A drone flies over a field while a tractor drives along a dirt road.
Feasibility Study: The Use of Remote Sensing Data in Digital Agriculture

Modern agriculture sits at the intersection of traditional farming practices and cutting-edge digitalization. Thanks to the availability of free remote sensing data (e.g., via Copernicus), farmers have access to enormous amounts of information. The challenge, however, lies in transforming this raw data into actionable, value-adding insights.

On behalf of the State Office for Environment, Agriculture, and Geology (LfULG), PIKOBYTES conducted a comprehensive feasibility study to evaluate the practical applications of this data. The focus was on two key application areas: optimizing fertilization strategies for resource efficiency and improving yield forecasts to enhance planning reliability. The study analyzes a wide range of scientific publications on the use of remote sensing products in agriculture and demonstrates how data-driven decision support for farmers can be implemented.

Project contents

In this scientific feasibility study, the PIKOBYTES team systematically evaluated and documented over 20 different indicators and data products to determine their specific suitability for agricultural practice. The spectrum ranged from classic vegetation indices such as NDVI, LAI, and NDWI to highly relevant meteorological data and soil-specific parameters. The methodological approach was characterized by a sound scientific foundation.

In addition to the precise characterization of each indicator, PIKOBYTES integrated a comprehensive review of relevant scientific studies to ensure the practical applicability of the results. To ensure seamless technical implementation, PIKOBYTES also specified processes for automated data access via interfaces such as the Sentinel Hub or the Climate Data Center of the German Weather Service. The practical utility of this complex data analysis is illustrated by the development of a specialized system for creating fertilizer and application maps, which enables highly precise management through the intelligent linking of vegetation indices, crop types, and specific growth stages.

The study is publicly available and can be found in the LfULG publication series (Issue 8/2025).

Technology

We rely on a sophisticated combination of proven methods and innovative technologies to not only implement projects, but to make them successful in the long term. Our strength lies in the intelligent combination of experience and progress – from established standards to state-of-the-art digital solutions.

We use the following methods and technologies for the Feasibility Study: The Use of Remote Sensing Data in Digital Agriculture

GIS
Systemanalyse
Räumliche Analysen
Fernerkundung
Smart Farming
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