Corn Blight Watch experiment
Aerial and ground surveillance of southern corn leaf blight in Corn Belt States during 1971
Source record↗
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Corn blight watch experiment results
Results pertaining to the detection and assessment of the severity and extent of southern corn leaf blight in the Corn Belt area are discussed. Ground observations, interpretation of color infrared photography, and machine analysis of multispectral scanner data were used to identify the blight.
Johannsen, C. J.↗
The corn blight problem: 1970 and 1971
Southern corn leaf blight is caused by the fungus, Helminthosporium maydis. Race T of H maydis adapted itself to the Texas male sterile cytoplasm corn. The problems caused by this variety of the blight in 1970 and 1971 are discussed, as well as the symptoms and development of the disease.
Bauer, M. E.↗
Corn blight review: Sampling model and ground data measurements program
The sampling plan involved the selection of the study area, determination of the flightline and segment sample design within the study area, and determination of a field sample design. Initial interview survey data consisting of crop species acreage and land use were collected. On all corn fields, additional information such as seed type, row direction, population, planting date, ect. were also collected. From this information, sample corn fields were selected to be observed through the growing season on a biweekly basis by county extension personnel.
Allen, R. D.↗
Detailed interpretation and analysis of selected corn blight watch data sets
A detailed interpretation and analysis of selected corn blight data set was undertaken in order to better define the present capabilities and limitations of agricultural remote multispectral sensing and automatic processing techniques and to establish the areas of investigation needing futher attention in the development of operational survey systems. While the emphasis of this effort was directed toward the detection of various corn blight levels, problems related to the more general task of crop identification were also investigated. Since the analog recognition computer (SPARC) was fully committed to the more routine aspects of processing and since the detailed interpretation and analysis required more in the way of quantitative information, the CDC 1604 digital computer was employed.
Nalepka, R. F.↗
Results of the 1971 Corn Blight Watch experiment
Advanced remote sensing techniques are used to: (1)Detect development and spread of corn leaf blight during the growing season; (2) assess the extent and severity of blight infection; (3) assess the impact of blight on corn production; and (4) estimate the applicability of these techniques to similar situations occurring in the future.
Macdonald, R. B.↗
Multispectral determination of vegetative cover in corn crop canopy
The relationship between different amounts of vegetative ground cover and the energy reflected by corn canopies was investigated. Low altitude photography and an airborne multispectral scanner were used to measure this reflected energy. Field plots were laid out, representing four growth stages of corn. Two plot locations were chosen-on a very dark and a very light surface soil. Color and color infrared photographs were taken from a vertical distance of 10 m. Estimates of ground cover were made from these photographs and were related to field measurements of leaf area index. Ground cover could be predicted from leaf area index measurements by a second order equation. Microdensitometry and digitzation of the three separated dye layers of color infrared film showed that the near infrared dye layer is most valuable in ground cover determinations. Computer analysis of the digitized photography provided an accurate method of determining precent ground cover.
Stoner, E. R.↗
Corn blight watch experiment
The corn blight problem is briefly described how the experiment was organized and conducted, the effect of the blight on the 1971 crop, and some conclusions that may be drawn as a result of the experiment. The information is based on preliminary reports of the Corn Blight Watch Steering Committee and incorporates much illustrative material conceived at Purdue University.
Source record↗
Monitoring corn and soybean crop development by remote sensing techniques
A system for spectrally monitoring the stages of crop development for corn and soybeans based upon red and photographic infrared spectral radiances is proposed. The red and photographic infrared spectral radiance, highly correlated with the green leaf area index or green leaf biomass, enable nondestructive monitoring of the crop canopy throughout the growing season. Five distinct periods are apparent which are related to crop development for corn and soybeans.
Tucker, C. J.↗
Influence of soils on Landsat spectral signatures of corn
Landsat data have been investigated extensively to determine crop types and acreage. However, confounding site factors have been found to reduce accuracy. Soils data in a small, contiguous area in southeast South Dakota were used to stratify Landsat data. A June 5 and July 29 CCT were used in a statistical analysis of corn training data. Significant soil parameters causing differences in study area soils were slope and parent material. Implication of the results is that, in this region, stratification of CCT data along parent material boundaries would improve corn classification accuracy. Research expanding on the interaction of soils and crops is both in progress and scheduled for additional studies in east central South Dakota.
