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Comparison of Satellite and UAV-Based Multispectral Imagery for Vineyard Variability Assessment

1
Dipartimento di Elettronica e Telecomunicazioni (DET), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
2
Dipartimento Energia (DENERG), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
3
Dipartimento di Scienze Agrarie, Forestali e Alimentari (DiSAFA), Università degli Studi di Torino, Largo Paolo Braccini 2, 10095 Grugliasco (TO), Italy
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(4), 436; https://doi.org/10.3390/rs11040436
Received: 14 January 2019 / Revised: 12 February 2019 / Accepted: 17 February 2019 / Published: 20 February 2019
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Abstract

In agriculture, remotely sensed data play a crucial role in providing valuable information on crop and soil status to perform effective management. Several spectral indices have proven to be valuable tools in describing crop spatial and temporal variability. In this paper, a detailed analysis and comparison of vineyard multispectral imagery, provided by decametric resolution satellite and low altitude Unmanned Aerial Vehicle (UAV) platforms, is presented. The effectiveness of Sentinel-2 imagery and of high-resolution UAV aerial images was evaluated by considering the well-known relation between the Normalised Difference Vegetation Index (NDVI) and crop vigour. After being pre-processed, the data from UAV was compared with the satellite imagery by computing three different NDVI indices to properly analyse the unbundled spectral contribution of the different elements in the vineyard environment considering: (i) the whole cropland surface; (ii) only the vine canopies; and (iii) only the inter-row terrain. The results show that the raw s resolution satellite imagery could not be directly used to reliably describe vineyard variability. Indeed, the contribution of inter-row surfaces to the remotely sensed dataset may affect the NDVI computation, leading to biased crop descriptors. On the contrary, vigour maps computed from the UAV imagery, considering only the pixels representing crop canopies, resulted to be more related to the in-field assessment compared to the satellite imagery. The proposed method may be extended to other crop typologies grown in rows or without intensive layout, where crop canopies do not extend to the whole surface or where the presence of weeds is significant. View Full-Text
Keywords: precision agriculture; remote sensing; satellite imagery; UAV; decision viticulture precision agriculture; remote sensing; satellite imagery; UAV; decision viticulture
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Khaliq, A.; Comba, L.; Biglia, A.; Ricauda Aimonino, D.; Chiaberge, M.; Gay, P. Comparison of Satellite and UAV-Based Multispectral Imagery for Vineyard Variability Assessment. Remote Sens. 2019, 11, 436.

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