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UC 92 — SoilFieldSpec

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Key Information
Title
Library of VNIRS field spectral data of soils
Acronym
SoilFieldSpec
Coordinator
Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB Potsdam) (Germany)Research Institute
Duration
24 months
Budget
Not shown at your access level. Hidden
Maturity
Committed
Source
In Proposal
Use Case Summit Pitch
Soils, Nutrients & GHG Emissions Accounting
Sectors
Arable cropFruitsVegetables
Data Types
Machine sensor dataFarm Management Information Systems (FMIS) dataModels & Macro data
SRIA Activities

3.1.2 Data integration and data quality

  • 3.1.2.4 Reference data sets & non-discriminatory data
  • 3.1.2.9 Granularity through smart systems & edge compute
  • 3.1.2.11 Models to increase data granularity
  • 3.1.2.12 Solutions for private/public interests

3.1.4 Applications of AI techniques

  • 3.1.4.1 Identify key reference/training data sets
  • 3.1.4.6 Digital twins of farms & environments
  • 3.1.4.7 Strengthen AI uptake; trust in AI

3.2.1 Enhancing functionality of and generating input for DSS including FMIS

  • 3.2.1.1 Data layers & algorithms for FMIS services
Themes
Earth observation & remote sensingLong-term experiments & databases
Partners (2)
  • Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB Potsdam)P1
    Coordinator

    GermanyResearch Institute

  • Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB Potsdam)P2

    GermanyResearch Institute

#OrganisationCountryType
P1Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB Potsdam)Coordinator

Introduction SoilFieldSpec addresses the limited availability of high-resolution soil information resulting from the high costs and low temporal frequency of conventional soil analysis. The use case focuses on visible and near- infrared spectroscopy (VNIRS) as a rapid, non-destructive, and mobile approach for in situ soil characterization under practical field conditions. Its main objective is the creation of a publicly available library of mobile VNIRS soil spectral data across different soilscapes to support precision agriculture, soil health monitoring, and environmental assessment. Methodologies The use case collects mobile in situ VNIRS measurements acquired directly in agricultural environments under varying field conditions. The collected spectra are linked to reference soil parameters such as soil organic matter (SOM), soil moisture, pH, texture, and macronutrients. In contrast to existing laboratory-based spectral libraries relying on pre-treated soil samples, SoilFieldSpec focuses on field-based measurements and the development of calibration approaches suitable for practical applications. The collected data supports the development of site-independent calibration models at farm and regional scales and enables benchmarking of mobile VNIRS systems against other soil mapping approaches. Output • VNIRS data publication: Public release of mobile in situ VNIRS field spectral data from soils in East Brandenburg (Germany). • SoilFieldSpec library: Collection and publication of mobile in situ VNIRS datasets from soils across different regions worldwide. • VNIRS calibration models: Development of site-independent calibration models for SOM, soil moisture, pH, and macronutrients at farm and regional levels. Impact The use case contributes to improving the spatial and temporal resolution of soil monitoring through affordable and rapid field-based measurements. By enabling real-time assessment of soil properties directly under field conditions, SoilFieldSpec supports precision agriculture, soil management decisions, and broader access to soil information for researchers, advisors, authorities, and farmers. What I Can Offer • Mobile in situ VNIRS datasets acquired under practical field conditions. • Publicly available soil spectral datasets and calibration resources. • Experience with field-based soil sensing and site-independent calibration approaches. • Benchmarking opportunities for evaluating mobile soil sensing technologies. What I Need • Collaboration on calibration modelling and spectral data processing. • Exchange on benchmarking methodologies and validation strategies. • Approaches for harmonizing and integrating heterogeneous soil spectral datasets. • Cooperation with related initiatives in soil sensing, precision agriculture, and environmental monitoring

Source: Annual AgData Use Case Summit 2026 booklet.

Statistics Registers data
  • 3.2.1.2 Extrapolate farm-generated sensor data
  • 3.2.1.3 New satellite imagery & ground sensors for DSS
  • 3.2.2 Farm modelling systems

    • 3.2.2.3 Whole-farm & landscape environmental impact
    • 3.2.2.4 Farm modelling for optimal practice

    3.2.3 Assessment of farm performance

    • 3.2.3.1 Thematic areas for farm metrics

    3.2.4 Data-based solutions for addressing environmental challenges

    • 3.2.4.1 Assess needs for environmental decision support
    • 3.2.4.2 Prescription maps for precision cropping
    • 3.2.4.4 Areas for biodiversity & pollinator conservation
    • 3.2.4.7 Long-term experiments for soil health & C

    3.2.5 Strategies and technologies for climate change adaptation

    • 3.2.5.1 Resilient livestock & cropping systems

    3.3 Data-based solutions for policy-making

    • 3.3.10 Europe-wide upscaling of (precision) farming data

    4.1 Public-private synergies (R&I activities)

    • 4.1.1.5 Develop reusable data-based solutions
    • 4.1.1.6 Scalable B2G data-sharing solutions

    4.2 Data governance, standards and security (R&I activities)

    • 4.2.4.5 Highlight Common European Agriculture Data Space

    4.3 Uptake & innovation management (R&I activities)

    • 4.3.1.1 Evidence of the value of data technologies
    • 4.3.1.3 User-friendly data platforms
    Germany
    Research Institute
    P2Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB Potsdam)GermanyResearch Institute