Dalsted, K. J.↗
An assessment of LANDSAT data acquisition history on identification and area estimation of corn and soybeans
Multitemporally registered LANDSAT MSS data from four acquisitions during the 1978 growing season were used in classification of eight sample segments in Iowa and Indiana. The results illustrate that use of LANDSAT acquisition when corn has tasseled is critical, as this is the optimum time for separation of corn and soybeans. An early season acquisition when the summer crops appear as bare soil can be beneficial in reducing the confusion between these two crops and other cover types. A subset of one visible and one infrared band from each date was found to produce results not significantly different from the use of all bands. Selection of a subset of these bands may also be feasible for multitemporal analysis.
Hixson, M. M.↗
Evaluation of results of US corn and soybeans exploratory experiment: Classification procedures verification test
The classification procedure utilized in making crop proportion estimates for corn and soybeans using remotely sensed data was evaluated. The procedure was derived during the transition year of the Large Area Crop Inventory Experiment. Analysis of variance techniques were applied to classifications performed by 3 groups of analysts who processed 25 segments selected from 4 agrophysical units (APU's). Group and APU effects were assessed to determine factors which affected the quality of the classifications. The classification results were studied to determine the effectiveness of the procedure in producing corn and soybeans proportion estimates.
Carnes, J. G.↗
Large area application of a corn hazard model
An application test of the crop calendar portion of a corn (maize) stress indicator model developed by the early warning, crop condition assessment component of AgRISTARS was performed over the corn for grain producing regions of the U.S.S.R. during the 1980 crop year using real data. Performance of the crop calendar submodel was favorable; efficiency gains in meteorological data analysis time were on a magnitude of 85 to 90 percent.
Ashburn, P.↗
Using Landsat digital data to detect moisture stress in corn-soybean growing regions
As a part of a follow-on study to the moisture stress detection effort conducted in the Large Area Crop Inventory Experiment (LACIE), a technique utilizing transformed Landsat digital data was evaluated for detecting moisture stress in humid growing regions using sample segments from Iowa, Illinois, and Indiana. At known growth stages of corn and soybeans, segments were classified as undergoing moisture stress or not undergoing stress. The remote-sensing-based information was compared to a weekly ground-based index (Crop Moisture Index). This comparison demonstrated that the remote sensing technique could be used to monitor the growing conditions within a region where corn and soybeans are the major crop.
Thompson, D. R.↗
An assessment of Landsat data acquisition history on identification and area estimation of corn and soybeans
During the past decade, numerous studies have demonstrated the potential of satellite remote sensing for providing accurate and timely crop area information. This study assessed the impact of Landsat data acquisition history on classification and area estimation accuracy of corn and soybeans. Multitemporally registered Landsat MSS data from four acquisitions during the 1978 growing season were used in classification of eight sample segments in the U.S. Corn Belt. The results illustrate the importance of selecting Landsat acquisitions based on spectral differences in crops at certain growth stages.
Hixson, M. M.↗
AgRISTARS: Supporting research. Classification of corn: Badhwar profile similarity technique
The same software programs used to classify spring wheat are applied to the classification of corn in 26 segments in the corn belt. Numerical results of the acreage estimation are given. Potential problem areas defined in an earlier application are examined.
Austin, W. W.↗
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.↗
Temporal relationships between spectral response and agronomic variables of a corn canopy
Attention is given to an experiment in which spectral radiance data collected in three spectral regions are related to corn canopy variables. The study extends the work of Tucker et al. (1979) in that more detailed measurements of corn canopy variables were made using quantitative techniques. Wet and dry green leaf biomass is considered along with the green leaf area index, chlorotic leaf biomass, chlorotic leaf area, and leaf water content. In addition, spectral data were collected with a hand-held radiometer having Landsat-D Thematic Mapper (TM) bands TM3 (0.63-0.69 micrometers), TM4 (0.76-0.90 micrometers), and TM5 (1.55-1.75 micrometers). TM3, TM4, and TM5 seem to be well situated spectrally for making remotely sensed measurements related to chlorophyll concentration, leaf density, and leaf water content.
Kimes, D. S.↗