1. Grazed biomass was estimated via satellite images more reliable than mowed biomass
Péter Koncz1,*, András Gubányi2, Bernadett Gecse3, Márton Tolnai3, Krisztina Pintér1, Péter Kertész3, Szilvia Fóti1, János Balogh3, Zoltán Nagy1,3
1MTA‒SZIE Plant Ecology Research Group, Szent István University, Páter u. 1, 2100 Gödöllő, Hungary
2 Hungarian Natural History Museum, Baross u. 13., 1088 Budapest, Hungary
3Szent István University, Institute of Botany and Ecophysiology, Páter K. u. 1., 2100 Gödöllő, Hungary
Landsat/usgs.gov
Why?
Sustainable grassland-based meat production requires precise estimation of the available and the harvested amount of biomass. Remote sensing could be a tool for this, however the correlation between the measured and the estimated biomass based on remote sensing is often weak.
What?
We tested the reliability of biomass estimation based on remote sensing under different plant (living vs. senescent and management (grazing vs. mowing) conditions.
Grazed
Mowed
Results
1) The correlation between the green biomass and NDVI was stronger than between the total (green and dry, senescent) biomass and NDVI (Fig 1).
Fig 1. NDVI vs. total (a) and green (b) biomass
How?
Biomass was measured 2-3 weekly in adjacent grazed (0.6 livestock ha-1) and mowed (cut once per year) semi-arid grassland sample sites (1 ha, Hungary). Biomass was separated into green and yellow, brown (senescent parts).
Remote sensed normalized difference vegetation index (NDVI) was obtained from Landsat 7 and 8 satellites for the total area (>500 ha).
Regression between the measured biomass and NDVI was used to estimate the biomass of the total area.
Biomass differences (based on NDVI) before and after grazing and mowing events were compared to the estimated grazed (based on animal dry matter uptake) and mowed biomass (weight of the harvested hay) (Koncz et al 2016).
2) The estimated grazed biomass based on NDVI differences (after and before grazing) was in close agreement with the estimated grazed biomass based on dry matter uptake of the animals. However, the amount of mowed biomass was poorly estimated based on NDVI differences (after and before mowing) (Fig 2).
So, what?
Grassland management practices influence the predictability of biomass estimation based on NDVI. Frequent NDVI data (i.e. data close to management events) could increase the predictability of biomass ased on remote sensing.
Fig 2. NDVI-based vs. estimated grazed and mowed biomass
Reference
Koncz, P. et al. (2017) Extensive grazing in contrast to mowing is climate friendly based on the farm–scale greenhouse gas balance. Agriculture, Ecosystems and Environment, 240, 121–134
Thanks to: AnimalChange EU-FP7 program ( MTA‒SZIE Plant Ecology Research Group