A means by which measurements of the optical properties of crops and soils can be knowledgeably compared from site to site and instrument to instrument is presented in detail. The definition of bidirectional reflectance factor is reviewed and discussed.Procedures for field implementation are illustrated and discussed.Spectral and goniometric properties of laboratory and field reference surfaces are given.It is concluded that intelligent use of the bidirectional reflectance factor technique is an accurate and practical means to obtain the spectral, optical properties of crops and soils needed for advancements in agricultural remote sensing.

Using polarization measurements, the reflectance factor R(theta(i),phi(i),theta(r),phi(r)) of two wheat canopies is divided into components due to specularly and diffusely reflected light. The data show that two key angles may be predicted, the angle of the polarizer for minimum flux and the angle of incidence of sunlight specularly reflected by a leaf to a sensor. The results show that specular reflection is a key aspect to radiation transfer by two canopies. Results suggest that the advent of heading in wheat may be remotely sensed from polarization measurements of the canopy reflectance.

Spectral responses of two glaciated soils, Chalmers silty clay loam and Fincastle silt loam, formed under prairie grass and forest vegetation, respectively, were measured both in the laboratory under controlled moisture equilibria, and in the field under various moisture and crop residue conditions. An Exotech Model 20C spectroradiometer was used to obtain spectral data in the laboratory under artificial illumination. Reflectance measurements ranged from 0.52‐to 2.32‐µm in 0.01µm increments. Asbestos tension tables were used to maintain a 0.10‐bar moisture equilibrium following saturation of crushed, sieved soil samples. The same spectroradiometer was used outdoors under solar illumination to obtain spectral response from dry and moistened field plots with and without corn residue cover, representing the two different soils. Results indicate that laboratory‐measured spectra of moist soil are directly proportional to the spectral response of that same field‐measured moist bare soil over the 0.52‐ to 1.75‐µm wavelength range. The magnitudes of difference in spectral response between identically treated Chalmers and Fincastle soils are greatest in the 0.6‐to 0.8‐µm transition region between the visible and near infrared, regardless of field condition or laboratory preparation studied.

Leaves have a major influence on canopy reflectance when they constitute the main spatial component in a vegetative canopy. Near normal‐incidence, directional‐hemispherical reflectance and transmittance of in situ individual leaves of soybean (Glycine max., Merr.) and corn (Zea mays, L.) were characterized as a function of wavelengths and growth. Spectral properties were measured in seven wavebands with an integrating sphere and prototype radiometer unit. Individual leaves periodically were monitored from emergence and unfolding through 47 d in soybean and 77 d in corn. Visible reflectance and transmittance decreased in soybean as leaves expanded, but increased after full leaf expansion. An opposite pattern was observed with soybean near‐infrared radiation (NIR) reflectance. Spectral properties varied little in mid‐ and upper‐canopy corn leaves with the exception of the green spectral region. Near constant values were attributed to the fact that corn leaves are fully expanded by the time they have fully emerged. Reflectance and transmittance properties of adaxial and abaxial surfaces differed by as much as an absolute 5% in soybeans while there were essentially no differences in corn. Differences in surface reflectance and transmittance in soybean were attributed to the dorsiventral morphology of soybean leaves. Reflectance and transmittance from adaxial and abaxial leaf surfaces may have to be considered in modeling soybean canopies while one surface should suffice to describe light interaction with corn canopy leaves.

To develop the full potential of multispectral data acquired from satellites, increased knowledge and understanding of the spectral characteristics of specific earth features is required. Knowledge of the relationships between the spectral characteristics and important parameters of earth surface features can best be obtained by carefully controlled studies over areas, fields, or plots where complete data describing the condition of targets is attainable and where frequent, timely spectral measurements can be obtained. The currently available instrumentation systems are either inadequate or too costly to obtain these data. Additionally, there is a critical need for standardized acquisition and calibration procedures to ensure the validity and comparability of data.The radiometric instrument will be a multiband radiometer with 8 bands between 0.4 and 12.5 micrometers; the data acquisition system will record data from the multiband radiometer, a precision radiation thermometer, and ancillary sources. The radiometer and data handling systems will be adaptable to helicopter, truck, or tripod platforms. The system will also be suitable for portable hand -held operation. The general characteristics of the system are that it will be: (i) comparatively inexpensive to acquire, maintain, and operate; (ii)simple to operate and calibrate; (iii) complete with data handling hardware and software and (iv) well -documented for use by researchers.The instrument system will be a prototype of an economical system which can be utilized by many researchers to obtain large numbers of accurate, calibrated spectral measurements. As such it is a key element in improving and advancing the capability for field research in remote sensing.

No abstract

No abstract

A crops and soils data base has been developed at Purdue University's Laboratory for Applications of Remote Sensing using spectral and agronomic measurements made by several government and university researchers.The data are being used to (1) quantitatively determine the relationships of spectral and agronomic characteristics of crops and soils, (2) define future sensor systems, and (3) develop advanced data analysis techniques.Researchers follow defined data acquisition and preprocessing techniques to provide fully annotated and calibrated sets of spectral, agronomic, and meteorological data. These procedures enable the researcher to combine his data with that acquired by other researchers for remote sensing research. The key elements or requirements for developing a field research data base of spectral data that can be transported across sites and years are appropriate experiment design, accurate spectral data calibration, defined field procedures, and thorough experiment documentation.