A set of error/uncertainty analyses were performed on several "improved" vegetation indices (VIs) planned for operational use in the Moderate Resolution Imaging Spectroradiometer (MODIS) VI products onboard the Terra (EOS AM-1) and Aqua (EOS PM-1) satellite platforms. The objective was to investigate the performance and accuracy of the satellite-derived VI products under improved sensor characteristics and algorithms. These include the "atmospheric resistant" VIs that incorporate the "blue" band for normalization of aerosol effects and the most widely-used, normalized difference vegetation index (NDVI). The analyses were conducted to evaluate specifically: (1) the impact of sensor calibration uncertainties on VI accuracies, (2) the capabilities of the atmospheric resistant VIs and various middle-infrared (MIR) derived VIs to minimize smoke aerosol contamination, and (3) the performances of the atmospheric resistant VIs under "residual" aerosol effects resulting from the assumptions in the MODIS aerosol correction algorithm. The results of these studies showed both the advantages and disadvantages of using the atmospheric resistant VIs for operational vegetation monitoring. The atmospheric resistant VIs successfully minimized optically thin aerosol smoke contamination (aerosol optical thickness (AOT) at 0.67 μm < 1.0) but not optically thick smoke (AOT at 0.67 μm > 1.0). On the other hand, their resistances to "residual" aerosol effects were greater when the effects resulted from the correction of optically-thick aerosol atmosphere. The atmospheric resistant VIs did not successfully minimize the residual aerosol effects from optically-thin aerosol atmosphere (AOT at 0.67 μm ≤ ∼0.15), which was caused mainly by the possible wrong choice of aerosol model used for the AOT estimation and correction. The resultant uncertainties of the atmospheric resistant Vls associated with calibration, which were twice as large as that of the NDVI, increased with increasing AOT. These results suggest that the atmospheric resistant VIs be computed from partially (Rayleigh/O₃) corrected reflectances under normal atmospheric conditions (e.g., visibility > 10 km). Aerosol corrections should only be performed when biomass burning, urban/industrial pollution, and dust storms (larger AOT) are detected.

The primary objective of this research is to investigate relationships between extremes in central Sierra Nevada tree growth, temperature and precipitation and winter and summer atmospheric circulation. Using existing Sierra Nevada chronologies, I developed two mean chronologies for the period of overlap between instrumental and tree-ring records (1900-1987), one for giant sequoia (Sequoiadendron giganteum) and one for treeline pines (Pinus balfouriana, Pinus albicaulis) and selected the highest and lowest quintiles of tree growth as extreme years. For these years, I constructed and analyzed maps of composite anomalies for the following climatic data: tropospheric pressure (SLP, 700 mb, 500 mb), storm track (positive vorticity advection [PVA], a variable not previously used in dendroclimatology), temperature, precipitation, and snow (a variable often assumed have the same effects on growth as winter precipitation). Results suggest that extreme growth in these trees is associated with distinct patterns of winter atmospheric circulation and snow depth that are consistent with instrumental studies for the Western U.S. The storm track and snow analyses, seldom used in dendroclimatology, added substance to inferences based on analyses of tropospheric and surface climate parameters. This study shows the strong potential for reconstruction of these variables using Sierra Nevada trees. Synthesis of these results suggests that sequoia exhibit low growth during years with meridional winter and summer circulation, winter storms primarily occluded in the Gulf of Alaska, and low snow depth; sequoia exhibit high growth during years with low winter pressure in the north Pacific, long duration storms, a SW-NE oriented storm track entering North America at the California-Oregon border, high snow depth and zonal summer flow. Treeline pines exhibit low growth during years with enhanced ridging over the eastern Pacific, cool, short duration winter storms along a northern track, low snow depth and high east Pacific summer SLP; these pines exhibit high growth during years with warm, long duration winter storms following a southern track, a quasi-PNA atmospheric circulation pattern, average snow depth and a northeastward displaced summer subtropical high. Evidence presented herein suggests that variation in extreme treeline pine growth tracks low frequency changes in north Pacific atmospheric circulation.

Vegetation mapping in and regions facilitates ecological studies, land management, and provides a record to which future land changes can be compared. Accurate and representative mapping of desert vegetation requires a sound field sampling program and a methodology to transform the data collected into a representative classification system. Time and cost constraints require that a remote sensing approach be used if such a classification system is to be applied on a regional scale. However, desert vegetation may be sparse and thus difficult to sense at typical satellite resolutions, especially given the problem of soil reflectance. This study was designed to address these concerns by conducting vegetation mapping research using field and satellite data from the US Army Yuma Proving Ground (USYPG) in Southwest Arizona. Line and belt transect data from the Army's Land Condition Trend Analysis (LCTA) Program were transformed into relative cover and relative density classification schemes using cluster analysis. Ordination analysis of the same data produced two and three-dimensional graphs on which the homogeneity of each vegetation class could be examined. It was found that the use of correspondence analysis (CA), detrended correspondence analysis (DCA), and non-metric multidimensional scaling (NMS) ordination methods was superior to the use of any single ordination method for helping to clarify between-class and within-class relationships in vegetation composition. Analysis of these between-class and within-class relationships were of key importance in examining how well relative cover and relative density schemes characterize the USYPG vegetation. Using these two classification schemes as reference data, maximum likelihood and artificial neural net classifications were then performed on a coregistered dataset consisting of a summer Landsat Thematic Mapper (TM) image, one spring and one summer ERS-1 microwave image, and elevation, slope, and aspect layers. Classifications using a combination of ERS-1 imagery and elevation, slope, and aspect data were superior to classifications carried out using Landsat TM data alone. In all classification iterations it was consistently found that the highest classification accuracy was obtained by using a combination of Landsat TM, ERS-1, and elevation, slope, and aspect data. Maximum likelihood classification accuracy was found to be higher than artificial neural net classification in all cases.

