University of Leicester
Rayner_2021_ECOLIND_EO_Ecosystem_Services.pdf (4.72 MB)

Effects of improved land-cover mapping on predicted ecosystem service outcomes in a lowland river catchment

Download (4.72 MB)
journal contribution
posted on 2022-01-14, 13:38 authored by M Rayner, H Balzter, L Jones, M Whelan, C Stoate
Reliable quantification of ecosystem service (ES) provision in agricultural landscapes depends on accurate mapping of the spatial configuration of land-use and land cover (LULC). In this paper we explore the benefits of enhanced spatial and thematic resolution in LULC mapping in terms of predicting ecosystem services and associated natural capital-based land-use policies. Copernicus Sentinel-2 satellite images were processed using Google Earth Engine (GEE) to generate a LULC map at 10 m resolution, which was compared to existing datasets at 20 m, 25 m, and 100 m resolution in the River Welland catchment (Eastern England). Spatial resolution had a significant effect on the abundance and spatial configuration of land cover types. For example, detected woodland cover in the finest resolution dataset was 2x that in the coarsest data. Finer spatial resolution also allowed small, fragmented patches of woodland and grassland to be identified. ES provision (crop yield, carbon storage and pollinator abundance) was estimated from each map using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The finest resolution map resulted in 21% lower predicted wheat production (due to lower estimates of cultivated land cover), 7% higher predicted carbon stocks and 43% higher predicted wild bee abundance compared to the coarsest resolution map. The estimated monetary value of ES provision increased by 23.2% between the 10 and 100 m dataset. We recommend that a LULC resolution of at least 10 m should be employed in agricultural landscapes to accurately capture ES provision. This can be achieved using GEE and could be used as a basis for the development of future natural capital policy.


Central England NERC Training Alliance (CENTA) Doctoral Training Partnership (Grant Reference: NE/ L002493/1). H. Balzter was partly supported by the NERC National Centre for Earth Observation (NCEO).



Max Rayner, Heiko Balzter, Laurence Jones, Mick Whelan, Chris Stoate, 'Effects of improved land-cover mapping on predicted ecosystem service outcomes in a lowland river catchment', Ecological Indicators, 133, 2021, 108463.

Author affiliation

School of Geography, Geology and the Environment; National Centre for Earth Observation


  • VoR (Version of Record)

Published in

Ecological Indicators






Elsevier BV



Acceptance date


Copyright date


Available date




Usage metrics

    University of Leicester Publications