Remote Sensing in Viticulture II

Dear Colleagues,

The technological and scientific developments in the last several decades have allowed the emergence of new approaches for data acquisition and the processing of remote sensed data within the context of precision viticulture. Remote sensing contributes to improvements in decision-support systems, making it possible to retrieve a multitude of information. Vineyard mapping, monitoring phytosanitary issues, yield and quality estimation, and water status monitoring are among the viticulture applications that can be performed with remotely sensed data. In fact, current technology and methodologies enable vineyard monitoring at a parcel scale or at an individual plant scale, with the possibility of estimating different biophysical and geometrical plant parameters, including multi-sensor data fusion approaches.

Given the current widespread availability and accessibility for acquiring, processing and analyzing proximal and remotely sensed data, it is possible to employ these data within any specific period, regardless of the location. Constant updates to time series data with different spatial, spectral and temporal resolutions available from satellite systems enable continuous vineyard monitoring at, local, regional and global scales. The emergence of unmanned aerial systems and mobile or stationary proximal sensing platforms has made it possible to acquire huge amounts of data from various sensors. Considering environmental and economic sustainability, the use of tridimensional, multi- or hyperspectral, and thermal data opens new possibilities to promote more sustainable and efficient vineyard management, supporting the preservation of natural resources.

This Special Issue aims to encourage the publication of studies or review articles documenting recent advances in the viticulture sector using remote sensing and intelligent field monitoring. It aims to cover the development of novel methodologies, algorithms, and applications using remotely sensed data including, but not limited to: grapevine vegetation monitoring using unmanned aerial vehicles (UAVs), airborne and satellite data; vigor mapping and site-specific applications; time series and multi-temporal vineyard analysis; digital image processing, computer vision and machine learning methods applied in viticulture; precision viticulture methods; advances in proximal sensing in viticulture, including the use of image sensors; as well as the estimation and mapping of water status, irrigation demands, and phytosanitary issues. 

Dr. Luís Pádua
Dr. Emanuel Peres
Prof. Dr. Raul Morais dos Santos
Guest Editors

Manuscript Submission Information

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