Digitization is also making its way into agriculture. In order to fully exploit the economic and ecological potential inherent in precision farming, fundamental information from soil maps and satellite data is necessary. Recently, satellite data with high temporal, spatial and radiometric resolution have become more readily available and enable up-to-date monitoring of the earth's surface. With the help of these data, the current state of vegetation on agricultural land can be assessed at any time. In combination with both Austrian soil information systems - financial soil estimation and soil mapping - new possibilities open up to obtain up-to-date indirect information on soil properties. The achievable added value of a combination of these bases was examined in the present project within six pilot areas and the arising difficulties and resulting uncertainties were recorded and described. Thus, the potential of the different data sources can be recognized.
Combining remote sensing data with data collected in the field opens up new possibilities. For example, information from satellite imagery can be very informative for delineating soil units in the field, especially those with extreme characteristics (e.g., lower-yielding sites such as soils over high overlying gravel bodies).
A major advantage is the constant availability and timeliness of remote sensing data. A vegetation index (Normalized Difference Vegetation Index - NDVI) and three biophysical variables (Leaf Area Index - LAI, Fraction of absorbed photosynthetically active radiation - FAPAR, Fraction of Green Vegetation Cover - FCOVER, Enhanced Vegetation Index - EVI) were calculated from the satellite data and important information for the soil was derived. By adding soil properties from available soil data, fertilizer application and seeding maps were created for the pilot areas studied.
Benefit of the project
Unfortunately, it was not possible to merge the two soil data sets and the satellite data over a large area in the data structure currently available. Accordingly, the planned automation for larger study areas was also not possible. However, the combination of the financial soil estimation data with the remote sensing data certainly has potential for the production of maps as a basis for precision agriculture.
Project acronym: BODAT
Project Management: AGES, Dr. Andreas Baumgarten, Institute for Sustainable Plant Production
BFW - Federal Forest Research Center
Federal Environmental Agency
Lower Austrian Provincial Chamber of Agriculture
Federal Institute for Agricultural Economics and Mountain Farming Questions
Higher Federal Teaching and Research Institute for Agriculture, Agricultural Engineering and Food Technology Wieselburg
Funding: Funding program BMLRT (BMNT, BMLFUW) - DAFNE
Last updated: 25.04.2023