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Three NASA-funded field campaigns have been hosted at the Howard University Research Campus in Beltsville, MD. In each of the years 2006, 2007 and 2008, WAVES field campaigns have coordinated ozonesonde launches, lidar operations and other measurements with A-train satellite overpasses for the purposes of satellite validation. The unique mix of measurement systems, physical location and the interagency, international group of researchers and students has permitted other objectives, such as mesoscale meteorological studies, to be addressed as well. We review the goals and accomplishments of the three WAVES missions with the emphasis on the nonsatellite validation component of WAVES, as the satellite validation activities have been reported elsewhere.

Most remote sensing estimations of vegetation variables such as Leaf Area Index (LAI), Absorbed Photosynthetically Active Radiation (APAR), and phytomass are made using broad band sensors with a bandwidth of approximately 100 nm. However, high resolution spectrometers are available and have not been fully exploited for the purpose of improving estimates of vegetation variables. A study directed to investigate the use of high spectral resolution spectroscopy for remote sensing estimates of APAR in vegetation canopies in the presence of nonphotosynthetic background materials such as soil and leaf litter is presented. A high spectral resolution method defined as the Chlorophyll Absorption Ratio Index (CARI) was developed for minimizing the effects of nonphotosynthetic materials in the remote estimates of APAR. CARI utilizes three bands at 550, 670, and 700 nm with bandwidth of 10 nm. Simulated canopy reflectance of a range of LAI were generated with the SAIL model using measurements of 42 different soil types as canopy background. CARI obtained from the simulated canopy reflectance was compared with the broad band vegetation indices (Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Simple Ratio (SR)). CARI reduced the effect of nonphotosynthetic background materials in the assessment of vegetation canopy APAR more effectively than broad band vegetation indices.

Field measurements of carbon dioxide and water vapor fluxes were analyzed in conjunction with reflectances obtained from a helicopter-mounted Modular Multiband Radiometer at a grassland study site during the First International Satellite Land Surface Climatology Project Field Experiment. These measurements are representative of the canopy scale and were made over a range of meteorological and soil moisture conditions during different stages in the annual life cycle of the prairie vegetation, and thus provide a good basis for investigating hpotheses/relationships potentially useful in remote sensing applications. We tested the hypothesis (Sellers, 1987) that the simple ratio vegetation index should be near-linearly related to the derivatives of the unstressed canopy stomatal conductance and the unstressed canopy photosynthesis with respect to photosynthetically active radiation. Even though there is some scatter in our data, the results seem to support this hypothesis.

Land surface reflectance measurements were obtained during the First ISLSCP Field Experiment (FIFE) field campaigns utilizing a variety of airborne and ground-based spectral radiometers. To study the validity of the assumption that the values obtained by the several different teams and instruments were interchangeable, the surface radiation measurement teams converged on a common site for one day during the fifth intensive field campaign in 1989. The bidirectional reflectances from the various instruments were basically found to be comparable.

A method for calculating surface energy balances is investigated which incorporates the vegetation index and/or other indicators of surface conductance at visible and near-IR channels. Data from the Konza Prairie are employed to confirm the hypothesized relationship between maximum canopy conductance and the observed simple-ratio vegetation index. The relationship is established, but more data regarding soil-surface contributions are required to estimate the total surface conductance to evapotranspiration.

The scattering dynamics of sparse vegetation canopies were studied within the framework of the three-dimensional radiative transfer model of Kimes (1984). The model was upgraded by including an algorithm for the anisotropic scattering of a soil boundary. Validation of the model was carried out using measured directional reflectance data for two canopies exhibiting typical scattering behavior with low and intermediate vegetation density. The canopies were: an orchard grass canopy; and a hard wheat canopy. A number of factors were found contributing to the final reflectance distribution of the canopies, including: (1) the strong anisotropic scattering properties of the soil; (2) the geometric effect of the vegetation probability gap function on the soil anisotropy and solar irradiance; and (3) the anisotropic scattering of vegetation which is controlled by the phase function and the layering of leaves. The application of the theoretical results to the development of earth-observing sensor systems is discussed.

A simple equation has been developed for describing the bidirectional reflectance of some vegetative canopies and bare soil surfaces. The equation describes directional reflectance as a function of zenith and azimuth view angles and solar azimuth angle. The equation works for simulated and field measured red and IR reflectance under clear sky conditions. Hemispherical reflectance can be calculated as a function of the simple equation coefficients by integrating the equation over the hemisphere of view angles. A single equation for estimating soil bidirectional reflectance was obtained using the relationships between solar zenith angles and the simple equation coefficients for medium and rough soil distributions. The equation has many useful applications such as providing a lower level boundary condition in complex plant canopy models and providing an additional tool for studying bidirectional effects on pointable sensors.

An important part of fundamental remote sensing research is based on the measurement and analysis of spectral reflectance from earth surface materials in situ. It has been found that for an effective analysis of the target of interest, different applications of remotely sensed data require spectral measurements from different portions of the electromagnetic spectrum. It is pointed out that the detailed spectral reflectance characteristics of forest vegetation are currently not well understood, particularly in the middle infrared wavelength region. Details regarding the need for in situ forest canopy measurements are examined, taking into account certain difficulties arising in the case of satellite observations. Because of these difficulties, the present paper provides a discussion of methodology and preliminary spectra based on an experiment to use a helicopter as an observing platform for in situ forest canopy spectra measurement.

The design of a high resolution, field portable spectrometer system is presented. The system provides the spectral resolution previously available only with laboratory based systems. The system's portability allows for essential in situ measurements, provides rapid acquisition and calibration of spectral reflectance data over a wavelength band from about 300 to 1000 nm. Features include a calibration scheme for normalizing data to the incident radiation, and the injection of a spectral calibration signal. Laboratory tests indicate that the system will perform as expected, and plans are being made to integrate the system with a ground based active and passive microwave data acquisition system.

Procedures used to map residential land cover on the Orlando, Florida, Urban fringe zone are detailed. The NASA Bureau of the Census Applications Systems Verification and Transfer project and the test site are described as well as the LANDSAT data used as the land cover information sources. Both single-date LANDSAT data processing and multitemporal principal components LANDSAT data processing are described. A summary of significant findings is included.