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Some essential processes for the development of a green-number-based logic for identifying (labeling) crops in LANDSAT imagery are documented. The supporting data and subsequent conclusions that resulted from development of a specific labeling logic for corn and soybean crops in the United States are recorded.
An overall approach to crop spectral understanding is presented which serves to maintain a strong link between actual plant responses and characteristics and spectral observations from ground based and spaceborne sensors. A specific technique for evaluating field reflectance data, as a part of the overall approach, is also described. Results of the application of this technique to corn and soybeans reflectance data collected by and at Purdue/LARS indicate that a number of common cultural and environmental factors can significantly affect the temporal spectral development patterns of these crops in tasseled cap greenness (a transformed variable of LANDSAT MSS signals).
Attention is given to the development of methods for combining spectral and meteorological data in crop yield models which are capable of providing accurate estimates of crop condition and yields throughout the growing season. The present investigation is concerned with initial tests of these concepts using spectral and agronomic data acquired in controlled experiments. The data were acquired at the Purdue University Agronomy Farm, 10 km northwest of West Lafayette, Indiana. Data were obtained throughout several growing seasons for corn and soybeans. Five methods or models for predicting yields were examined. On the basis of the obtained results, it is concluded that estimating intercepted solar radiation using spectral data is a viable approach for merging spectral and meteorological data in crop yield models.
The capability of aerial color infrared photography for identifying and locating soilscapes most susceptible to drought development or those having different soil drainages was evaluated. Although west central and southwestern Minnesota had a significant precipitation deficit during the 1980 crop season, indications of plant stress were not observed either from ground observation or through interpretation of imagery at the selected sampling sites. Well-drained soil was more depleted during the "maximium green peak" period than the poorly drained soil. The recharge was more evident on the poorly drained site in the fall. Measurements of leaf water potential and leaf temperature for corn and soybean leaves were made by multispectral band scanner and recorded for analysis.
A Landsat MSS and TM classification approach based on three features derived from the greenness profile has proved very effective in separating and identifying corn, soybeans, and other ground cover classes in the U.S. The objective of this study is to investigate the separation of summer crops in Argentina, one of the most important commodity exporters, using the same greenness profile features that have proved effective in the U.S. Corn Belt. The area chosen for study is a more complex cropping practice area located in the north-west corner of Buenos Aires province in Pampa Humeda, where corn, soybean, sorghum, sunflower, and pastures are cultivated. It is shown that the profile features can provide very effective separation, except in the case of corn from sorghum. Separation between corn and soybeans was found to be greater than in the U.S. This study suggests that the automatic, unsupervised classification approach developed in the U.S., with relatively minor modification, can be used for summer crop area estimation in Argentina.
Current strategies for monitoring the physiologic status of terrestrial vegetation rely on remote sensing reflectance (R) measurements, whi ch provide estimates of relative vegetation vigor based primarily on chlorophyll content. Vegetation chlorophyll fluorescence (CF) offers a non-destructive alternative and a more direct approach for diagnosis of vegetation stress before a significant reduction in chlorophyll content has occurred. Thus, monitoring of vegetation vigor based on CF may allow earlier stress detection and more accurate carbon sequestra tion estimates, than is possible using R data alone. However, the observed apparent vegetation reflectance (Ra) in reality includes contrib utions from both the reflected and fluoresced radiation. The aim of t his study is to determine the relative R and CF fractions contributing to Ra from the vegetation in the red to near-infrared region of the spectrum. The practical objectives of the study are to: 1) evaluate t he relationship between CF and R at the foliar level for corn, soybean, maple; and 2) for corn, determine if the relationship established f or healthy (optimal N) vegetation changes under N defiiency. To obtai n generally applicable results, experimental measurements were conducted on unrelated crop and tree species (maple, soybean and corn), unde r controlled conditions and a gradient of inorganic N fertilization l evels. Optical R spectra and actively induced CF emissions were obtained on the same foliar samples, in conjunction with measurements of p hotosynthetic function, pigment levels, and C and N content. The comm on spectral trends or similarities were examined. On average, 10-20% of apparent R at 685 nm was actually due to CF. The spectral trends in steady and maximum F varied significantly, with Fs (especially red) showing higher ability for species and treatment separation. The relative contribution of ChF to R varied significantly among species, with maple emitting much higher F amounts, as compared to corn and soybea n. Fs individual red and far-red bands and their ratio exhibited consistent species separations. For corn, the relative CF fraction increased in concert with the nutrient stress levels from <2% for non-stressed foliage to >7% for severely nutrient deficient plants. F685s provide d optimal treatment separation. This study confirms the trends in F68 5sE740s associated with N deficiency and vegetation stress, established usmg single narrow band excitation.
