Mapping managed grassland ecosystem from space and modelling. By Ramesh Ningthoujam

Monitoring of grassland management in long-term ecological experiments (LTEs) at an ecosystem level is necessary due to potential impacts on biomass production in response to climate change. Knowledge gaps remain about how grasses with different nutrients and management affected the leaf chlorophyll content (CC) and intrinsic photosynthetic capacity (maximum carboxylation rate: Vcmax) in grassland ecosystem. Though space-borne optical remote sensing data are employed, it is not yet known how varying grass management affect vegetation indices (VIs) for productivity estimation via spatially and temporally CC, LAI and Vcmax. A better understanding of how fertilisation and management to remote sensing might assist in monitoring the large-scale grassland ecosystems in a repetitive and non-destructive manner.


In May 2019, the Ecological Continuity Trust announced that Imperial College London is to receive £1,710 to carry out a 7 month project “Quantifying grass chlorophyll content, leaf area index and productivity relationship” to Dr Ramesh Ningthoujam, Prof. Colin Prentice and Prof. Mick Crawley ( The project will produce new data syntheses comprising of plot data (SPAD-502, LI-COR), PROSPECT model, satellite-derived and P-model outputs. This applies to the current medium resolutions Landsat 8 Operational Land Imaging (OLI), Sentinel-2 Multispectral Imaging (MSI) and upcoming hyperspectral missions. Currently, most vegetation models and satellite based used to predict the net primary productivity (NPP) of grassland only consider the light-used efficiency concept. They only accounted for very limited differences in how grasses of varying fertilization and management respond to grass CC, LAI and Vcmax. The inclusion of fertiliser manipulated leaf photosynthetic properties (CC, LAI, Vcmax) derived from OLI/ MSI in vegetation models will provide better estimation of NPP of managed grassland ecosystem. So the ultimate goal is to provide the important management processes based on spatially and temporally derived chlorophyll content, LAI, Vcmax and nitrogen nutrient in particular to changing NPP and species diversity, to enable more accurate predictions of how managed grassland will respond to future climatic factors.


The project progress will be available at the ECT website via



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