Spectral mixture modeling: Further analysis of rock and soil types at the Viking Lander sites

A new image processing technique was applied to Viking Lander multispectral images. Spectral endmembers were defined that included soil, rock and shade. Mixtures of these endmembers were found to account for nearly all the spectral variance in a Viking Lander image

Compositional variability of the Martian surface

Spectral reflectance data from Viking Landers and Orbiters and from telescopic observations were analyzed with the objective of isolating compositional information about the Martian surface and assessing compositional variability. Two approaches were used to calibrate the data to reflectance to permit direct comparisons with laboratory reference spectra of well characterized materials. In Viking Lander multispectral images (six spectral bands) most of the spectral variation is caused by changes in lighting geometry within individual scenes, from scene to scene, and over time. Lighting variations are both wavelength independent and wavelength dependent. By calibrating lander image radiance values to reflectance using spectral mixture analysis, the possible range of compositions was assessed with reference to a collection of laboratory samples, also resampled to the lander spectral bands. All spectra from the lander images studied plot (in six-space) within a planar triangle having at the apexes the respective spectra of tan basaltic palagonite, gray basalt, and shale. Within this plane all lander spectra fit as mixtures of these three endmembers. Reference spectra that plot outside of the triangle are unable to account for the spectral variation observed in the images

Address Delivered before the Oxford County Agricultural Society

An address to the members of the Oxford County Agricultural Society discussing the role of the American farmer in relation to the wealth, power, and progress of the nation. Adams discusses mid-19th Century, rural attitudes toward the politics, education, business, economy, and social standing of farmers and agriculture in America.https://digitalcommons.library.umaine.edu/mainebicentennial/1072/thumbnail.jp

Why do narcissists disregard social-etiquette norms? A test of two explanations for why narcissism relates to offensive-language use

Narcissists often fail to abide by norms for polite social conduct, but why? The current study addressed this issue by exploring reasons why narcissists use more offensive language (i.e., profanity) than non-narcissists. In this study, 602 participants completed a survey in which they responded on a measure of trait narcissism, rated several offensive words on the degree to which the words were attention-grabbing and offensive, and then indicated how frequently they used the words. Consistent with the idea that narcissists use offensive language to gain attention, narcissists were incrementally more likely to use offensive language if they perceived such language to be highly attention-grabbing, and they were also more likely to perceive offensive language as attention-grabbing. Consistent with the idea that narcissists use more offensive language because they are less sensitive to the offensiveness of the language, an additional mediation analysis showed that narcissists perceived offensive language as less offensive than non-narcissists, a perception that, in turn, enhanced use of offensive language. Thus, this study provides evidence for two mechanisms that underlie narcissists’ frequent use of offensive language, and broadly contributes to the understudied issue of why narcissists violate social-etiquette norms

Using endmembers in AVIRIS images to estimate changes in vegetative biomass

Field techniques for estimating vegetative biomass are labor intensive, and rarely are used to monitor changes in biomass over time. Remote-sensing offers an attractive alternative to field measurements; however, because there is no simple correspondence between encoded radiance in multispectral images and biomass, it is not possible to measure vegetative biomass directly from AVIRIS images. Ways to estimate vegetative biomass by identifying community types and then applying biomass scalars derived from field measurements are investigated. Field measurements of community-scale vegetative biomass can be made, at least for local areas, but it is not always possible to identify vegetation communities unambiguously using remote measurements and conventional image-processing techniques. Furthermore, even when communities are well characterized in a single image, it typically is difficult to assess the extent and nature of changes in a time series of images, owing to uncertainties introduced by variations in illumination geometry, atmospheric attenuation, and instrumental responses. Our objective is to develop an improved method based on spectral mixture analysis to characterize and identify vegetative communities, that can be applied to multi-temporal AVIRIS and other types of images. In previous studies, multi-temporal data sets (AVIRIS and TM) of Owens Valley, CA were analyzed and vegetation communities were defined in terms of fractions of reference (laboratory and field) endmember spectra. An advantage of converting an image to fractions of reference endmembers is that, although fractions in a given pixel may vary from image to image in a time series, the endmembers themselves typically are constant, thus providing a consistent frame of reference

Mapping and monitoring changes in vegetation communities of Jasper Ridge, CA, using spectral fractions derived from AVIRIS images

