Estimating Urban Evapotranspiration at 10m Resolution Using Vegetation Information from Sentinel-2: A Case Study for the Beijing Sponge City
Xuanze Zhang, Peilin Song
Abstract
Estimating accurately evapotranspiration (ET) in urban ecosystems is difficult due to the complex surface conditions and a lack of fine measurement of vegetation dynamics. To overcome such difficulties using recent developments of remote sensing technology, we estimate leaf area index (LAI) from Sentinel-2-based Normalized Difference Vegetation Index (NDVI) using the NDVI–LAI nonlinear relationship. By applying Sentinel-2-based LAI and land cover classification (LCC) to a carbon-water coupling model (PML-V2.1) with surface meteorological forcing data as input, we, for the first time, estimate monthly ET at 10m × 10m resolution for the Beijing Sponge City. Results show that for the whole sponge city during June 2018, the LAI, ET and gross primary productivity (GPP) are 0.83 m2 m−2, 1.6 mm d−1 and 2.8 gC m−2 d−1, respectively. For different LCCs, lakes and rivers have the highest ET (≥8 mm d−1), followed by mixed forests and croplands (ET is 4–6 mm d−1 and LAI is 2–3 m2 m−2) with dominant contribution (>80%) from plant transpiration, while grasslands (2–4 mm d−1) have 50–70% from transpiration due to smaller LAI (1~2 m2 m−2). The impervious surfaces occupying ~60% of the sponge city area, have the smallest ET (<2.0 mm d−1) in which interception evaporation by impervious surface contributes 20–30%, and transpiration from greenbelts (0.5–1.0 m2 m−2 of LAI) contributes 40–50%. These findings can provide a valuable scientific basis for policymaking and urban water use planning. This study proposes a Sentinel-2-based technology for estimating ET as a feasible framework to evaluate city-level hydrological dynamics in urban ecosystems.