A simple filtered photodiode instrument for continuous measurement of narrowband NDVI and PRI over vegetated canopies

Abstract Recent advances in understanding relationships between spectral reflectance of vegetation canopies and the structural and physiological drivers of canopy-atmosphere carbon dioxide exchange highlight the potential for using narrowband spectral vegetation indices to spatially scale CO 2 fluxes beyond the area of a tower footprint. However, ground reference observations of narrowband spectral reflectance in support of satellite observations can be challenging to obtain because (1) automated sampling of both upwelling and downwelling radiation is required over extended time periods to characterize diurnal and seasonal variability, (2) hyperspectral spectroradiometer data and hardware can be sensitive to environmental factors such as temperature and moisture, and (3) hyperspectral spectroradiometers are expensive, greatly limiting prospects for widespread automated sampling. We have therefore developed the QuadPod: a simple, lightweight, relatively low cost and low power sensor capable of continuously measuring upwelling and downwelling radiation in 10 nm wavebands centered at 532 nm, 568 nm, 676 nm, and 800 nm. QuadPod measurements can be combined to calculate spectral reflectance indices (e.g., the photochemical reflectance index, PRI; and the normalized difference vegetation index, NDVI) useful for modeling canopy-atmosphere carbon exchange. The basic QuadPod instrument design described here can be implemented using any combination of optical filters in order to calculate other spectral vegetation indices.

[1]  J. Maranville,et al.  Photosynthesis Light Sensor and Meter , 1971 .

[2]  N. Coops,et al.  Instrumentation and approach for unattended year round tower based measurements of spectral reflectance , 2007 .

[3]  Christopher B. Field,et al.  Remote sensing of the xanthophyll cycle and chlorophyll fluorescence in sunflower leaves and canopies , 1990, Oecologia.

[4]  Andrew D Richardson,et al.  Near-surface remote sensing of spatial and temporal variation in canopy phenology. , 2009, Ecological applications : a publication of the Ecological Society of America.

[5]  W. Oechel,et al.  FLUXNET: A New Tool to Study the Temporal and Spatial Variability of Ecosystem-Scale Carbon Dioxide, Water Vapor, and Energy Flux Densities , 2001 .

[6]  T. A. Black,et al.  A MODIS-derived photochemical reflectance index to detect inter-annual variations in the photosynthetic light-use efficiency of a boreal deciduous forest , 2005 .

[7]  Thomas Hilker,et al.  Effects of mutual shading of tree crowns on prediction of photosynthetic light-use efficiency in a coastal Douglas-fir forest. , 2008, Tree physiology.

[8]  Growth and Reproductive Allocation of Adenocaulon Bicolor Following Experimental Removal of Sunflecks , 1992 .

[9]  C. B. Tanner,et al.  Sensors for Measuring Light Available for Photosynthesis , 1966 .

[10]  John A. Gamon,et al.  Assessing leaf pigment content and activity with a reflectometer , 1999 .

[11]  John A. Gamon,et al.  Mapping carbon and water vapor fluxes in a chaparral ecosystem using vegetation indices derived from AVIRIS , 2006 .

[12]  P. Sellers Canopy reflectance, photosynthesis, and transpiration. II. the role of biophysics in the linearity of their interdependence , 1987 .

[13]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[14]  J. Monteith SOLAR RADIATION AND PRODUCTIVITY IN TROPICAL ECOSYSTEMS , 1972 .

[15]  C. Wessman,et al.  Photosynthetically active radiation heterogeneity within a monodominant Congolese rain forest canopy , 2000 .

[16]  A Low-Cost Sensor for Measuring Spatiotemporal Variation of Light Intensity on the Streambed , 2003, Journal of the North American Benthological Society.

[17]  John A. Gamon,et al.  A mobile tram system for systematic sampling of ecosystem optical properties , 2006 .

[18]  Nicholas C. Coops,et al.  MODIS spectral signals at a flux tower site: Relationships with high-resolution data, and CO2 flux and light use efficiency measurements , 2006 .

[19]  Mark D. Schwartz,et al.  Monitoring global change with phenology: The case of the spring green wave , 1994 .

[20]  T. A. Black,et al.  Remote sensing of photosynthetic-light-use efficiency of boreal forest , 2000 .

[21]  Edward J. Milton,et al.  Calibration of dual‐beam spectroradiometric data , 2006 .

[22]  N. Coops,et al.  A multi-angle spectrometer for automatic measurement of plant canopy reflectance spectra , 2006 .

[23]  W. Oechel,et al.  A new model of gross primary productivity for North American ecosystems based solely on the enhanced vegetation index and land surface temperature from MODIS , 2008 .

[24]  Dar A. Roberts,et al.  Modeling spatially distributed ecosystem flux of boreal forest using hyperspectral indices from AVIRIS imagery , 2001 .

[25]  J. Peñuelas,et al.  Estimation of plant water concentration by the reflectance Water Index WI (R900/R970) , 1997 .

[26]  A simple red:far-red sensor using gallium arsenide phosphide detectors , 1996 .

[27]  D. Sims,et al.  Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages , 2002 .

[28]  C. Justice,et al.  Validating MODIS Terrestrial Ecology Products: Linking In Situ and Satellite Measurements , 1999 .

[29]  Maosheng Zhao,et al.  A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production , 2004 .

[30]  M. Schildhauer,et al.  Spectral Network (SpecNet)—What is it and why do we need it? , 2006 .

[31]  Karl Fred Huemmrich,et al.  High temporal resolution NDVI phenology from micrometeorological radiation sensors , 1999 .

[32]  T. Painter,et al.  Reflectance quantities in optical remote sensing - definitions and case studies , 2006 .

[33]  N. Coops,et al.  Multi-Angle Remote Sensing of Forest Light Use Efficiency , 2007 .

[34]  K. Hibbard,et al.  A Global Terrestrial Monitoring Network Integrating Tower Fluxes, Flask Sampling, Ecosystem Modeling and EOS Satellite Data , 1999 .

[35]  C. Field,et al.  A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency , 1992 .

[36]  M. A. Wolf,et al.  Portable monitor for solar radiation that accumulates irradiance histograms for 32 leaf-mounted sensors , 1985 .

[37]  Hans Peter Schmid,et al.  Potential of MODIS ocean bands for estimating CO2 flux from terrestrial vegetation: A novel approach , 2004 .

[38]  S. Wofsy,et al.  Midday values of gross CO2 flux and light use efficiency during satellite overpasses can be used to directly estimate eight-day mean flux , 2005 .

[39]  B. Bond,et al.  A micro-power precision amplifier for converting the output of light sensors to a voltage readable by miniature data loggers. , 1999, Tree physiology.

[40]  W. Oechel,et al.  Parallel adjustments in vegetation greenness and ecosystem CO2 exchange in response to drought in a Southern California chaparral ecosystem , 2006 .

[41]  Lee A. Vierling,et al.  Differences in arctic tundra vegetation type and phenology as seen using bidirectional radiometry in the early growing season , 1997 .

[42]  Elizabeth M. Middleton,et al.  Regional mapping of gross light-use efficiency using MODIS spectral indices , 2008 .

[43]  A. Viña,et al.  Remote estimation of leaf area index and green leaf biomass in maize canopies , 2003 .

[44]  T. A. Black,et al.  Separating physiologically and directionally induced changes in PRI using BRDF models , 2008 .