaccari, Jacopo Primicerio, Claudio Belli, Alessandro Zaldei, Roberto Bianconi, and Beniamino Gioli. 2015. "Intercomparison of UAV, Aircraft and Satellite Remote Sensing Platforms for Precision Viticulture" Remote Sensing 7, no. 3: 2971-2990. https://doi.org/10.3390/rs70302971

APA Style

Matese, A., Toscano, P., Di Gennaro, S. F., Genesio, L., Vaccari, F. P., Primicerio, J., Belli, C., Zaldei, A., Bianconi, R., & Gioli, B. (2015). Intercomparison of UAV, Aircraft and Satellite Remote Sensing Platforms for Precision Viticulture. Remote Sensing, 7(3), 2971-2990. https://doi.org/10.3390/rs70302971

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