AgrismaRT sarà presente con le U.O. CRA-ABP, CRA-VIC e UNIFI-GESAAF alla First Conference  EAGE on Proximal Sensing Supporting Precision Agriculture EAGE che si terrà a Torino dal 6 al 10 September. http://www.eage.org/

In 2015 the First Conference on Proximal Sensing Supporting Precision Agriculture will take place simultaneously to the 21st European Meeting of Environmental and Engineering Geophysics and the First European Airborne Electromagnetics Conference.

Precision agriculture applications need high detailed information in respect to spatial and temporal variability of soil properties, hydrology, and crop evolution. The benefits of precision agriculture to farmers are maximized crop yields and reduced input costs, allowing a farm field to be divided into different management zones for the overall purpose of optimizing economic benefits and environmental protection.

A great variety of soil and crop sensors have been developed and used in the last decade, to provide these maps by non-invasive, quick and relatively cheap methods. State of the art of these technologies is in continuous evolution such as the related data interpretation and elaboration.
The conference will therefore provide an interdisciplinary forum for researchers, professionals and engineers from all over the world to show their latest researches and to share experience in the fields of proximal sensing in agriculture.

The scientific program will be structured according to the following main topics:

1) Applications and techniques of soil proximal sensing
This topic will include innovative researches and applications of soil electrical conductivity/resistivity mapping and tomography, electromagnetic devices (EMI and GPR), soil spectroscopy and radiometric methods, electrochemical and mechanical devices, development of new sensors and multisensors platforms.

2) Applications and techniques of canopy proximal sensing
The topic will cover with applications of innovative and non-invasive technologies to evaluate the spatial variation of vegetation vigour, crop quality and physiological parameters. These technologies include machine vision, Vis-NIR spectroscopy, multi and hyperspectral cameras, NDVI, ultrasonic and LIDAR sensors.

3) Geostatistical methods for proximal sensing, data elaboration and data fusion Proximal sensing provides a great amount of data, which need to be elaborated to produce reliable and useful predictive maps. In this topic, several methods of spatial statistics, data-mining and data-fusion will be presented.