Contents lists available at ScienceDirect Remote Sensing of Environment journal homepage: www.elsevier.com/locate/rse A smart multiple spatial and temporal resolution system to support precision agriculture from satellite images: Proof of concept on Aglianico vineyard A. Brook a , V. De Micco b , G. Battipaglia c , A. Erbaggio d , G. Ludeno e , I. Catapano e , A. Bonfante f, ⁎ a Spectroscopy & Remote Sensing Laboratory, Department of Geography and Environmental Studies, University of Haifa, Mount Carmel 3498838, Israel b Department of Agricultural Sciences, University of Naples Federico II, Via Università 100, I-80055 Portici, (Naples), Italy c Department of Environmental, Biological and Pharmaceutical Sciences and Technologies, University of Campania "L. Vanvitelli", Via Vivaldi 43, I-81100 Caserta, Italy d Freelance e Institute for the Electromagnetic Sensing of the Environment, National Research Council, (IREA-CNR), Naples, Italy f Institute for Mediterranean Agricultural and Forest Systems -CNR-ISAFOM, National Research Council, Via Patacca, 85, 80056 Ercolano, NA, Italy ARTICLE INFO Keywords: CNN image reconstruction Pan-sharpening Vineyard plant status Dendro-ecological analysis Plant hydraulics Precision agriculture Sentinel-2A UAV Wood anatomy And isotopes ABSTRACT In this century, one of the main objectives of agriculture is sustainability addressed to achieve food security, based on the improvement of use efficiency of farm resources, the increasing of crop yield and quality, under climate change conditions. The optimization of farm resources, as well as the control of soil degradation pro- cesses (e.g., soil erosion), can be realized through crop monitoring in the field, aiming to manage the local spatial variability (time and space) with a high resolution. In the case of high profitability crops, as the case of vineyards for high-quality wines, the capability to manage and follow spatial behavior of plants during the season re- presents an opportunity to improve farmer incomes and preserve the environmental health. However, any field monitoring represents an additional cost for the farmer, which slows down the objective of a diffuse sustainable agriculture. Satellite multispectral images have been widely used for production management in large areas. However, their observation is limited by the pre-defined and fixed scale with relatively coarse spatial resolution, resulting in limitations in their application. In this paper, encouraged by recent achievements in convolutional neural network (CNN), a multiscale full- connected CNN is constructed for the pan-sharpening of Sentinel-2A images by UAV images. The reconstructed data are validated by independent multispectral UAV images and in-situ spectral measurements. The re- constructed Sentinel-2A images provide a temporal evaluation of plant responses using selected vegetation in- dices. The proposed methodology has been tested on plant measurements taken either in-vivo and through the retrospective reconstruction of the eco-physiological vine behavior, by the evaluation of water conductivity and water use efficiency indexes from anatomical and isotopic traits recorded in vine trunk wood. In this study, the use of such a methodology able to combine the pro and cons of space-borne and UAVs data to evaluate plant responses, with high spatial and temporal resolution, has been applied in a vineyard of southern Italy by analyzing the period from 2015 to 2018. The obtained results have shown a good corre- spondence between the vegetation indexes obtained from reconstructed Sentinel-2A data and plant hydraulic traits obtained from tree-ring based retrospective reconstruction of vine eco-physiological behavior. 1. Introduction Sustainable agriculture is one of the main objectives of this century. United Nations and FAO, through the Sustainable Development Goal 2 (SDG2 -Zero Hunger) and the Sustainable Crop Production Intensification (SCPI) Strategic Objective A of FAO STRATEGIC FRA- MEWORK 2010–2019 (FAO, 2009), underline the need to improve farm resource use efficiency (i.e. water and nutrients) as the sole strategy able to increase crop production and quality, face climate change and achieve food security. The achievement of sustainable agriculture is grounded on the knowledge of the agricultural system (soil, climate, crop) and the use of tools able to support the farmer's management strategies (e.g., Decision Support System -DSS, Terribile et al., 2015; LCIS, Bonfante et al., 2019). https://doi.org/10.1016/j.rse.2020.111679 Received 15 May 2019; Received in revised form 7 January 2020; Accepted 22 January 2020 ⁎ Corresponding author. E-mail address: Antonello.bonfante@cnr.it (A. Bonfante). Remote Sensing of Environment 240 (2020) 111679 0034-4257/ © 2020 Elsevier Inc. All rights reserved. T