Satellite remote sensing of surface energy balance : success, failures, and unresolved issues in FIFE

The FIFE staff science group, consisting of the authors, developed and evaluated process models relating surface energy and mass flux, that is, surface rates, to boundary layer and surface biophysical characteristics, that is, surface states. In addition, we developed and evaluated remote sensing algorithms for inferring surface state characteristics. In this paper we report the results of our efforts. We also look in detail at the sensor and satellite platform requirements (spatial resolution and orbital requirements) as driven by surface energy balance dynamics and spatial variability. We examine also the scale invariance of the process models and remote sensing algorithms, that is, to what degree do the remotely sensed parameters and energy balance relations translate from the patch level where they were developed to the mesoscale level where they are required? Finally, we examine the atmospheric correction and calibration issues involved in extending the remotely sensed observations within a season and between years. From these investigations we conclude that (1) existing formulations for the radiation balance and latent heat components of the surface energy balance equation are valid at the patch level. (2) Many of the surface physiological characteristics that parameterize these formulations can be estimated using satellite remote sensing at both local and regional scales; a few important ones cannot. (3) The mathematical structures relating radiation and surface energy flux to remote sensing parameters are, for the most part, scale invariant over the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) study area. The conditions for scale invariance are derived. (4) The precision of satellite remote sensing estimates of surface reflectance, calibrated and corrected for atmospheric effects, is no worse than about 1% absolute. The errors may actually be smaller, but an upper bound of 1% results from sampling variance caused by differences among the satellite and ground sensors in spatial resolution, atmospheric effects, and calibration. (5) Afternoon cumulus in the study area required both the Landsat and the SPOT satellites for monitoring of the vegetation dynamics. This result implies the need for multiple polar orbiters, or geosynchronous satellites in an operational implementation. We found that canopy Fpar, the fraction of incident photosynthetically active radiation absorbed by a canopy, can be estimated with an error of about 10% using remote sensing, provided that regional variability in the reflectance of the canopy substrate is dealt with properly. We also found that spectral vegetation indices (VIs) respond primarily to the photosynthetically active radiation absorbed by the live or green component of the canopy as opposed to its necrotic or dead vegetation. This is of critical importance since radiation absorption by the live part of the canopy is the rate-limiting process for photosynthesis and other key process rates such as evaporation. We found for the FIFE study area the surface moisture content at O to 10 cm to be another key rate-limiting variable in photosynthesis and evaporation. At gravimetric soil moisture levels below 20%, photosynthesis and evaporation were strongly attenuated. Only microwave sensors have shown potential for satellite remote sensing of soil moisture and only in the top few centimeters. Hydrological models may also play a critical role in monitoring root zone soil moisture levels, but additional research is needed. From our review of the research of others in FIFE we conclude that downwelling shortwave radiation and surface albedo are also amenable to remote sensing. Unfortunately, from our research we also found that the remote estimation of surface temperature to useful accuracies is problematical; consequently, the use of thermal infrared measurements to infer sensible heat flux is probably not feasible to acceptable accuracies.

[1]  D. M. Gates,et al.  Spectral Properties of Plants , 1965 .

[2]  M. M. Schreiber,et al.  Reflectance and internal structure of leaves from several crops during a growing season. , 1971 .

[3]  T. Hsiao.  Plant Responses to Water Stress , 1973 .

[4]  P. Jarvis.  The Interpretation of the Variations in Leaf Water Potential and Stomatal Conductance Found in Canopies in the Field , 1976 .

[5]  R. Kauth,et al.  The tasselled cap - A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat , 1976 .

[6]  F. X. Kneizys,et al.  Atmospheric transmittance/radiance: Computer code LOWTRAN 5 , 1978 .

[7]  J. Dave.  Extensive datasets of the diffuse radiation in realistic atmospheric models with aerosols and common absorbing gases , 1978 .

[8]  C. Tucker.  Remote sensing of leaf water content in the near infrared , 1980 .

[9]  P. A. Murtha,et al.  Development and testing of a method of estimating sensible heat flux from natural surfaces using remotely sensed surface temperatures , 1981 .

[10]  E. R. Stoner,et al.  Characteristic variations in reflectance of surface soils , 1981 .

[11]  J. A. Burgess,et al.  Performance Evaluation And Calibration Of A Modular Multiband Radiometer For Remote Sensing Field Research , 1982, Optics & Photonics.

[12]  B. Séguin,et al.  Using midday surface temperature to estimate daily evaporation from satellite thermal IR data , 1983 .

[13]  W. Verhoef.  Light scattering by leaf layers with application to canopy reflectance modelling: The SAIL model , 1984 .

[14]  Jerry L. Hatfield,et al.  Intercepted photosynthetically active radiation estimated by spectral reflectance , 1984 .

[15]  G. Asrar,et al.  Estimating Absorbed Photosynthetic Radiation and Leaf Area Index from Spectral Reflectance in Wheat1 , 1984 .

[16]  P. Sellers.  Canopy reflectance, photosynthesis and transpiration , 1985 .

