Normalized difference spectral indices for estimating photosynthetic efficiency and capacity at a canopy scale derived from hyperspectral and CO2 flux measurements in rice
نویسندگان
چکیده
We explored simple and useful spectral indices for estimating photosynthetic variables (radiation use efficiency and photosynthetic capacity) at a canopy scale based on seasonal measurements of hyperspectral reflectance, ecosystem CO2 flux, and plant and micrometeorological variables. An experimental study was conducted over the simple and homogenous ecosystem of an irrigated rice field. Photosynthetically active radiation absorbed by the canopy (APAR), the canopy absorptivity of APAR (fAPAR), net ecosystem exchange of CO2 (NEECO2) gross primary productivity (GPP), photosynthetic capacity at the saturating APAR (Pmax), and three parameters of radiation use efficiency (εN: NEECO2/APAR; εG: GPP/APAR; φ: quantum efficiency) were derived from the data set. Based on the statistical analysis of relationships between these ecophysiological variables and reflectance indicators such as normalized difference spectral indices (NDSI[i,j]) using all combinations of two wavelengths (i and j nm), we found several new indices that would were more effective than conventional spectral indices such as photochemical reflectance index (PRI) and normalized difference vegetation index (NDVI=NDSI[near-infrared, red]). εG was correlated well with NDSI[710, 410], NDSI[710, 520], and NDSI[530, 550] derived from nadir measurements. φ was best correlated with NDSI[450, 1330]. NDSI[550, 410] and NDSI[720, 420] had a consistent linear relationships with fAPAR throughout the growing season, whereas conventional indices such as NDVI showed very different relationships before and after heading. Off-nadir measurements were more closely related to the efficiency parameters than nadir measurements. Our results provide useful insights for assessing plant productivity and ecosystem CO2 exchange, using a wide range of available spectral data as well as useful information for designing future sensors for ecosystem observations. © 2007 Elsevier Inc. All rights reserved.
منابع مشابه
Evaluating Hyperspectral Vegetation Indices for Leaf Area Index Estimation of Oryza sativa L. at Diverse Phenological Stages
Hyperspectral reflectance derived vegetation indices (VIs) are used for non-destructive leaf area index (LAI) monitoring for precise and efficient N nutrition management. This study tested the hypothesis that there is potential for using various hyperspectral VIs for estimating LAI at different growth stages of rice under varying N rates. Hyperspectral reflectance and crop canopy LAI measuremen...
متن کاملPredicting CO2 flux with hyperspectral reflectance
Predicting landscape-scale CO2 flux at a pasture and rice paddy with long-term hyperspectral canopy reflectance measurements J. H. Matthes, S. H. Knox, C. Sturtevant, O. Sonnentag, J. Verfaillie, and D. Baldocchi Dept. Geography, Dartmouth College, 6017 Fairchild, Hanover, NH, USA Dept. Environmental Science, Policy, and Management, University of California – Berkeley, Berkeley, CA, USA Dépt. G...
متن کاملDeriving a light use efficiency estimation algorithm using in situ hyperspectral and eddy covariance measurements for a maize canopy in Northeast China
We estimated the light use efficiency (LUE) via vegetation canopy chlorophyll content (CCCcanopy) based on in situ measurements of spectral reflectance, biophysical characteristics, ecosystem CO 2 fluxes and micrometeorological factors over a maize canopy in Northeast China. The results showed that among the common chlorophyll-related vegetation indices (VIs), CCCcanopy had the most obviously e...
متن کاملProgress in Remote Sensing of Photosynthetic Activity over the Amazon Basin
Although quantifying the massive exchange of carbon that takes place over the Amazon Basin remains a challenge, progress is being made as the remote sensing community moves from using traditional, reflectance-based vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), to the more functional Photochemical Reflectance Index (PRI). This new index, together with satellite-d...
متن کاملHigh density biomass estimation: Testing the utility of Vegetation Indices and the Random Forest Regression algorithm
Accurate estimates of wetland above ground biomass (AGB) have increasingly been identified as a critical component for an efficient wetland monitoring and management system. Multispectral remote sensing based indices have proven inadequate in estimating biomass especially at high canopy density. In this study we investigated the use of vegetation indices derived from field hyperspectral data to...
متن کامل