1. Smart Farming
The agricultural sector in Flevoland (a province of the Netherlands) is both nationally and internationally famous for its cultivation of (seed)-potatoes. The province houses Emmeloord, also known as the “World Potato City”. The sector estimates it is the second largest exporter in the world and generates the highest yield per acre worldwide. Nevertheless, it is estimated that the yields can be increased with an additional 10 to 20 percent and the quality of the products can also be increased if the cultivation process is controlled better. An essential element in further improvement is information. Information on when and where which cultivation measures like fertilization, irrigation and pest and disease control measures must be applied. The goal of this project is the realization of “Task Map 2.0” and “AgroGIS”. A task map is a standardized digital instruction which can be used by a dedicated machine to automatically and independently perform different tasks on particular areas of the parcel. Tasks like planting, fertilizing, irrigating, spraying pesticides, etc. The addition “2.0” refers to the fact that in contrast to the current task maps, which are based on one or only a few information sources, “Task Map 2.0” is the result of a comprehensive analysis of as many as possible relevant parcel data, of which a large amount is obtained from open data sources, and biophysical properties; historical yield data, soil properties, crop processing data of the current growth season and observed data for the current growth season like crop scans, laboratory analyses, satellite images, aerial photos and meteorological data. All this data is collected, stored and integrally analyzed in a special information system: “AgroGIS”. The analysis consists of finding spatial and temporal relationships using all data layers to indicate sub-optimal crop growth. These relationships are partly established by automatic image optimization and interpretation algorithms and partly by visual inspection of the images by image analysis experts with a background in agriculture. Next specialized crop advisors interpret the information from “AgroGIS” and the found relationships to formulate an advice and construct “Task Map 2.0”. The farmer him/herself ultimately decides whether (s)he fully or partially accepts the recommendations of “Task Map 2.0”.
1. Smart Farming The agricultural sector in Flevoland (a province of the Netherlands) is both nationally and internationally famous for its cultivation of (seed)-potatoes. The province houses Emmeloord, also known as the “World Potato City”. The sector estimates it is the second largest exporter in the world and generates the highest yield per acre worldwide. Nevertheless, it is estimated that the yields can be increased with an additional 10 to 20 percent and the quality of the products can also be increased if the cultivation process is controlled better. An essential element in further improvement is information. Information on when and where which cultivation measures like fertilization, irrigation and pest and disease control measures must be applied. The goal of this project is the realization of “Task Map 2.0” and “AgroGIS”. A task map is a standardized digital instruction which can be used by a dedicated machine to automatically and independently perform different tasks on particular areas of the parcel. Tasks like planting, fertilizing, irrigating, spraying pesticides, etc. The addition “2.0” refers to the fact that in contrast to the current task maps, which are based on one or only a few information sources, “Task Map 2.0” is the result of a comprehensive analysis of as many as possible relevant parcel data, of which a large amount is obtained from open data sources, and biophysical properties; historical yield data, soil properties, crop processing data of the current growth season and observed data for the current growth season like crop scans, laboratory analyses, satellite images, aerial photos and meteorological data. All this data is collected, stored and integrally analyzed in a special information system: “AgroGIS”. The analysis consists of finding spatial and temporal relationships using all data layers to indicate sub-optimal crop growth. These relationships are partly established by automatic image optimization and interpretation algorithms and partly by visual inspection of the images by image analysis experts with a background in agriculture. Next specialized crop advisors interpret the information from “AgroGIS” and the found relationships to formulate an advice and construct “Task Map 2.0”. The farmer him/herself ultimately decides whether (s)he fully or partially accepts the recommendations of “Task Map 2.0”.
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