[17]  R. Fraser,et al.  The Relative Importance of Aerosol Scattering and Absorption in Remote Sensing , 1985, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Richard L. Thompson,et al.  Optimal solar/viewing geometry for an accurate estimation of leaf area index and leaf angle distribution from bidirectional canopy reflectance data , 1985 .

[19]  S. Idso,et al.  An analysis of infrared temperature observations over wheat and calculation of latent heat flux , 1986 .

[20]  D. Vidal-Madjar,et al.  Evaluation of a Surface/Vegetation Parameterization Using Satellite Measurements of Surface Temperature , 1986 .

[21]  G. Asrar,et al.  Light Interception and Leaf Area Estimates from Measurements of Grass Canopy Reflectance , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[22]  J. L. Barker,et al.  Landsat MSS and TM post-calibration dynamic ranges , 1986 .

[23]  Bhaskar J. Choudhury,et al.  Relationships between vegetation indices, radiation absorption, and net photosynthesis evaluated by a sensitivity analysis , 1987 .

[24]  B. Markham,et al.  Radiometric properties of U.S. processed Landsat MSS data , 1987 .

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

[26]  P. Sellers.  Relations between canopy reflectance, photosynthesis and transpiration - Links between optics, biophysics and canopy architecture , 1987 .

[27]  Yoram J. Kaufman,et al.  Atmospheric effect on spectral signature-measurements and corrections , 1988 .

[28]  B. Rock,et al.  Detection of changes in leaf water content using Near- and Middle-Infrared reflectances , 1989 .

[29]  Susan L. Ustin,et al.  Anisotropy of thermal infrared exitance in sunflower canopies , 1989 .

[30]  W. James Shuttleworth,et al.  Calibrating the Simple Biosphere Model for Amazonian Tropical Forest Using Field and Remote Sensing Data. Part I: Average Calibration with Field Data , 1989 .

[31]  P. Deschamps,et al.  Description of a computer code to simulate the satellite signal in the solar spectrum : the 5S code , 1990 .

[32]  F. Hall,et al.  Use of narrow-band spectra to estimate the fraction of absorbed photosynthetically active radiation , 1990 .

[33]  Robert Frouin,et al.  Satellite estimates of downwelling longwave irradiance at the surface during FIFE , 1990 .

[34]  Robert Frouin,et al.  Variability of photosynthetically available and total solar irradiance at the surface during FIFE - A satellite description , 1990 .

[35]  U. Wegmüller.  The effect of freezing and thawing on the microwave signatures of bare soil. , 1990 .

[36]  Alan K. Knapp,et al.  Physiological Interactions Along Resource Gradients in a Tallgrass Prairie , 1991 .

[37]  Charles L. Walthall,et al.  Estimation of Shortwave Hemispherical Reflectance (Albedo) from Bidirectionally Reflected Radiance Data , 1991 .

[38]  James R. Wang,et al.  Satellite remote sensing of surface energy and mass balance - Results from FIFE , 1991 .

[39]  G. Collatz,et al.  Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer , 1991 .

[40]  S. Goetz,et al.  Radiometric rectification - Toward a common radiometric response among multidate, multisensor images , 1991 .

[41]  B. L. Blad,et al.  Estimation of sensible heat flux from remotely sensed canopy temperatures , 1992 .

[42]  Charles L. Walthall,et al.  Prairie grassland bidirectional reflectances measured by different instruments at the FIFE site , 1992 .

[43]  J. I. MacPherson,et al.  Spatial and temporal variations of the fluxes of carbon dioxide and sensible and latent heat over the FIFE site , 1992 .

[44]  C. Field,et al.  A reanalysis using improved leaf models and a new canopy integration scheme , 1992 .

[45]  James R. Wang,et al.  Active and passive microwave measurements of soil moisture in FIFE , 1992 .

[46]  E. Walter-Shea,et al.  Biophysical properties affecting vegetative canopy reflectance and absorbed photosynthetically active radiation at the FIFE site , 1992 .

[47]  Piers J. Sellers,et al.  Relations between surface conductance and spectral vegetation indices at intermediate (100 m2 to 15 km2) length scales , 1992 .

[48]  J. Norman,et al.  Leaf gas exchange of Andropogon gerardii Vitman, Panicum virgatum L., and Sorghastrum nutans (L.) Nash in a tallgrass prairie , 1992 .

[49]  Brian L. Markham,et al.  Overview of atmospheric correction and radiometric calibration efforts during FIFE , 1992 .

[50]  Variation in energy balance components from six sites in a native prairie for three years , 1992 .

[51]  R. Dubayah.  Estimating net solar radiation using Landsat Thematic Mapper and digital elevation data , 1992 .

[52]  M. Spanner,et al.  Atmospheric correction of remotely sensed image data by a simplified model , 1992 .

[53]  S. Goward,et al.  Vegetation canopy PAR absorptance and the normalized difference vegetation index - An assessment using the SAIL model , 1992 .

[54]  Y. Kaufman,et al.  Algorithm for atmospheric corrections of aircraft and satellite imagery , 1992 .

[55]  Piers J. Sellers,et al.  Remote sensing of the land biosphere and biogeochemistry in the EOS era: science priorities, methods and implementation—EOS land biosphere and biogeochemical cycles panels , 1993 .