Researchprojects

BAB 049/21: Open Data Cube as data repository and analysis tool for drought monitoring

Development of analysis tools for recurring agricultural policy issues based on the example of drought monitoring

Initial situation

A data cube (ODC) was set up at the Federal Institute of Agricultural Economics and Mountain Farming (BAB) in order to efficiently manage and analyze the constantly growing amount of raster data. The unique feature of the BAB's Open Data Cube is the extension of the technology originally intended for satellite images so that other data can also be indexed and loaded as time series into this multidimensional data cube. This will make it possible to intersect and evaluate a variety of raster and rasterized vector data (including ALS, INVEKOS and climate data) and satellite images together in one system. In addition to the purely spatial analysis, the temporal dimension can also be taken into account in the calculations and evaluations in the multidimensional data cube, which enables high-performance analyses of time series.

Objective

The aim is to establish the ODC as an analysis tool at the BAB in order to be able to carry out recurring data evaluations as a basis for decision-making on agricultural policy issues in the future in a much more targeted and, above all, more performant manner. The ODC should serve as a networked data center and be able to function openly for data integration via cloud object storage interfaces (e.g. S3).This is intended to replace part of the existing geodata infrastructure.This solution minimizes sources of error, makes the most up-to-date data immediately available to all users and is managed decentrally.The aim is for users to be able to carry out the necessary analyses independently via an internet browser on the underlying infrastructure. Existing analysis functions are to be expanded and recurring evaluations of various issues can be updated. As an example application, monitoring of Austria's climatic development is being developed specifically for agricultural areas. The ODC is to be transferred from a pilot environment to a scalable, fail-safe productive environment in the further course of the project.

Status of the project

The Jupyterhub platform around the ODC was migrated from a test environment to a Kubernetes cluster (system for orchestrating container applications), which ensures high reliability and rapid scalability.
In 2023, the infrastructure was further optimized and expanded into a dask cluster.This makes it possible to parallelize processes and make the best possible use of the hardware resources of the Kubernetes cluster in order to increase performance.In addition, login to the platform was replaced by single sign-on (SSO).

As a methodological use case, defined climate parameters (e.g. the climatic water balance, heat days and dry periods of 10 or more days) were calculated for each cadastral municipality in Austria for the normal climate period 1961-1990 and 1991-2020.The aim was to show climate changes and to create a basis that allows these or similar recurring questions to be answered at short notice with current data if required.

The ODC was presented and discussed at the GI-Salzburg 2023.

Planned work 2024

Due to the positive experience gained in the course of the ODC project and the possibility of storing the growing amounts of raster data (satellite, ALS, climate data, etc.) in a structured way and being able to evaluate them in combination for many questions, the ODC and the Jupyterhub environment will be further developed in 2024.The results of analyses already carried out, such as the calculation of climate parameters for arable and grassland areas, are to be updated once up-to-date data has been acquired. The long-term trend is now moving towards decentralized evaluation, where the large volumes of data no longer need to be stored.For this reason, the infrastructure will be further developed and data will increasingly be integrated using STAC (Spatio Temporal Asset Catalogs) in 2024. This is a specification that enables interoperable access to a wide range of global data without having to download this data yourself.

At the current request of the BML, the monitoring of climatic development is to be expanded. With a focus on agricultural areas, current climatic indices (based on climate data) and vegetation indices (based on satellite data) are to be calculated and compared with long-term mean values.

Schedule

Project start: 01/2021
Project end: 12/2024

 

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