MINNEAPOLIS, June 13, 2017 /PRNewswire
Geosys, a leading provider of agronomic decision support tools, today launched Geosys™ Labs, a new program that will make its global database of satellite imagery and weather data available to initiatives dedicated to addressing the growing challenges facing the agriculture industry.
Geosys is requesting applications via its website from companies, NGOs and universities interested in establishing a partnership for a proof of concept project. As part of these partnerships, Geosys will provide free access to its remote sensing technologies and agronomic expertise. While there is no specific limitation on the number of projects, qualifying partners must address one of the following objectives:
"Businesses across the ag supply chain face many challenges today, including changing weather patterns and the need to increase production of high quality food with limited resources," said Damien Lepoutre, founder and president of Geosys. "To mark our 30th anniversary this year, we will support organizations and individuals working to solve these critical challenges by providing access to our data and experts who can help uncover opportunities to improve the future of agriculture."
Since 1987, Geosys has managed global satellite imagery from a growing virtual constellation of public and private satellites to help improve decision making practices for customers that represent the entire ecosystem of the agriculture supply chain.
"Geosys Labs is an extension of our traditional business capabilities," said Vincent Lelandais, customer solutions lead, Geosys. "Our objective is to assist efforts that will better our world and the agriculture ecosystem by providing data and imagery to power future solutions."
Photo: Sentinel-2 is the first optical Earth observation mission of its kind to include three bands in the ‘red edge’, which provide key information on the state of vegetation. In this image from 6 July 2015 acquired near Toulouse, France, the satellite’s multispectral instrument was able to discriminate between two types of crops: sunflower (in orange) and maize (in yellow). Copyright Copernicus Sentinel data (2015)/ESA/University of Louvain/CESBIO.