Engineering topics

Bauer, M. E.

Publications and source records attributed to Bauer, M. E..

At least 19 records

NASA NTRS1991

Satellite spectral data and archaeological reconnaissance in western Greece

A Macro-geographical reconnaissance of the Western Peloponnesos adopts spectral signatures taken by Landsat-5 Thematic Mapper as a new instrument of archaeological survey in Greece. Ancient records indicate that indigenous resources contributed to the prosperity of the region. Natural resources and Ancient, Medieval, and Pre-modern Folklife in the Western Peloponnesos describes the principal lines of research. For a supervised classification of attested ancient resources, a variety of biophysical surface features were pinpointed: stone quarries, coal mines, forests of oak and silver fir, terracotta-producing clay beds, crops, and various wild but exploited shrubs such as flax.

Cooper, Frederick A.↗

NASA NTRS1990

Canopy architecture measured with a laser

A laser based method was employed to measure and numerically describe the architecture of a corn canopy. Use of the method provides an interception coefficient for classes of vegetation in layers of the canopy viewed in various directions. Architectural data obtained for similar corn canopies but measured by differing methods are comparable to the results obtained using the laser based method. These results provide input data to mathematical models employed in remote sensing for describing the radiation environment in a plant canopy and predicting its reflectance.

Vanderbilt, Vern C.↗

NASA NTRS1986

Effects of nitrogen fertilization on growth and reflectance characteristics of winter wheat

The use of remote sensing to determine seasonal changes in agronomic and spectral properties of winter wheat canopies with different levels of N fertilization is investigated. Field experiments were conducted at Purdue Agronomy Farm, West Lafayette, IN during the 1978-1979 and 1979-1980 growing season. Spectral reflectance, total leaf N concentration, leaf chlorophyll concentration, leaf are index (LAI), and fresh and dry phytomass are measured and analyzed. Three distinct wheat canopies are detected for the O, 60, and 120 kg N/ha levels of fertilization; it is observed that with an increase in N the reflectance in the visible, and middle IR wavelengths decrease, and the IR reflectance is increased. The canopies with 120 kg N/ha display the highest LAI, maintain green leaf area the longest, and increase in fresh and dry phytomass. The relationship between spectral and agronomic variables is examined; the effect of changing chlorophyll concentration and LAI on the reflectance is studied.

Hinzman, L. D.↗

NASA NTRS1986

Field spectroscopy of agricultural crops

The development of the full potential of multispectral data acquired from satellites, requires quantitative knowledge, and physical models of the spectral properties of specific earth surface features. Knowledge of the relationships between spectral-radiometric characteristics and important biophysical parameters of agricultural crops and soils can best be obtained by carefully controlled studies of fields or plots. It is important to select plots where data describing the agronomic-biophysical properties of the crop canopies and soil background are attainable, taking into account also the feasibility of frequent timely calibrated spectral measurements. The term 'field spectroscopy' is employed for this research. The present paper is concerned with field research which was sponsored by NASA as part of the AgRISTARS Supporting Research Project. Attention is given to field research objectives, field research instrumentation, measurement procedures, spectral-temporal profile modeling, and the effects of cultural and environmental factors on crop reflectance.

Bauer, M. E.↗

NASA NTRS1985

Sun-view angle effects on reflectance factors of corn canopies

The effects of sun and view angles on reflectance factors of corn (Zea mays L.) canopies ranging from the six leaf stage to harvest maturity were studied on the Purdue University Agronomy Farm by a multiband radiometer. The two methods of acquiring spectral data, the truck system and the tower systrem, are described. The analysis of the spectral data is presented in three parts: solar angle effects on reflectance factors viewed at nadir; solar angle effects on reflectance factors viewed at a fixed sun angle; and both sun and view angles effect on reflectance factors. The analysis revealed that for nadir-viewed reflectance factors there is a strong solar angle dependence in all spectral bands for canopies with low leaf area index. Reflectance factors observed from the sun angle at different view azimuth angles showed that the position of the sensor relative to the sun is important in determining angular reflectance characteristics. For both sun and view angles, reflectance factors are maximized when the sensor view direction is towards the sun.