This dissertation presents a geographical analysis of air pollution in the Tucson region. Image processing, geographic information system (GIS), climatological, and statistical tools are used to develop and analyze air pollution-related databases. These databases are then used in conjunction with a limited number of spatial measurements of ozone concentrations to create accurate and theoretically sound ground-level ozone maps. High spatial resolution, gridded, multi-temporal, atmospheric emissions inventories (EIs) of ozone precursor chemical (i.e. volatile organic compounds (VOCs) and nitrogen oxides (NOₓ)) emissions are initially developed. GIS-driven "top-down" and "bottom-up" methods are employed to create anthropogenic VOC and NOx emissions inventories while satellite imagery and field surveys are employed to create biogenic VOC (BVOC) emissions inventories. Accounting for approximately 50% of the anthropogenic emissions, on-road vehicles are the dominant anthropogenic source. The forest and desert lands emit nearly all of the BVOCs within the entire Tucson region while exotic trees such as eucalyptus, pine, and palm emit most of the BVOCs within the City of Tucson. Relationships between VOC and NOₓ emissions, atmospheric conditions, and ambient ozone levels are determined by examining spatio-temporal variations in ozone levels, temporal variations in VOC and NOₓ emissions and atmospheric conditions, atmospheric conditions which are conducive to elevated ozone levels. In addition, the likelihood of ozone transport from Phoenix to Tucson is assessed. The highest ozone levels occur at "rural," downwind monitors, occur in August, and occur during the early afternoon hours. Atmospheric conditions conducive to elevated concentrations differ between the months while inter-city ozone transport is most likely to occur in June. Pooled, cross-sectional, times series, regression models are developed with the aid of cluster analysis and principal components analysis to spatially predict daily maximum 1-hr and 8-hr average ozone concentrations. Gridded, multi-temporal estimates of VOCs and NOₓ emissions are the primary predictor variables in the regression models. The pooled models are reasonably accurate with overall R² values from 0.90 to 0.92, 6 to 7% error, and predicted concentrations that are typically within 0.003 to 0.004 ppm of the observed concentrations. The predicted highest ozone concentrations occur in a monitorless area on the eastern edge of the City of Tucson.

Airborne multispectral video was evaluated as a tool for obtaining urban land cover information for hydrological simulations. Land cover data was obtained for a small urban watershed in Tucson, Arizona using four methods: multispectral aerial video (2 meter and 4 meter pixel resolution), National High Altitude Photography (NHAP), multispectral satellite imagery from Systeme Pour l'Observation de la Terre (SPOT), and by conventional survey. A semi-automated land cover classification produced four classes: vegetation, buildings, pavement, and bare soil. The land cover data from each classification was used as input to a runoff simulation model. Runoff values generate by each simulation were compared to observed runoff. A chi-square goodness-of-fit test indicated that SPOT produced landcover data most similar to the conventional classification. In the curve number model, the SPOT data produced simulated runoff values most similar to observed runoff.

This thesis provides the results of research that explores the relationship between climatic conditions and the incidence of valley fever in Pima County. Valley fever is caused by a soil-dwelling fungus, C. immitis, which responds to changes in climate conditions. Bivariate and compositing analyses provided the basic relationships necessary for the development of monthly multivariate models. The models are designed to predict deviation from mean incidence based on past, current, and forecast climate conditions. Temperature and precipitation are important predictors of incidence, and were used in model development. Winter temperature and precipitation variables were included in the model more frequently than variables in other seasons, and most variables were on the time scale of one year or more prior to the month being predicted. Model results were moderate, and months with high incidence can be predicted more accurately than months with low incidence.

No description available.

Until very recently the south-western part of the Eastern Townships had not received a great deal of attention from geomorphologists; indeed in the Eastern Townships as a whole the work has been essentially of a reconnaissance nature. However, lying as it does at the junction of the Appalachian ridges to the south and the St. Lawrence Lowlands to the north, one might expect it to be interesting from two points of view: firstly in having morphological features common to both areas and secondly in offering the possibility of a comparison between their sequences of development. In recent years the attention has been focussed on two particular topics which reflect increasing awareness of the significance of the area as a field of geomorphological research: the development of pre-glacial topography (Sangree, 1953; Bird, 1961) and studies of glacial geomorphology (Dresser and Denis, 1944; Sangree, 1953; Cooke, 1957). [...]

A micrometeorological station was established on the sea ice at Tanquary Fiord, Northern Ellesmere Island, during the late spring and early summer period of 1964. [...]

The purposes of the present study may be stated as follows : i. To present a logical chronological account of the physiographic development of Melville Peninsula. ii. To trace the major events of the Pleistocene glaciation and deglaciation in Melville peninsula. iii. To discuss the geomorphic processes which are active today in modifying the present surface configuration ofMelville Peninsula. iv. On the basis of the above discussion, to divide the peninsula into physiographic regions and to describe them systematically.