An important application of remote sensing is to map and monitor changes over large areas of the land surface. This is particularly significant with the current interest in monitoring vegetation communities. Most of traditional methods for mapping different types of plant communities are based upon statistical classification techniques (i.e., parallel piped, nearest-neighbor, etc.) applied to uncalibrated multispectral data. Classes from these techniques are typically difficult to interpret (particularly to a field ecologist/botanist). Also, classes derived for one image can be very different from those derived from another image of the same area, making interpretation of observed temporal changes nearly impossible. More recently, neural networks have been applied to classification. Neural network classification, based upon spectral matching, is weak in dealing with spectral mixtures (a condition prevalent in images of natural surfaces). Another approach to mapping vegetation communities is based on spectral mixture analysis, which can provide a consistent framework for image interpretation. Roberts et al. (1990) mapped vegetation using the band residuals from a simple mixing model (the same spectral endmembers applied to all image pixels). Sabol et al. (1992b) and Roberts et al. (1992) used different methods to apply the most appropriate spectral endmembers to each image pixel, thereby allowing mapping of vegetation based upon the the different endmember spectra. In this paper, we describe a new approach to classification of vegetation communities based upon the spectra fractions derived from spectral mixture analysis. This approach was applied to three 1992 AVIRIS images of Jasper Ridge, California to observe seasonal changes in surface composition

Temporal variation in spectral detection thresholds of substrate and vegetation in AVIRIS images

The ability to map changes over large surface areas over time is one of the advantages in using remote sensing as a monitoring tool. Temporal changes in the surface may be gradual, making them difficult to detect in the short-term, and because they commonly occur at the subpixel scale, they may be difficult to detect in the long-term as well. Also, subtle changes may be real or merely an artifact of image noise. It is, therefore, necessary to understand the factors that limit the detection of surface materials in evaluating temporal data. The spectral detectability of vegetation and soil in the 1990 July and October Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data of Jasper Ridge, CA was evaluated and compared

3. Launching the New Enterprise

As the academic year of 1945-46 approached, the intensity of activity in preparation for actually opening the school in the fall term became overwhelming. Incredible though it may seem, Ives and Day were able in a period of a few weeks to assemble the nucleus of a faculty, several of whom formed a continuing source of counsel and advice both during the school’s formative years and thereafter. Includes: The First Dean and the School’s Dedication; A Participant’s View of the Early Years; Ives Moves On; Several Views of Martin P. Catherwood; The Founders

AVIRIS spectral trajectories for forested areas of the Gifford Pinchot National Forest

A simple mixing model employing reference endmembers (green vegetation, non-photosynthetic vegetation, soil and shade), and using 180 AVIRIS bands, was used to establish an interpretive framework for a forested area in the Pacific Northwest. A regrowth trend, based on changes in the endmember proportions, was defined for conifers that extends from clearcuts to mature forest, and by implication to old growth. Deciduous species within replanted forest plots caused the fractions to be displaced from the main coniferous regrowth trend and to move toward the green vegetation fraction. The results indicate that the spectral information in AVIRIS can be inverted to estimate approximate stand age and relative proportion of deciduous species in the context of the area studied. Using AVIRIS we measured a 3 to 5 percent increase in woody material in old-growth forest, as distinct from other mature forest. This result is consistent with a predicted increase in NPV in old-growth forest, based on field observations. Previous application of the mixing analysis to a TM image of the same area separated old growth based solely on the shade fraction; however the approach required successful removal of shade introduced by topography. Our new results suggest that with the high spectral resolution and high signal-to-noise of AVIRIS images it may be possible to characterize and map old-growth forests in the Northwest using both the NPV fraction and shade

A study of indoor carbon dioxide levels and sick leave among office workers

BACKGROUND: A previous observational study detected a strong positive relationship between sick leave absences and carbon dioxide (CO(2)) concentrations in office buildings in the Boston area. The authors speculated that the observed association was due to a causal effect associated with low dilution ventilation, perhaps increased airborne transmission of respiratory infections. This study was undertaken to explore this association. METHODS: We conducted an intervention study of indoor CO(2) levels and sick leave among hourly office workers employed by a large corporation. Outdoor air supply rates were adjusted periodically to increase the range of CO(2) concentrations. We recorded indoor CO(2) concentrations every 10 minutes and calculated a CO(2) concentration differential as a measure of outdoor air supply per person by subtracting the 1–3 a.m. average CO(2) concentration from the same-day 9 a.m. – 5 a.m. average concentration. The metric of CO(2) differential was used as a surrogate for the concentration of exhaled breath and for potential exposure to human source airborne respiratory pathogens. RESULTS: The weekly mean, workday, CO(2) concentration differential ranged from 37 to 250 ppm with a peak CO(2) concentration above background of 312 ppm as compared with the American Society of Heating, Refrigeration and Air-conditioning Engineers (ASHRAE) recommended maximum differential of 700 ppm. We determined the frequency of sick leave among 294 hourly workers scheduled to work approximately 49,804.2 days in the study areas using company records. We found no association between sick leave and CO(2) differential CONCLUSIONS: The CO(2) differential was in the range of very low values, as compared with the ASHRAE recommended maximum differential of 700 ppm. Although no effect was found, this study was unable to test whether higher CO(2) differentials may be associated with increased sick leave