Ray D. Jackson

Spectral response of a plant canopy with different soil backgrounds

Abstract The spectral behavior of a cotton canopy with four soil types alternately inserted underneath was examined at various levels of vegetation density. Measured composite spectra, representing various mixtures of vegetation with different soil backgrounds, were compared with existing measures of greenness, including the NIR-red band ratios, the perpendicular vegetation index (PVI), and the greenness vegetation index (GVI). Observed spectral patterns involving constant vegetation amounts with different soil backgrounds could not be explained nor predicted by either the ratio or the orthogonal greenness measures. All greenness measures were found to be strongly dependent on soil brightness. Furthermore, soil-induced greenness changes became greater with increasing amounts of vegetation up to 60% green cover. The results presented suggests that soil and plant spectra interactively mix in a nonadditive, partly correlated manner to produce composite canopy spectra.

Interpreting vegetation indices

Remotely sensed spectral vegetation indices are widely used and have benefited numerous disciplines interested in the assessment of biomass, water use, plant stress, plant health and crop production. The successful use of these indices requires knowledge of the units of the input variables used to form the indices, and an understanding of the manner in which the external environment and the architectural aspects of a vegetation canopy influence and alter the computed index values. Although vegetation indices were developed to extract the plant signal only, the soil background, moisture condition, solar zenith angle, view angle, as well as the atmosphere, alter the index values in complex ways. The nature of these problems are explored both in an empirical and in a theoretical sense, and suggestions are offered for the effective use and interpretation of vegetation indices.

The Dependence of Bare Soil Albedo on Soil Water Content

Abstract Simple albedo measurement may prove useful for sensing surface soil water content and as a research tool in the study of evaporation of water from soil. Intensive concurrent measurements of the albedo and soil water content of a drying bare soil indicate that albedo, normalized for sun zenith angle effects, is a linear function of the soil water content of a very thin surface layer (less than 0.2 cm thick) over a sizeable volumetric water content range (0.00 to 0.18 for an Avondale loam). Albedo is also well correlated with the average soil water content of greater soil thicknesses. Measurements to a depth of 10 cm indicate that the relation is relatively independent of season.

Reflectance- and radiance-based methods for the in-flight absolute calibration of multispectral sensors

Abstract Variations reported in the in-flight absolute radiometric calibration of the Coastal Zone Color Scanner (CZCS) and the Thematic Mapper (TM) on Landsat 4 are reviewed. At short wavelengths these sensors exhibited a gradual reduction in response, while in the midinfrared the TM showed oscillatory variations, according to the results of TM internal calibration. The methodology and results are presented for five reflectance-based calibrations of the Landsat 5 TM at White Sands, NM, in the period July 1984 to November 1985. These show a ±2.8% standard deviation (1 σ) for the six solar-reflective bands. Analysis and preliminary results of a second, independent calibration method based on radiance measurements from a helicopter at White Sands indicate that this is potentially an accurate method for corroborating the results from the reflectance-based method.

Evaluation of simplified procedures for retrieval of land surface reflectance factors from satellite sensor output

Abstract In response to the need for a simple atmospheric correction method and the consequent verification of such a method, an experiment was conducted to acquire a data set suitable for testing atmospheric correction procedures under a variety of atmospheric conditions. Several procedures, including radiative transfer codes (RTCs) with simulated atmospheres, image-based procedures and dark-object subtraction (DOS), were evaluated by comparing surface reflectance factors derived from Landsat Thematic Mapper (TM) digital data with low-altitude, aircraft-based measurements for seven dates over a 1-year period. Acceptable results, approximately ± 0.02 reflectance (1 σ RMS), were achieved based on an RTC with appropriate simulated atmospheres. The DOS technique was the least accurate method and, in fact, produced greater error in estimations of near-IR reflectance than no correction at all. Two hybrid approaches, which combined the image-based nature of DOS with the precision of an RTC, provided sufficient accuracy and simplicity to warrant consideration for use on an operational basis. Though these results were probably site-specific (characterized by relatively low aerosol levels and low humidity), they illustrate the feasibility of simple atmospheric correction methods and the usefulness of a diverse data set for validation of such techniques.