Ranson, K. J.↗

NASA NTRS1985

Spectral estimators of absorbed photosynthetically active radiation in corn canopies

Most models of crop growth and yield require an estimate of canopy leaf area index (LAI) or absorption of radiation. Relationships between photosynthetically active radiation (PAR) absorbed by corn canopies and the spectral reflectance of the canopies were investigated. Reflectance factor data were acquired with a Landsat MSS band radiometer. From planting to silking, the three spectrally predicted vegetation indices examined were associated with more than 95 percent of the variability in absorbed PAR. The relationships developed between absorbed PAR and the three indices were evaluated with reflectance factor data acquired from corn canopies planted in 1979 through 1982. Seasonal cumulations of measured LAI and each of the three indices were associated with greater than 50 percent of the variation in final grain yields from the test years. Seasonal cumulations of daily absorbed PAR were associated with up to 73 percent of the variation in final grain yields. Absorbed PAR, cumulated through the growing season, is a better indicator of yield than cumulated leaf area index. Absorbed PAR may be estimated reliably from spectral reflectance data of crop canopies.

Gallo, K. P.↗

NASA NTRS1984

Vegetation and soils field research data base: Experiment summaries

Understanding of the relationships between the optical, spectral characteristics and important biological-physical parameters of earth-surface features can best be obtained by carefully controlled studies over fields and plots where complete data describing the condition of targets are attainable and where frequent, timely spectral measurement can be obtained. Development of a vegetation and soils field research data base was initiated in 1972 at Purdue University's Laboratory for Applications of Remote Sensing and expanded in the fall of 1974 by NASA as part of LACIE. Since then, over 250,000 truck-mounted and helicopter-borne spectrometer/multiband radiometer observations have been obtained of more than 50 soil series and 20 species of crops, grasses, and trees. These data are supplemented by an extensive set of biophysical and meteorological data acquired during each mission. The field research data form one of the most complete and best-documented data sets acquired for agricultural remote sensing research. Thus, they are well-suited to serve as a data base for research to: (1) quantiatively determine the relationships of spectral and biophysical characteristics of vegetation, (2) define future sensor systems, and (3) develop advanced data analysis techniques.

Biehl, L. L.↗

NASA NTRS1984

Growth and reflectance characteristics of winter wheat canopies

A valuable input to crop growth and yield models would be estimates of current crop condition. If multispectral reflectance indicates crop condition, then remote sensing may provide an additional tool for crop assessment. The effects of nitrogen fertilization on the spectral reflectance and agronomic characteristics of winter wheat (Triticum aestivum L.) were determined through field experiments. Spectral reflectance was measured during the 1979 and 1980 growing seasons with a spectroradiometer. Agronomic data included total leaf N concentration, leaf chlorophyll concentration, stage of development, leaf area index (LAI), plant moisture, and fresh and dry phytomass. Nitrogen deficiency caused increased visible, reduced near infrared, and increased middle infrared reflectance. These changes were related to lower levels of chlorophyll and reduced leaf area in the N-deficient plots. Green LAI, an important descriptor of wheat canopies, could be reliably estimated with multispectral data. The potential of remote sensing in distinguishing stressed from healthy crops is demonstrated. Evidence suggests multispectral imagery may be useful for monitoring crop condition.

Hinzman, L. D.↗

NASA NTRS1984

Variation in spectral response of soybeans with respect to illumination, view, and canopy geometry

Comparisons of the spectral response for incomplete (well-defined row structure) and complete (overlapping row structure) canopies of soybeans indicated a greater dependence on Sun and view geometry for the incomplete canopies. Red and near-IR reflectance for the incomplete canopy decreased as solar zenith angle increased for a nadir view angle until the soil between the plant rows was completely shaded. Thereafter for increasing solar zenith angle, the red reflectance leveled off and the near-IR reflectance increased. A 'hot spot' effect was evident for the red and near-IR reflectance factors. The 'hot spot' effect was more pronounced for the red band based on relative reflectance value changes. The ratios of off-nadir to nadir acquired data reveal that off-nadir red band reflectance factors more closely approximated straightdown measurements for time periods away from solar noon. Normalized difference generally approximated straightdown measurements during the middle portion of the day.

