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|Title:||High Resolution Field Spectroscopy Measurements for Estimating Gross Ecosystem Production in a Rice Field|
|Authors:||ROSSINI Micol; MERONI Michele; MIGLIAVACCA MIRCO; MANCA Giovanni; COGLIATI Sergio; BUSETTO Lorenzo; PICCHI Valentina; CESCATTI Alessandro; SEUFERT Guenther; COLOMBO Roberto|
|Citation:||AGRICULTURAL AND FOREST METEOROLOGY vol. 150 no. 9 p. 1283-1296|
|Publisher:||ELSEVIER SCIENCE BV|
|Type:||Articles in periodicals and books|
|Abstract:||This study investigates the possibility of monitoring carbon fixation of a terrestrial ecosystem from high spectral resolution field spectroscopy measurements. Canopy radiance spectra were collected under clear sky conditions using high resolution spectrometers which made it possible to estimate sun-induced chlorophyll fluorescence at the oxygen absorption band O2-A located at 760 nm (F760) as well as spectral vegetation indices. Spectral observations were collected in a rice field monitored with an eddy covariance (EC) flux tower continuously measuring the net ecosystem exchange (NEE) of the crop. Estimation of gross ecosystem productivity (GEP) from remotely sensed data was based on the widely used light-use efficiency model (LUE), which states that carbon uptake is a function of the photosynthetically active radiation absorbed by vegetation (APAR) and light-use efficiency (e) which represents the conversion efficiency of energy to fixed carbon. Hyperspectral data were used to derive both the APAR and the e term. Different versions of the LUE model were formalized and tested on EC fluxes during two growing seasons. We started using a LUE model in which e is held constant and remote sensing data are used to estimate APAR. We then investigated the improvements in GEP modelling provided by the partitioning between photosynthetic (PV) and non-photosynthetic (NPV) components of vegetation in APAR estimation, holding e constant. The use of spectral indices related to APARPV instead of APAR resulted in an improvement in midday GEP estimation of about 50% with respect to the basic LUE model, root mean square error in cross-validation (RMSEcv) from 8.5 to 4.5 µmol CO2 m-2 s-1. Afterwards, we tested the use of the apparent fluorescence yield (Fy*760) and the scaled Photochemical Reflectance Index (sPRI) to derive e. Modeling e improved the estimation of GEP and provided an RMSEcv of 3.8 and 3.7 µmol CO2 m-2 s-1 using Fy*760 and sPRI, respectively. This research compares GEP estimation accuracy of various remote sensing indices, including for the first time sun-induced fluorescence estimated with very high spectral resolution.|
|JRC Institute:||Sustainable Resources|
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