Spectral indices in N-Space

Linear combinations of n spectral bands form physically significant indices in n-dimensional space. The 2-dimensional (2-D) perpendicular vegetation index (PVI) of Richardson and Wiegand and the 4-D tasseled cap of Kauth and Thomas are special cases of n-space indices. A procedure for calculating the coefficients of n-space indices is described. Spectra from 12 wheat and two bare soil (wet and dry) plots were multiplied point by point (at 1-nm intervals) by response functions representing five satellite sensors. Reflectance values were obtained for each band for each sensor (atmospheric effects and sensor characteristics such as noise, resolution, and calibration, were not considered). N-Space indices were calculated for various band combination for the several sensors and their dynamic range for a 0–100% change in vegetation was compared. A 6-D vegetation index (greenness) calculated using six of the thematic mapper bands had the greatest dynamic range, followed closely by two 5-D and one 4-D greenness from the same sensor. The 2-D greenness using bands 4 (near-IR) and 7 (mid-IR) of the thematic mapper had a greater dynamic range than any band combination of the other four satellite sensors. The 4-D greenness of the Landsat-4 MSS and the 3-D index of the SPOT HRV were similar. The 2-D indices from the AVHRR sensors on NOAA-6 and NOAA-7 changed less with vegetation changes than did the other three.

Discrimination of growth and water stress in wheat by various vegetation indices through clear and turbid atmospheres

Abstract Reflectance data were obtained over a drought-stressed and a well-watered wheat plot with a hand-held radiometer having bands similar to the MSS bands of the Landsat satellites. Data for 48 clear days were interpolated to yield reflectance values for each day of the growing season, from planting until harvest. With an atmospheric path radiance model and Landsat 2 calibration data, the reflectances were used to simulate Landsat digital counts (not quantized) for the four Landsat bands for each day of the growing season, through a clear ( ⋍100- km meteorological range) and a turbid ( ⋍10- km meteorological range) atmosphere. Several ratios and linear combinations of bands were calculated using the simulated data, then assessed for their relative ability to discriminate vegetative growth and plant stress through the two atmospheres. The results showed that water stress was not detected by any of the indices until after growth was retarded, and the sensitivity of the various indices to vegetation depended on plant growth stage and atmospheric path radiance.

Remote-Sensing of Crop Yields

Our research efforts with durum wheat have led to the development of the SDD concept. Its application makes possible crop yield estimates from remotely acquired canopy temperatures and auxiliary air temperature measurements obtained during the period from head emergence to the cessation of head growth. Canopy albedo measurements appear adequate to delineate this critical period, making the technique potentially adaptable to predictions of crop yields by remote-sensing. The trifactor nomograms produced from combinations of the linear regression equations also suggest that the SDD concept may be used for scheduling irrigations by remote-sensing.

Determination of sensible heat flux over sparse canopy using thermal infrared data

Surface temperatures, Ts, were estimated for a natural vegetative surface in Owens Valley, California, with infrared thermometric observations collected from an aircraft. The region is quite arid and is composed primarily of bushes (∼30%) and bare soil (∼70%). Application of the bulk transfer equation for the estimation of sensible heat, H, gave unsatisfactory values when compared to Bowen ratio and eddy correlation methods over a particular site. This was attributed to the inability with existing data to properly evaluate the resistance to heat transfer, rah. To obtain appropriate rah-values the added resistance to heat transfer, kB−1, was allowed to vary although there is both theoretical and experimental evidence that kB−1 for vegetative surfaces can be treated as constant. The present data indicate that for partial canopy cover under arid conditions kB−1 may be a function of Ts measured radiometrically. The equation determining kB−1 was simplified and tested over another arid site with good results; however, this had a limited data set (i.e., 6 data points). The dimensionless kB−1 equation is simplified for use over full canopy cover and is shown to give satisfactory estimates of H over a fully-grown wheat crop.

Estimation of Daily Evapotranspiration from one Time-of-Day Measurements

Jackson, R.D., Hatfield, J.L., Reginato, R.J., Idso, S.B. and Pinter, P.J., Jr., 1983. Estimation of daily evapotranspiration from one time-of-day measurements. Agric. Water Manage., 7: 351–362. The estimation of evapotranspiration (ET) on a regional basis requires remote sensing inputs. When obtained from air or space platforms, remotely sensed measurements are usually made at periodic intervals, and are essentially instantaneous in nature. A problem, then, is the estimation of daily values of ET from one time of day measurements. A technique is presented that allows the calculation of the coefficient necessary to convert one time of day measurements to daily totals. Input requirements are latitude, day of year, and time of day. This coefficient was applied to measured one time of day ET values and the results were compared to lysimetrically determined daily totals obtaind at five locations and for four crops. One time of day ET was also calculated using an ET model that requires remotely sensed surface temperatures. These values were converted to daily totals and compared with measured values. The results indicated that reliable estimates of daily total ET from one time of day measurements could be made for cloud free days. For cloudy days the results are less reliable, but they suggest that estimates may be improved by considering the amount and temporal distribution of cloud cover.