Computomics brings sustainable economic success to plant breeders and growers by distilling complex biological data with our machine learning technology, enabling them to produce stable, value-added products, which contribute to resource-efficient agriculture that can feed the world.
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We founded Computomics so farmers and breeders can reap the benefits of our machine learning algorithms.
Agriculture, crop acreage, Monitor crops, crop types extent, Land use, Assess land value, ownership, type, use, Measure land use statistics, Agricultural commodities, Agriculture and rural development policy, Farming, Real-estate management, Local and regional planners, City authorities, Planners, Regional governments, Town authorities, Agriculture and rural policy makers
NEO signals changes to agriculture parcels. Monitoring, based on satellite imagery in combination with artificial intelligence, aims to detect changes in the boundaries of the parcels. The service saves time and money because, based on the mutation signalling, parcels can be looked at more specifically to determine the new parcel boundaries. This supports the process of keeping the national LPIS (Land Parcel Identification System) registry up to date. The service that NEO provides is unique: it is the first time that mutation signalling based on earth observation is performed automatically on this scale. In this way the 500.000 parcels in the Netherlands are monitored. Open data from the national satellite data portal in the Netherlands is used.
Agriculture, Infrastructure, Coastal, Floods, Forests, Inland Water, Land Ecosystems, Land use, Landslides, Sea-ice and icebergs, Snow & Ice, Topography, Urban Areas, Security, Assess Environmental impact of farming, Monitor crops, Assess Deforestation / Forest Degradation, Assess environmental impact of forestry, Assess and monitor water bodies , Monitor land ecosystems and biodiversity, Monitor land cover and detect change , Baseline mapping , Map line of sight visibility (land surface), Asset infrastructure monitoring, Monitor coastal ecosystem, Monitor the coast line, Map and assess flooding, Detect and monitor wildfires, Forecast and assess landslides, Monitor sensitive risk areas, Forecasting epidemics and diseases, land administration, land use studies, monitoring of settlements, urban atlas, urban development, smart cities, rural areas, building inventory, building footprint, spatial planning, land cover, Solar energy, Construction, Forestry, Real-estate management, Transportation
The complexity of modern urban environments has led to the introduction of 3D Land Information Systems (LISs), which tend to replace traditional 2D LIS architectures for the purposes of urban planning and regeneration, land administration, real estate management and civil development. Both the need for 3D visualization of the geometry of buildings in various time instances through the years and the need for acquisition of 3D models in various levels of detail (LoDs), which not only fulfill the requirements of the various users but also they speed up the visualization process, are obvious. Thus, additional dimensions, that is, for time and scale, need to be supported by a modern LIS. This service introduces a 5D modelling pipeline that may be adopted by a multi-purpose LIS for the selective creation of 3D models of an urban area in various time instances and at various LoDs, enriched with cadastral and other spatial data. The methodology is based on automatic change detection algorithms for spatial-temporal analysis of the spatial changes that took place in subsequent time periods, using image orientation, dense image matching and structure from motion algorithms, the procedure requires photogrammetric stereo plotting, implements procedural modelling and relies on the availability of overlapping aerial and terrestrial imagery, ground control points and cadastral information.
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