Ranson, K. J.↗

NASA NTRS1984

Microwave and optical remote sensing of forest vegetation

The objectives and anticipated results of a study to define the strengths and limitations of microwave (SIR-B) and optical (thematic Mapper) data, singly and in combination, for the purpose of characterizing forest cover types and condition classes are described. Other specific objectives include: (1) the assessment of the effectiveness of a contextual classification algorithm (SECHO); (2) evaluation of the utility of different look angles of SAR data in determining differences in stand density of commercial forests; and (3) the determination of the effectiveness of the L-band HH polarized SIR-B data in differentiating forest-stand densities.

Hoffer, R. M.↗

NASA NTRS1984

Spectral estimators of absorbed photosynthetically active radiation in corn canopies

Most models of crop growth and yield require an estimate of canopy leaf area index (LAI) or absorption of radiation. Relationships between photosynthetically active radiation (PAR) absorbed by corn canopies and the spectral reflectance of the canopies were investigated. Reflectance factor data were acquired with a LANDSAT MSS band radiometer. From planting to silking, the three spectrally predicted vegetation indices examined were associated with more than 95% of the variability in absorbed PAR. The relationships developed between absorbed PAR and the three indices were evaluated with reflectance factor data acquired from corn canopies planted in 1979 through 1982. Seasonal cumulations of measured LAI and each of the three indices were associated with greater than 50% of the variation in final grain yields from the test years. Seasonal cumulations of daily absorbed PAR were associated with up to 73% of the variation in final grain yields. Absorbed PAR, cumulated through the growing season, is a better indicator of yield than cumulated leaf area index. Absorbed PAR may be estimated reliably from spectral reflectance data of crop canopies.

Gallo, K. P.↗

NASA NTRS1983

Remote sensing of agricultural crops and soils

Research in the correlative and noncorrelative approaches to image registration and the spectral estimation of corn canopy phytomass and water content is reported. Scene radiation research results discussed include: corn and soybean LANDSAT MSS classification performance as a function of scene characteristics; estimating crop development stages from MSS data; the interception of photosynthetically active radiation in corn and soybean canopies; costs of measuring leaf area index of corn; LANDSAT spectral inputs to crop models including the use of the greenness index to assess crop stress and the evaluation of MSS data for estimating corn and soybean development stages; field research experiment design data acquisition and preprocessing; and Sun-view angles studies of corn and soybean canopies in support of vegetation canopy reflection modeling.

Bauer, M. E.↗

NASA NTRS1982

Relation of agronomic and multispectral reflectance characteristics of spring wheat canopies

The relationships between crop canopy variables such as leaf area index (LAI) and their multispectral reflectance properties were investigated along with the potential for estimating canopy variables from remotely sensed reflectance measurements. Reflectance spectra over the 0.4 to 2.5 micron wavelength range were acquired during each of the major development stages of spring wheat canopies at Williston, North Dakota, during three seasons. Treatments included planting date, N fertilization, cultivar, and soil moisture. Agronomic measurements included development stage, biomass, LAI, and percent soil cover. High correlations were found between reflectance and percent cover, LAI, and biomass. A near infrared wavelength band, 0.76 to 0.90 microns, was most important in explaining variation in LAI and percent cover, while a middle infrared band, 2.08 to 2.35 microns, explained the most variation in biomass and plant water content. Transformations, including the near infrared/red reflectance ratio and greenness index, were also highly correlated to canopy variables. The relationship of canopy variables to reflectance decreased as the crop began to ripen. the canopy variables could be accurately predicted using measurements from three to five wavelength bands. The wavelength bands proposed for the thematic mapper sensor were more strongly related to the canopy variables than the LANDSAT MSS bands.

