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At least 595 records · Page 33

Landsat features for agricultural applications

This paper presents relationships among Landsat MSS bands and selected transformations of them, with emphasis on the Tasseled-Cap Transformation and its Brightness, Greenness variables. It also discusses relationships between reflectance measurements made in the Landsat spectral bands and actual Landsat data. Agronomically oriented analyses of reflectance measurements of wheat throughout a growing season are presented, with a comparison of various green measures, correlation with crop development stage, and examination of the effects of moisture stress. The final example addresses the use of transformed variables in a newly developed approach to forestry change detection.

Malila, W. A.↗

Procedure M - An advanced procedure for stratified area estimation using Landsat

Procedure M is a systematic approach to processing multispectral scanner data for classification and acreage estimation. The procedure incorporates a statistically robust mechanism for estimation while utilizing component technologies that are based on the physically expected or measured responses of the canopy, atmosphere and sensor. This paper describes Procedure M in the context of large-area agricultural applications, emphasizing three specific configurations: for winter wheat, spring small grains, and corn and soybeans.

Holmes, Q. A.↗

A model of plant canopy polarization response

Sensors to remotely measure the linear polarization of ground scenes have been proposed for the Multispectral Resource Sampler (MRS), a satellite sensor system proposed to complement the Thematic Mapper. At present justification for a sensor on MRS to measure scene polarization is limited. This paper discusses a model for the amount of linearly polarized light reflected by the shiny leaves of such crops as wheat, corn, and sorghum. The theory demonstrates that, potentially, measurements of the linearly polarized light from a crop canopy may be used as an additional feature to discriminate between crops. Examination of the model suggests that, potentially, satellite polarization measurements may be used to monitor crop development stage, leaf water content, leaf area index, hail damage, and certain plant diseases. The model adds to the understanding of the potential information content of scene polarization measurements acquired by future satellite sensor systems such as MRS.

Vanderbilt, V. C.↗

Preliminary evaluation of spectral, normal and meteorological crop stage estimation approaches

Several of the projects in the AgRISTARS program require crop phenology information, including classification, acreage and yield estimation, and detection of episodal events. This study evaluates several crop calendar estimation techniques for their potential use in the program. The techniques, although generic in approach, were developed and tested on spring wheat data collected in 1978. There are three basic approaches to crop stage estimation: historical averages for an area (normal crop calendars), agrometeorological modeling of known crop-weather relationships agrometeorological (agromet) crop calendars, and interpretation of spectral signatures (spectral crop calendars). In all, 10 combinations of planting and biostage estimation models were evaluated. Dates of stage occurrence are estimated with biases between -4 and +4 days while root mean square errors range from 10 to 15 days. Results are inconclusive as to the superiority of any of the models and further evaluation of the models with the 1979 data set is recommended.

Cate, R. B.↗

As-Built documentation of programs to implement the Robertson and Doraiswamy/Thompson models

The software which implements two spring wheat phenology models is described. The main program routines for the Doraiswamy/Thompson crop phenology model and the basic Robertson crop phenology model are DTMAIN and BRMAIN. These routines read meteorological data files and coefficient files, accept the planting date information and other information from the user, and initiate processing. Daily processing for the basic Robertson program consists only of calculation of the basic Robertson increment of crop development. Additional processing in the Doraiswamy/Thompson program includes the calculation of a moisture stress index and correction of the basic increment of development. Output for both consists of listings of the daily results.

Valenziano, D. J.↗

The 1981 Argentina ground data collection

Over 600 fields in the corn, soybean and wheat growing regions of the Argentine pampa were categorized by crop or cover type and ancillary data including crop calendars, historical crop production statistics and certain cropping practices were also gathered. A summary of the field work undertaken is included along with a country overview, a chronology of field trip planning and field work events, and the field work inventory of selected sample segments. LANDSAT images were annotated and used as the field work base and several hundred ground and aerial photographs were taken. These items along with segment descriptions are presented. Meetings were held with officials of the State Secretariat of Agriculture (SEAG) and the National Commission on Space Investigations (CNIE), and their support to the program are described.

Horvath, R.↗

AgRISTARS: Foreign commodity production forecasting. Country summary report, Australia

Australia is one of the world's major growers and exporters of wheat and as such is one of the countries of interest in the AgRISTARS program which endeavors to develop technology to estimate crop production using aerospace remote sensing. A compilation of geographic, political, and agricultural information on Australia is presented. Also included is a summary of the aerospace remote sensing, meteorological, and ground-observed data which were collected with respect to Australia, as well as a summary of contacts between AgRISTARS and Australia personnel.