We are investigating the use of spectral indices derived from actively induced fluorescence spectra and passive optical spectra. We examined the influence of photosynthetic pigment, carbon (C) and nitrogen (N) content on the spectral fluorescence and passive optical property characteristics of mature, upper leaves from plants provided different N fertilizer application rates: 20%, 50%, 100% and 150% of recommended N levels. A suite of optical, fluorescence, and biophysical measurements were collected on leaves from field grown corn (Zea mays L.) and soybean plants (Glycine max L.) grown in pots (greenhouse + ambient sunlight. Steady state laser-induced fluorescence emission spectra (5 nm resolution) were obtained from adaxial and abaxial surfaces resulting from excitation at single wavelengths (280, 380 or 360, and 532 nm). For emission spectra produced by each of these excitation wavelengths, ratios of emission peaks were calculated, including the red far-red chlorophyll fluorescence (ChlF) ratio (F685/F740) and the far-red/green (F740/F525) ratio. High resolution (< 3 nm) optical spectra (350-2500 nm) of reflectance, transmittance, and absorptance were also acquired for both adaxial and abaxial leaf surfaces. Species differences were demonstrated for several optical parameters. A 'red edge' derivative ratio determined from transmittance spectra [as the maximum first deivative, between 650-750 nm, normalized to the value at 744 nm, or Dmax/D744], was strongly associated with the C/N ratio (r(exp 2) = 0.90, P +/- 0.001). This ratio, calculated from reflectance spectra, was inversely related to chlorophyll b content (r(exp 2) = 0.91, P +/- 0.001) as was the ChlF (F685/F740) ratio obtained with 532 nm excitation (r(exp 2) = 0.76, P +/- 0.01). Discrimination of N treatment groups was possible with specific fluorescence band ratios (e.g., F740/F525 obtained with 380 nm excitation). Higher ChlF and blue-green emissions were measured from the abaxial leaf surfaces. Abaxial surfaces also produced higher reflectances, in general, in the 400-800 nm spectrum.
An optimal decision model of crop production, trade, and storage was developed for use in estimating the economic consequences of improved forecasts and estimates of worldwide crop production. The model extends earlier distribution benefits models to include production effects as well. Application to improved information systems meeting the goals set in the large area crop inventory experiment (LACIE) indicates annual benefits to the United States of $200 to $250 million for wheat, $50 to $100 million for corn, and $6 to $11 million for soybeans, using conservative assumptions on expected LANDSAT system performance.
Progress in the application of digital analysis of multispectral scanner data to agro-environmental studies is described. Simulation of LANDSAT D thematic mapper (TM) observations from aircraft multispectral scanner data and field spectrometer data collected over a corn-soybean agricultural region in Webster County, Iowa during the 1979 growing season in support of the NASA/AgRISTARS program is described. The simulations were analyzed to evaluate the potential utility of the TM (1.55-1.75 micron) mid-infrared observations in corn-soybean discrimination. Current LANDSAT data was analyzed to study snow cover in northern New England and wetlands in Nebraska and Vermont. The application of satellite remote sensor data in additional environmental research areas is described.
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There are no author-identified significant results in this report.
There are no author-identified significant results in this report.
There are no author-identified significant results in this report.
Remote sensing techniques, particularly LANDSAT data, were used to assess soil moisture stress through crop signature in southwestern Minnesota. Related objectives were: localization of droughty, well drained, and poorly drained soils; detection of stress from hail, wind, and disease damage; and the use of remote sensing data for agricultural management. Since the amount and distribution of precipitation were adequate during the 1977 and 1978 growing seasons, no significant stress occurred. Crop conditions were very favorable. As a result, crop signatures were too uniform to reflect soilscape variations and crop condition changes. In 1979 precipitation was again adequate to excess, particularly in June and August. In some cases, poorly drained sites especially, stress conditions developed as a result of excess of water and could be identified on color infrared photographs.
The results from the U.S. corn/soybeans exploratory experiment which was completed during FY 1980 are summarized. The experiment consisted of two parts: the classification procedures verification test and the simulated aggregation test. Evaluations of labeling, proportion estimation, and aggregation procedures are presented.
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Theory and experiments have shown that passive microwave radiometers can be used to measure soil moisture. However, the presence of a vegetative cover alters the measurement that might be obtained under bare conditions. Deterministically accounting for the effect of vegetation and developing algorithms for extracting soil moisture from observations of a vegetable-soil complex present significant obstacles to the practical use of this approach. The presence of a vegetation canopy reduces the sensitivity of passive microwave instruments to soil moisture variations. The reduction in sensitivity, as compared to a bare-soil relationship, increases as microwave frequency increases, implying that the longest wavelength sensors should provide the most information. Sensitivity also decreases as the amount of vegetative wet biomass increases for a given type of vegetation.