Linking remote sensing and crop models to estimate the aboveground biomass of annual and perennial forage crops
Facundo is an Agricultural Engineer from the University of Buenos Aires (2017). He has worked on numerous projects as a member of the Regional Analysis and Remote Sensing Laboratory at the Agricultural Plant Physiology and Ecology Research Institute, University of Buenos Aires UBA-LART. These projects are related to the generation of knowledge in the field of Agricultural and Environmental Sciences and particularly in the evaluation and use of natural resources. He is doing a PhD in Agricultural Sciences EPG-FAUBA and currently, Facundo is a teaching assistant of the Ecology course in the Department of Natural Resources. His work is focused on the estimation of aboveground biomass of annual and perennial forage resources to help farmers in the process of making decisions about the profitability and sustainability of agricultural systems.
Contact: [email protected]
About the project
The prediction of aboveground biomass of forage resources under different environmental by crop management combinations allows making decisions more objectively and increasing the efficiency and sustainability of livestock systems. Traditional sampling through harvesting biomass estimation is time-consuming and labor-intensive. Therefore, the spatial and temporal coverage through this method is limited. Crop models (such as APSIM) and remote sensing represent an alternative to predict crop growth and development, but several challenges remain to be solved before they can be used to estimate aboveground biomass. Dead standing biomass makes it difficult to estimate green biomass and total aboveground biomass using remote sensing, while crop models are not capable of predicting biomass at the paddock scale when the spatial variability is high within the same soil unit. The objective of this project is to develop aboveground biomass estimation models of forage resources in pastoral systems under different environmental and management conditions. Information provided by remote sensors (MODIS and Sentinel2) and field data for an annual (sorghum) and a perennial forage crop (tall wheatgrass - Thinopyrum ponticum) will be used to calibrate APSIM. The expected result of this work is the generation of scientific knowledge that allows overcoming the limitations imposed by each approach. In the short term, it is expected to have more precise aboveground biomass estimation with better spatial and temporal coverage, and in the long term to increase meat production and sustainability of livestock systems.
EPG-FAUBA University of Buenos Aires.
Dr Martin Oesterheld (primary supervisor), Dr Mariano Oyarzabal, Dr Gonzalo Irisarri and Dr Jonathan Ojeda
- Biomass estimation of forage resources through remote sensing and process-based crop models
- Estimation of aboveground biomass of a megathermic pasture (Setaria sphacelata) based on process-based crop models with different structure
- Multi-resolution analysis of aggregated spatial data to simulate yield and irrigation water demand at regional scales (oral presentation)
- Crop-livestock adaptation to climate change based on modelling and remote-sensing
- Effects of soil- and climate data aggregation on simulated potato yield and irrigation water requirement