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Institute of

LV Rural Studies

Project

Development of an automated support system to monitor agricultural funding sites (timeStamp)


Lead Institute LV Institute of Rural Studies

Identification of land use by Sentinel-1 satellite image time series
© Bild links [image left]: www.esa.int - Bild rechts [image right]: http://webapp.flf.julius-kuehn.de/gisapp/projekte

The monitoring of area-related measures in context of the Common Agricultural Policy (CAP) and nature conservation is currently carried out through time-consuming and cost-intensive on-site inspections. By using Sentinel satellite data, authorities of the agricultural and nature conservation agencies shall be able to reduce on-site inspections in the future. A cloud-based web application has been developed to aid this process, by performing an automated satellite data analysis, displaying evaluation results and download options for users.

Background and Objective

The good spatial coverage and high temporal resolution of the Sentinel satellites of the European Copernicus Earth observation programme enable a close temporal recording of agricultural land use and the identification of land use changes.
We aim to aid administrative authorities and other interested users to integrate satellite data anylsis into their work in order to impove the efficiency of time- and cost-intensive on-site checks in areal monitoring. Within the project "timeStamp" scientists of the Thünen Institute and the other project partners have been developing a web application. This application evaluates whether the declared land use corresponds with the land use depicted by satellite data, or if land use change is indicated. As an exemplary use case the "monitoring EFA/greening catch crop sites in the context of the EU agricultural funding (CAP)" has been implemented. Control cues are provided with a traffic light colour coding.
In addition, a multifunctional basic function provides standard time-series graphs, test parameters and change indicators to be used in monitoring land use change and land use management.

Target Group

Ministries of agriculture and environment, land authorities, official nature conservation, agricultural administration, European Commission

Approach

The following steps are undertaken:

  • user workshops with cooperating authorities to assess the functionalities required and to determination the subject-specific and technical requirements of the web application to be developed
  • based on the requirements analysis, the processed satellite-image time series of Sentinel-2 are used to develop appropriate indicators and evaluation approaches (algorithms) and be validated by test data sets to monitor the lifetime of catch crops
  • development and visualisation of indicators for the multifunctional base function based on Sentinel-1 and -2-time series data
  • evaluation algorithms for the application are implemented into a cloud-based processing environment
  • implementation of an object-related evaluation of field and site geometries to be monitored based on remote sensing data
  • development of a user-friendly web application to provide data exchange, selection of test indicators for the control sites and a spatial visualization of the results including site-specific information (e.g., a traffic-light system) for on-site controls
  • user workshop to inform potential users and get their feedback on usability and user experience
  • migration of the application to CODE-DE and operationalisation

Data and Methods

By analysing the Sentinel-1 (radar) and Sentinel-2 (spectral) time series data, algorithms for the identification of catch crops can be derived using appropriate metrics (measures) and indices for seeding, growth and plough of the catch crops.

For the development of the algorithms, catch-crop sites in the field are mapped and IACS and on-site control data are used for training and tests.

The technical infrastructure of the application has been implemented in the Microsoft AzureCloud initially and will be migrated to CODE-DE. The backend has a modular design based on docker containers. With the user interface users can create, upload and manage jobs and also display and download the results.

Our Research Questions

  • What subject-specific requirements (required input data, metrics, indicators, temporal rhythms of the evaluations) have the respective authorities to the web application?
  • What are technical requirements for the target system (including data formats, software environments, interfaces, programming languages)?
  • What are appropriate metrics, indicators, and algorithms (e.g., NDVI, matching with phenological pattern profiles,) to recognize the lifetime of catch crops?

Preliminary Results

The prototype of the timeStamp application provides a cloud-based software infrastructure for automated remote sensing data analysis.

The user interface enables users with basic knowledge on remote sensing to integrate satellite data into their work.

The multifunctional basic function offers evaluation options for a variety of topics related to monitoring land use and nature conservation. The verification of catch crop sites is based on the analysis of the temporal pattern of the vegetation index (NDVI). Based on a set of test parameters (e.g. minima, maxima, trends) the probability of the presence of a catch crop is calculated. These site-specific evaluation results and the output of visual control instructions can support a targeted planning of spot checks.

The timeStamp application will developed further within the projects 'SenSchiene' and 'Copernicus lights green'.

Involved external Thünen-Partners

Funding Body

  • Federal Ministry for Economic Affairs and Energy (BMWi)
    (national, öffentlich)
  • German Aerospace Center (DLR)
    (national, öffentlich)

Duration

8.2018 - 12.2022

More Information

Projekt type:
Project funding number: 50EW1704A
Funding program: DLR - Entwicklung und Implementierungsvorbereitung von Copernicus Diensten für den öffentlichen Bedarf in Deutschland
Project status: ongoing

Publications to the project

  1. 0

    Schulz C, Holtgrave A-K, Kleinschmit B (2021) Large-scale winter catch crop monitoring with Sentinel-2 time series and machine learning - An alternative to on-site controls? Comput Electron Agric 186:106173, DOI:10.1016/j.compag.2021.106173

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