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Research Article Open access CC BY 4.0

Remote Sensing and GIS Applications in Vineyard Zoning and Yield Prediction

Mohammed Umar Ali

International Journal of Environment and Climate Change · pp. 11–18 · Published 25 Nov 2025

10.9734/ijecc/2025/v15i125143

Abstract

Remote sensing, which allows us to track the health and condition of the vegetation, is one component of precision agriculture. Numerous studies have examined the applications of remote sensing in agriculture; reviews consolidate this research and examine diverse scientific methodologies. Using imagery obtained by remote sensing platforms like satellites, aircraft, and unmanned aerial vehicles, this project attempts to compile the current vegetation indices utilized in viticulture. Spectroscopy, multispectral and hyper spectral imaging, thermography, electrical resistivity, laser imaging detection and ranging, computer vision, and chlorophyll fluorescence are among the sensing technologies that we describe in this paper. These technologies vary in spatial resolution, data acquisition cost, and suitability for specific vineyard management goals. We also discuss the platforms on which these technologies are typically mounted or embedded for either proximal or remote monitoring. One of the main goals of employing these technologies is to gather and provide data and information to winemakers and grape farmers so they may use it to make better decisions and manage their vineyards and property. Topics covered include crop forecasting, yield and fruit composition, vineyard sampling, targeted management, vegetative growth, canopy architecture, nutrient and water status, pests and diseases, soil and topography, and the present and future use of these technologies in vineyards. These technologies' underlying principles are also explained. The technologies have a lot of potential for farmers, but field-scale acceptance and use will require user-friendly devices and software as well as reasonable prices.

Digital viticulture precision viticulture remote sensing GIS imagery

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