Presentation
i_SSS - Tool Setup and a Closer Look at Regionalisation
SessionProject Poster Session
Event Type
Project Poster
Pre-Recorded
TimeTuesday, June 23rd4:13pm - 4:16pm
LocationAnalog 2
DescriptionSpatial and temporal site characteristics of agricultural crop land are important determinants regarding potential crop yield. The variation of crop yield depends mainly on the soil's attributes and the local weather conditions. Farming, which is not appropriate to the local conditions, may lead to in situ (affects the local ecosystem) or ex situ (may be caused through matter diffusion into neighbouring ecosystems for example) impairments.
To minimise environmental damages the objective of this project is the development of a Decision Support System (DSS). The DSS is based on the free open-source application SAGA-GIS (System for Automated Geoscientific Analyses - Geographic Information System). SAGA-GIS offers a framework for already over 650 geoscientific tools, which will be expanded by those tools, which are developed during the course of this project.
Several data sources for weather forecasts are analysed and evaluated. To reduce the amount of data, which is fed into the DSS, input data is preprocessed to reduce unnecessary content and convert it into needed formats. Nevertheless, because of the complexity and high amount of necessary computation time, SAGA-GIS respectively the DSS is deployed on HPC infrastructure. The HPC infrastructure allows a time- and storage-efficient data processing and handling, script automated workflows perform periodical data updates automatically.
For this poster we focus on the progress we made regarding the downscaling of weather forecast variables and how we utilise HPC architecture to support this component of our DSS.
To minimise environmental damages the objective of this project is the development of a Decision Support System (DSS). The DSS is based on the free open-source application SAGA-GIS (System for Automated Geoscientific Analyses - Geographic Information System). SAGA-GIS offers a framework for already over 650 geoscientific tools, which will be expanded by those tools, which are developed during the course of this project.
Several data sources for weather forecasts are analysed and evaluated. To reduce the amount of data, which is fed into the DSS, input data is preprocessed to reduce unnecessary content and convert it into needed formats. Nevertheless, because of the complexity and high amount of necessary computation time, SAGA-GIS respectively the DSS is deployed on HPC infrastructure. The HPC infrastructure allows a time- and storage-efficient data processing and handling, script automated workflows perform periodical data updates automatically.
For this poster we focus on the progress we made regarding the downscaling of weather forecast variables and how we utilise HPC architecture to support this component of our DSS.
Poster PDF