2. Project setup and data collection
The Smart Farming project is a collaboration between Dutch research institutes, Dutch industry and Dutch agricultural businesses. This collaboration led to the forming of the Smart Farming consortium: Aequator, BocaVista, Ecoflight, Infram, National Aerospace Laboratory, Profytodsd and Weevers Marknesse. This consortium was formed to investigate the possibility of using remote sensing solutions to gain better control of the cultivation process. Two farmers participated in the project. The parcels of these farmers which were investigated as part of this project are both located in the Dutch North East polder. During the growth season of 2014 one farmer cultivated seed-potatoes and the other farmer cultivated ware-potatoes. The first steps of this project consisted of the collection of data. Different types of data were used to find relationships which indicate sub-optimal crop growth. The collected data can be divided into four groups: x Soil: Electric conductivity of substrates, pH-values, organic matter content and lutum content. x Vegetation: Remote sensing images; Images from Unmanned Aerial Systems (UAS) and satellites. x Meteorological: Information about approximately 30 weather parameters. x GIS: Parcel registration, elevation map, soil map and other thematic maps.
2. Project setup and data collection The Smart Farming project is a collaboration between Dutch research institutes, Dutch industry and Dutch agricultural businesses. This collaboration led to the forming of the Smart Farming consortium: Aequator, BocaVista, Ecoflight, Infram, National Aerospace Laboratory, Profytodsd and Weevers Marknesse. This consortium was formed to investigate the possibility of using remote sensing solutions to gain better control of the cultivation process. Two farmers participated in the project. The parcels of these farmers which were investigated as part of this project are both located in the Dutch North East polder. During the growth season of 2014 one farmer cultivated seed-potatoes and the other farmer cultivated ware-potatoes. The first steps of this project consisted of the collection of data. Different types of data were used to find relationships which indicate sub-optimal crop growth. The collected data can be divided into four groups: x Soil: Electric conductivity of substrates, pH-values, organic matter content and lutum content. x Vegetation: Remote sensing images; Images from Unmanned Aerial Systems (UAS) and satellites. x Meteorological: Information about approximately 30 weather parameters. x GIS: Parcel registration, elevation map, soil map and other thematic maps.
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