Henninger, D. L.↗

AgRISTARS: Supporting research. Spring small grains planting date distribution model

A model was developed using 996 planting dates at 51 LANDSAT segments for spring wheat and spring barley in Minnesota, Montana, North Dakota, and South Dakota in 1979. Daily maximum and minimum temperatures and precipitation were obtained from the cooperative weather stations nearest to each segment. The model uses a growing degree day summation modified for daily temperature range to estimate the beginning of planting and uses a soil surface wetness variable to estimate how a fixed number of planting days are distributed after planting begins. For 1979, the model predicts first, median, and last planting dates with root mean square errors of 7.91, 6.61, and 7.09 days, respectively. The model also provides three or four dates to represent periods of planting activity within the planting season. Although the full model was not tested on an independent data set, it may be suitable in areas other than the U.S. Great Plains where spring small grains are planted as soon as soil and air temperatures become warm enough in the spring for plant growth.

Hodges, T.↗

A model of plant canopy polarization

A model for the amount of linearly polarized light reflected by the shiny leaves of grain crops is based on the morphological and phenological characteristics of the plant canopy and upon the Fresnel equations which describe the light reflection process at the smooth boundary separating two dielectrics. The theory used demonstrates that, potentially, measurements of the linearly polarized light from a crop canopy may be used as an additional feature to discriminate between crops such as wheat and barley, two crops which are so spectrally similar that they are misclassified with unacceptable frequency. Examination of the model suggests that, potentially, satellite polarization measurements may be used to monitor crop development stage, leaf water content, leaf area index, hail damage, and certain plant diseases. The information content of these measurements is needed to evaluate the proposed polarization sensor for the satellite-borne multispectral resource sampler.

Vanderbilt, V. C.↗

Analysis of scanner data for crop inventories

Progress and technical issues are reported in the development of corn/soybeans area estimation procedures for use on data from South America, with particular emphasis on Argentina. Aspects related to the supporting research section of the AgRISTARS Project discussed include: (1) multisegment corn/soybean estimation; (2) through the season separability of corn and soybeans within the U.S. corn belt; (3) TTS estimation; (4) insights derived from the baseline corn and soybean procedure; (5) small fields research; and (6) simulating the spectral appearance of wheat as a function of its growth and development. To assist the foreign commodity production forecasting, the performance of the baseline corn/soybean procedure was analyzed and the procedure modified. Fundamental limitations were found in the existing guidelines for discriminating these two crops. The temporal and spectral characteristics of corn and soybeans must be determined because other crops grow with them in Argentina. The state of software technology is assessed and the use of profile techniques for estimation is considered.

Horvath, R.↗

The extension of a uniform canopy reflectance model to include row effects

The effect of row structure is assumed to be caused by the variation in density of vegetation across rows rather than to a profile in canopy height. The calculation of crop reflectance using vegetation density modulation across rows follows a parallel procedure to that for a uniform canopy. Predictions using the row model for wheat show that the effect of changes in sun to row azimuth are greatest in Landsat Band 5 (red band) and can result in underestimation of crop vigor.

Suits, G. H.↗

Selection of the Argentine indicator region

Determined from available Argentine crop statistics, selection of the Indicator Region was based on the highest wheat, corn, and soybean producing provinces, which were: Buenos Aires, Cordoba, Entre Rios, and Santa Fe. Each province in Argentina was examined for the availability of LANDSAT data; area, yield and production statistics; crop calendars; and other ancillary data. The Argentine Indicator Region is described.

Ramirez, C. J.↗

Agronomic characterization of the Argentina Indicator Region

An overview of the Argentina indicator region including information on topography, climate, soils and vegetation is presented followed by a regionalization of crop livestock land use. Corn/soybean production and exports as well as agricultural practices are discussed. Similarities and differences in the physical agronomic scene, crop livestock land use and agricultural practices between the U.S. corn belt and the Argentine pampa are considered. The Argentine agricultural economy is described. Crop calendars for the Argentina indicator region, an accompanying description, notes on crop-livestock zones, wheat production, field size, and agricultural problems and practices are included.

Hicks, D. R.↗

Within-field variability of plant and soil parameters

The variability of ground truth data collected for vegetation experiments was investigated. Two fields of wheat and one field of corn were sampled on two different dates. The variability of crop and soil parameters within a field, between two fields of the same type, and within a field over time were compared statistically. The number of samples from each test site required in order to be able to determine with confidence the mean and standard deviations for a given variable was determined. Eight samples were found to be adequate for plant height determinations, while twenty samples were required for plant moisture and soil moisture characterization. Eighteen samples were necessary for detecting within field variability over time and for between field variability for the same crop. The necessary sample sites vary according to the physiological growth stage of the crop and recent weather events that affect the moisture and/or height characteristics of the field in question.

Ulaby, F. T.↗

Air pollutant production by algal cell cultures

The production of phytotoxic air pollutants by cultures of Chlorella vulgaris and Euglena gracilis is considered. Algal and plant culture systems, a fumigation system, and ethylene, ethane, cyanide, and nitrogen oxides assays are discussed. Bean, tobacco, mustard green, cantaloupe and wheat plants all showed injury when fumigated with algal gases for 4 hours. Only coleus plants showed any resistance to the gases. It is found that a closed or recycled air effluent system does not produce plant injury from algal air pollutants.

Fong, F.↗