Remote sensing of LAI, chlorophyll and leaf nitrogen pools of crop- and grasslands in five European landscapes

[摘要] Leaf nitrogen and leaf surface area influence the exchange of gases betweenterrestrial ecosystems and the atmosphere, and play a significant role in theglobal cycles of carbon, nitrogen and water. The purpose of this study is touse field-based and satellite remote-sensing-based methods to assess leafnitrogen pools in five diverse European agricultural landscapes located inDenmark, Scotland (United Kingdom), Poland, the Netherlands and Italy.REGFLEC (REGularized canopy reFLECtance) is an advanced image-based inversecanopy radiative transfer modelling system which has shown proficiency forregional mapping of leaf area index (LAI) and leaf chlorophyll(CHL_l) using remote sensing data. In this study, high spatialresolution (10–20 m) remote sensing images acquired from the multispectralsensors aboard the SPOT (Satellite For Observation of Earth) satellites wereused to assess the capability of REGFLEC for mapping spatial variations inLAI, CHL_land the relation to leaf nitrogen (N_l) datain five diverse European agricultural landscapes. REGFLEC is based onphysical laws and includes an automatic model parameterization scheme whichmakes the tool independent of field data for model calibration. In thisstudy, REGFLEC performance was evaluated using LAI measurements andnon-destructive measurements (using a SPAD meter) of leaf-scaleCHL_l and N_l concentrations in 93 fields representingcrop- and grasslands of the five landscapes. Furthermore, empiricalrelationships between field measurements (LAI, CHL_l andN_l and five spectral vegetation indices (the NormalizedDifference Vegetation Index, the Simple Ratio, the Enhanced VegetationIndex-2, the Green Normalized Difference Vegetation Index, and the greenchlorophyll index) were used to assess field data coherence and to serve as acomparison basis for assessing REGFLEC model performance. The fieldmeasurements showed strong vertical CHL_l gradient profiles in26% of fields which affected REGFLEC performance as well as therelationships between spectral vegetation indices (SVIs) and fieldmeasurements. When the range of surface types increased, the REGFLEC resultswere in better agreement with field data than the empirical SVI regressionmodels. Selecting only homogeneous canopies with uniform CHL_ldistributions as reference data for evaluation, REGFLEC was able to explain69% of LAI observations (rmse = 0.76), 46% of measured canopychlorophyll contents (rmse = 719 mg m⁻²) and 51% of measuredcanopy nitrogen contents (rmse = 2.7 g m⁻²). Better results wereobtained for individual landscapes, except for Italy, where REGFLEC performedpoorly due to a lack of dense vegetation canopies at the time of satelliterecording. Presence of vegetation is needed to parameterize the REGFLECmodel. Combining REGFLEC- and SVI-based model results to minimize errors fora "snap-shot" assessment of total leaf nitrogen pools in the fivelandscapes, results varied from 0.6 to 4.0 t km⁻². Differences in leafnitrogen pools between landscapes are attributed to seasonal variations,extents of agricultural area, species variations, and spatial variations innutrient availability. In order to facilitate a substantial assessment ofvariations in N_l pools and their relation to landscape basednitrogen and carbon cycling processes, time series of satellite data areneeded. The upcoming Sentinel-2 satellite mission will provide new multiplenarrowband data opportunities at high spatio-temporal resolution which areexpected to further improve remote sensing capabilities for mapping LAI,CHL_l and N_l.

[学科分类] 地球化学与岩石