Bauer, M. E.↗

NASA NTRS1982

Remote sensing of agricultural crops and soils

Research results and accomplishments of sixteen tasks in the following areas are described: (1) corn and soybean scene radiation research; (2) soil moisture research; (3) sampling and aggregation research; (4) pattern recognition and image registration research; and (5) computer and data base services.

Bauer, M. E.↗

NASA NTRS1982

Soybean canopy reflectance as a function of view and illumination geometry

The results of an experiment designed to characterize a soybean field by its reflectance at various view and illumination angles and by its physical and agronomic attributes are presented. Reflectances were calculated from measurements at four wavelength bands through eight view azimuth and seven view zenith directions for various solar zenith and azimuth angles during portions of three days. An ancillary data set consisting of the agronomic and physical characteristics of the soybean field is described. The results indicate that the distribution of reflectance from a soybean field is a function of the solar illumination and viewing geometry, wavelength and row direction, as well as the state of development of the canopy. Shadows between rows greatly affected the reflectance in the visible wavelength bands and to a lesser extent in the near infrared wavelengths. A model is proposed that describes the reflectance variation as a function of projected solar and projected viewing angles. The model appears to approximate the reflectance variations in the visible wavelength bands from a canopy with well defined row structure.

Bauer, M. E.↗

NASA NTRS1982

Spectral estimates of solar radiation intercepted by corn canopies

Reflectance factor data were acquired with a Landsat band radiometer throughout two growing seasons for corn (Zea mays L.) canopies differing in planting dates, populations, and soil types. Agronomic data collected included leaf area index (LAI), biomass, development stage, and final grain yields. The spectral variable, greenness, was associated with 78 percent of the variation in LAI over all treatments. Single observations of LAI or greenness have limited value in predicting corn yields. The proportions of solar radiation intercepted (SRI) by these canopies were estimated using either measured LAI or greenness. Both SRI estimates, when accumulated over the growing season, accounted for approximately 65 percent of the variation in yields. Models which simulated the daily effects of weather and intercepted solar radiation on growth had the highest correlations to grain yields. This concept of estimating intercepted solar radiation using spectral data represents a viable approach for merging spectral and meteorological data for crop yield models.

Bauer, M. E.↗

NASA NTRS1982

A crops and soils data base for scene radiation research

Management and planning activities with respect to food production require accurate and timely information on crops and soils on a global basis. The needed information can be obtained with the aid of satellite-borne sensors, if the relations between the spectral properties and the important biological-physical parameters of crops and soils are known. In order to obtain this knowledge, the development of a crops and soils scene radiation research data base was initiated. Work related to the development of this data base is discussed, taking into account details regarding the conducted experiments, the performed measurements, the calibration of spectral data, questions of data base access, and the expansion of the crops and soils scene radiation data base for 1982.

Biehl, L. L.↗

NASA NTRS1982

Corn and soybean Landsat MSS classification performance as a function of scene characteristics

In order to fully utilize remote sensing to inventory crop production, it is important to identify the factors that affect the accuracy of Landsat classifications. The objective of this study was to investigate the effect of scene characteristics involving crop, soil, and weather variables on the accuracy of Landsat classifications of corn and soybeans. Segments sampling the U.S. Corn Belt were classified using a Gaussian maximum likelihood classifier on multitemporally registered data from two key acquisition periods. Field size had a strong effect on classification accuracy with small fields tending to have low accuracies even when the effect of mixed pixels was eliminated. Other scene characteristics accounting for variability in classification accuracy included proportions of corn and soybeans, crop diversity index, proportion of all field crops, soil drainage, slope, soil order, long-term average soybean yield, maximum yield, relative position of the segment in the Corn Belt, weather, and crop development stage.

Batista, G. T.↗