Henk Janssen
Expert Agri
Parcel Data. Every field. Every detail.
Satellite-driven agricultural parcel data. From crop type and biomass to drought risk, flood risk and yield potential.
What we monitor
We monitor agricultural parcels throughout the growing season: tracking crop development, biomass levels, parcel boundaries and the activities taking place on each field, from ploughing and mowing to harvest. For every parcel we combine satellite observations with public geospatial registrations to classify the current crop, assess risk factors such as drought and flooding, and estimate yield potential based on vegetation indices, shadow cover and subsurface characteristics. Detection, classification and continuous change monitoring are all part of a single, regularly updated dataset.
Methodology & Technology
We combine Sentinel and other satellite imagery, aerial photography and publicly available geospatial datasets (including the BRP Basisregistratie Gewaspercelen and the national Cadastre) and process them through automated remote sensing algorithms and machine learning models to detect parcel boundaries, classify crop types and calculate a comprehensive set of agronomic and risk attributes at field level.
Quality control procedures run throughout the processing workflow, and outputs are validated against reference datasets before delivery. Spatial resolution ranges from centimetres to metres depending on the location and use case, with time series continuously updated as new satellite data becomes available. Enabling both operational monitoring during the growing season and longer-term trend analysis across years.
Examples of what we detect
Parcel geometry records the precise boundary coordinates of each field in WGS 84, derived from BRP registration data and updated whenever boundaries change — for example following ditch filling or land consolidation. It is the spatial foundation for all other attributes and the link to external GIS and administrative systems.
Surface area records the total field size in square metres. It is the baseline unit for agronomic calculations, subsidy administration and scaling any per-hectare measurement to total production or risk exposure.
Category classifies each parcel as arable land, grassland or fallow, providing the top-level agronomic context that determines which monitoring parameters, benchmarks and policy frameworks apply.
Current cultivation identifies the crop grown on the parcel in the current calendar year. From maize and potatoes to temporary grassland and agri-environmental mixtures. It is the primary attribute for crop-specific analysis, compliance verification and supply chain sourcing assessments.
Previous cultivation records the crop grown in the prior year, enabling crop rotation analysis, soil health assessment and multi-year performance comparisons at field level.
NDVI represents the current greenness and vegetation density of the parcel based on satellite spectral analysis. A value above 0.4 indicates active, healthy vegetation; values at or below 0.4 signal that vegetation is under stress, dying or absent. Making this the most widely used early-warning indicator for crop problems during the growing season.
EVI provides a complementary vegetation health signal that is more sensitive than NDVI in areas with high biomass and less affected by shadows, atmospheric moisture or snow. It is the preferred index where precision matters and where standard NDVI is known to saturate under dense canopy conditions.
SWI measures current moisture levels in the shallow subsurface directly below ground level, expressed as a percentage from 0 to 100. High values indicate saturated conditions with flood risk potential; low values signal drought stress — making this the key operational indicator for irrigation management and risk monitoring during dry or wet periods.
Drought risk is a structural parcel-level score from 1 to 6, based on subsurface soil type and its water-holding capacity. Unlike SWI, which reflects current conditions, drought risk reflects the inherent vulnerability of a parcel to dry periods. Essential for long-term planning, insurance risk assessment and precision agriculture investment decisions.
Flooding risk flags whether a parcel is located in a flood-prone zone with a medium or higher probability of inundation. It combines topographic position with hydrological risk models and is a critical input for climate risk disclosure, crop insurance and infrastructure planning near agricultural land.
Elevation profile classifies the topographic shape of each parcel as flat, concave, convex or sloped, derived from digital elevation models. Shape determines water runoff behaviour, pooling risk and the evenness of crop development across the field. All of which affect both yield and management decisions.
Shadow coverage records the percentage of the parcel surface that is in shadow at solar noon on the shortest day of the year. Caused by adjacent trees, buildings or other structures. High shadow coverage reduces photosynthetically active radiation and is a meaningful predictor of yield reduction, especially on parcels bordering urban areas or tree lines.
Heterogeneity scores each parcel from 1 to 5 based on its internal spatial variability. Reflecting how uniformly productive the field is likely to be. Low-heterogeneity parcels have more consistent yield potential; high-heterogeneity parcels are candidates for precision agriculture interventions targeting within-field variation.
These two proximity attributes record the distance in metres from each parcel to the nearest road and to the nearest surface water body. They are relevant for logistics planning, spray buffer compliance, irrigation access assessment and flood risk contextualisation.
Output & integration
Parcel data is available via API for direct integration into GIS platforms, agricultural management systems and data analytics environments, and via periodic reporting for organisations that require structured delivery on a scheduled basis.
All outputs are provided in standard geospatial formats (compatible with QGIS, ArcGIS and BI tooling) and are linkable to BRP and Cadastral identifiers, enabling seamless connection to existing administrative and agronomic workflows.
The dataset combines directly with crop monitoring data for in-season performance analysis, with water data for drought and flood risk modelling, with impervious surface data for urban-agricultural boundary assessments, and with landscape element data for nature-inclusive farming and agri-environment scheme reporting.
Connected Intelligence
Challenge us.
We work with organisations that have specific, complex or non-standard data needs and we like it that way. Tell us what you’re looking for.
Explore our parcel data and it’s possibilities.
Henk Janssen
Expert Agri
