Non-Price Determinants of Automotive Demand: Restyling Matters Most

This paper analyzes market share changes in automobile and light truck submarkets. We find that new product, as measured by restyling, represents the most consistent, dominant determinant of demand. On average a ten percent reduction in relative price would yield only one-tenth the market share impact of a restyling. Alternatively, one would have to double one’s relative advertising expenditures to match the impact of a restyling. Several demand determinants not previously modeled, including rebranding and warranty curtailments, were detrimental to domestic manufacturer market shares. Safety appliance adoptions and changes in vehicle reliability had minimal impact on demand.automobile pricing, warranty, safety appliances, rebranding, reliability

Almond Beverage, Oat Water, and Soaked Soybean Juice: How the Dairy Pride Act Attempts to Remedy Consumer Confusion About Plant-Based Milks

With sales of plant-based milks, such as almond and soy milk, on the rise and dairy industry sales declining, dairy industry supporters are taking issue with plant-based milk products calling themselves “milk.”10 In an effort to combat the “mislabeling” of non-dairy products, a few Senators banded together in an attempt to save the dairy industry by creating the DAIRY PRIDE Act.11 The Act was introduced in an effort to prohibit plant-based milk producers from using the term “milk” on their products and instead use a less misleading name, such as “almond imitation milk” or “soy beverage.”12 This Comment argues that, although the DAIRY PRIDE Act claims to remedy consumer confusion regarding the nutritional value of these plant-based products, the Act’s practical effect is to create anticompetitive issues between the dairy and plant-based milk industries by allowing Congress to pick winners and losers in this space, which could lead to congressional overreach in other markets under the guise of helping the consumer

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

A set of training statistics for the 30 meter resolution simulated thematic mapper MSS data was generated based on land use/land cover classes. In addition to this supervised data set, a nonsupervised multicluster block of training statistics is being defined in order to compare the classification results and evaluate the effect of the different training selection methods on classification performance. Two test data sets, defined using a stratified sampling procedure incorporating a grid system with dimensions of 50 lines by 50 columns, and another set based on an analyst supervised set of test fields were used to evaluate the classifications of the TMS data. The supervised training data set generated training statistics, and a per point Gaussian maximum likelihood classification of the 1979 TMS data was obtained. The August 1980 MSS data was radiometrically adjusted. The SAR data was redigitized and the SAR imagery was qualitatively analyzed

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

Separate holograms of horizontally (HH) and vertically (HV) polarized responses obtained by the APQ-102 side-looking radar were processed through an optical correlator and the resulting image was recorded on positive film from which black and white negative and positive prints were made. Visual comparison of the HH and HV images reveals a distinct dark band in the imagery which covers about 30% of the radar strip. Preliminary evaluaton of the flight line 1 date indicates that various features on the HH and HV images seem to have different response levels. The amount of sidelap due to the look angle between flight lines 1 and 2 is negligible. NASA mission #425 to obtain flightlines of NS-001 MSS data and supporting aerial photography was successfully flown. Flight line 3 data are of very good quality and virtually cloud-free. Results of data analysis for selection of test fields and for evaluation of waveband combination and spatial resolution are presented

Evaluation of SLAR and simulated thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

Kershaw County, South Carolina was selected as the study site for analyzing simulated thematic mapper MSS data and dual-polarized X-band synthetic aperture radar (SAR) data. The impact of the improved spatial and spectral characteristics of the LANDSAT D thematic mapper data on computer aided analysis for forest cover type mapping was examined as well as the value of synthetic aperture radar data for differentiating forest and other cover types. The utility of pattern recognition techniques for analyzing SAR data was assessed. Topics covered include: (1) collection and of TMS and reference data; (2) reformatting, geometric and radiometric rectification, and spatial resolution degradation of TMS data; (3) development of training statistics and test data sets; (4) evaluation of different numbers and combinations of wavelength bands on classification performance; (5) comparison among three classification algorithms; and (6) the effectiveness of the principal component transformation in data analysis. The collection, digitization, reformatting, and geometric adjustment of SAR data are also discussed. Image interpretation results and classification results are presented

Basic Forest Cover Mapping Using Digitized Remote Sensor Data and Automatic Data Processing Techniques

Increasing demands on the forest resource will necessitate increasingly more intensive management in the future. In order to achieve this goal, reliable and timely information over large geographic areas will be required. Remote sensing techniques offer much potential for the procurement of such information. This research, then, was pointed toward study of that potential. Four objectives were established as follows: 1) to determine the optimum number of the available twelve multispectral scanner (MSS) wavelength bands to use for forest cover mapping with automatic data processing (ADP) techniques; 2) to determine the current capability to map basic forest cover using MSS data and ADP techniques; 3) to determine the relative utility, to forest cover mapping, of the four spectral regions available in the twelve-channel MSS data (i.e. visible, and near, middle and thermal infrared); and 4) to compare the accuracy of digitized color infrared photography with that of MSS data for forest cover mapping using ADP techniques. In attaining the first objective, statistics defining the six cover type classes of interest (deciduous forest, coniferous forest, water, forage, corn, and soybeans) were calculated and used by the computer as a basis for the selection of best wavelength band combinations ranging in size from one through ten wavelength bands each. With the spectral information contained in each of these combinations, and with all twelve channels, the entire test area was classified into the six defined classes, using the LARSYS programs. Tests of the computer\u27s performance indicated that the use of five wavelength bands would fulfill the dual requirements of adequate accuracy and moderate computer time. In fulfilling the second objective, the automatically selected best combination of five channels (one each from the green and red visible wavelengths, and the near, middle and thermal infrared wavelengths) produced classification accuracies in excess of 90 percent for deciduous and coniferous forest. When these two classes were grouped, the accuracy for combined forest was in excess of 95 percent. The use of all twelve channels caused only a slight increase in overall accuracy. In satisfying the third objective, the LARSYS feature selection processor was allowed to consider wavelength bands constituting only various subsets of the four spectral regions. On this basis, it selected a number of five-channel combinations. Classifications performed by these various channel combinations indicate that the visible wavelengths are sufficiently accurate for classifying combined forest, but inadequate for differentiating between deciduous and coniferous forest. The infrared channels separated the two forest classes with reasonable accuracy, but allowed confusion between forest and the agricultural classes. The deletion of either the near or the middle infrared individually, did not reduce accuracies, but, when both were deleted, accuracies dropped drastically. The deletion of the thermal infrared had little effect on forest cover mapping but did allow considerable confusion among the agricultural cover types. These results indicate that the thermal infrared is desirable, but not necessary, for basic forest cover mapping, and that accurate classification of deciduous and coniferous forest cover can be achieved with the visible plus either the near or middle infrared spectral regions. To meet the fourth objective, small-scale color infrared photography, acquired the same day over the test site, was color separated, digitized in three wavelength bands and, automatically classified. In general, the digitized photography was inadequate for automatic forest cover mapping and compared poorly to the MSS data results when similar wavelength bands were used. These results were apparently caused by the narrower dynamic range, poorer spectral resolution, and uneven illumination (due to vignetting and the anti-solar point) of the photographic data

Agricultural scene understanding

The author has identified the following significant results. The LACIE field measurement data were radiometrically calibrated. Calibration enabled valid comparisons of measurements from different dates, sensors, and/or locations. Thermal band canopy results included: (1) Wind velocity had a significant influence on the overhead radiance temperature and the effect was quantized. Biomass and soil temperatures, temperature gradient, and canopy geometry were altered. (2) Temperature gradient was a function of wind velocity. (3) Temperature gradient of the wheat canopy was relatively constant during the day. (4) The laser technique provided good quality geometric characterization