The accurate determination of cloud cover amount is important for characterizing the role of cloud feedbacks in the climate system. Clouds have a large influence on the climate system through their effect on the earth's radiation budget. As indicated by the NASA Earth Radiation Budget Experiment (ERBE), the change in the earth's radiation budget brought about by clouds is ~-15 Wm⁻² on a global scale, which is several times the ~4 Wm⁻² gain in energy to the troposphere-surface system that would arise from a doubling of CO₂ in the atmosphere. Consequently, even a small change in global cloud amount may lead to a major change in the climate system. Threshold methods are commonly used to derive cloud properties from satellite imagery data. Here, in order to quantify errors due to thresholds, cloud cover is obtained using three different values of thresholds. The three thresholds are applied to the 11 μm, (4 km)² NOAA-9 AVHRR GAC satellite imagery data over four oceanic regions. Regional cloud-cover fractions are obtained for two different scales, (60 km)² and (250 km)². The spatial coherence method for obtaining cloud cover from imagery data is applied to coincident data. The differences between cloud cover derived by the spatial coherence method and by the threshold methods depends on the setting of the threshold. Because the spatial coherence method is believed to provide good estimates of cloud cover for opaque, single-layered cloud systems, this study is limited to such systems, and the differences in derived cloud cover are interpreted as errors due to the application of thresholds. The threshold errors are caused by pixels that are partially covered by clouds and the errors have a dependence on the regional scale cloud cover. The errors can be derived from the distribution of pixel-scale cloud cover. Two simple models which assume idealized distributions for pixel-scale cloud cover are constructed and used to estimate the threshold errors. The results show that these models, though simple, perform rather well in estimating the differences between cloud cover derived by the spatial coherence method and those obtained by threshold methods. / Graduation date: 1992

Physical-biological interactions in the Southern Ocean were investigated using remote sensing data from several different satellite sensors. Satellite sea surface temperature data were used to study the dynamics of the Antarctic Polar Front (PF). Satellite ocean color data were used to estimate surface chlorophyll concentrations and their relation to various physical forcings within the Southern Ocean. A detailed study of phytoplankton blooms at the Antarctic Polar Front revealed that elevated chlorophyll concentrations (phytoplankton blooms) occur most often in areas where the PF interacts with large topographic features within the Southern Ocean. The physical dynamics of the PF are strongly influenced by the topography, and in turn strongly influence phytoplankton bloom dynamics. The analysis of satellite data from the modern Southern Ocean indicates that phytoplankton are limited by the availability of the micronutrient iron in most areas. This iron-limitation implies that the elevated iron inputs during glacial periods would have led to increased phytoplankton primary and export production and a stronger sink for atmospheric CO��� in the Southern Ocean. / Graduation date: 2000

Multispectral aerial and satellite remote sensing plays a major role in crop yield prediction due to its ability to detect crop growth conditions on spatial and temporal scales in a cost effective manner. Many empirical relationships have been established in the past between spectral vegetation indices and leaf area index, fractional ground cover, and crop growth rates for different crops through ground sampling. Remote sensing-based vegetation index (VI) yield models using airborne and satellite data have been developed only for grain crops like barley, corn, wheat, and sorghum. So it becomes important to validate and extend the VI-based model for tuber crops like potato, taking into account the most significant parameters that affect the final crop yield of these crops.

Much conservation work focuses on individual species, partly because of the perception that wildlife species are effective symbols for raising funds and drawing awareness to environmental causes. However, for species-based studies to aid conservation efforts, the biological and ecological needs of species need to be addressed in a way that informs decisions and provides concrete recommendations for land managers. This thesis addresses the forest cover needs of Ciconia stormi, a rare and understudied bird species that inhabits the islands of Borneo and Sumatra and parts of peninsular Malaysia. Levels of forest canopy cover associated with areas inhabited by Ciconia stormi are identified at multiple spatial resolutions using a 500m MODIS soft classification product, 30m Landsat data, and hemispherical photographs. Important threshold values of 75 percent tree cover was identified at the regional scale, and 85 percent at foraging sites. There has been severe forest disturbance in regions inhabited by Ciconia stormi between 1993 and 2004, indicating the species may be somewhat tolerant to disturbance. Areas having been logged at least 20 years before present average over 85 percent canopy cover and have few large gaps, indicating that these forests may be suitable habitat for the species.

Many large terrestrial ecosystems have patterned landscapes as a result of a positive feedback system between vegetation communities and environmental factors. One example is tree island habitats in the Florida Everglades. Although they only occupy a small portion of the Everglades landscape, tree islands are important features as the focus of nutrient accumulation and wildlife biodiversity in the Everglades ecosystem. The hardwood hammock community on the elevated head of tree island habitats can accumulate high phosphorus concentration in the otherwise P-limited Everglades ecosystem. In this dissertation, I examined two hypotheses derived from the chemohydrodynamic nutrient accumulation model, which suggests that high transpiration of tree island hammock plants is the driving force for nutrient accumulation in tree island soil. According to this model, I hypothesized that tree islands with lower dry season transpiration should have less phosphorus accumulated than the tree islands with higher dry season transpiration. By examining the water use and nutrient status from 18 tree islands in both slough (perennially wet) and prairie (seasonally wet) locations, I was able to compare water availability and nutrient accumulation in slough and prairie tree islands with different marsh hydroperiods. Chapter 1 uses elemental and stable isotope analysis to look at water stress and nutrient concentration in tree island plants. I showed that the prairie tree island plants suffer from drought stress during the dry season, when the marshes in the prairies dry out. Prairie tree islands also have lower soil and plant P concentration than the slough tree islands. Moreover, I showed that foliar N isotope ratio serves as a stable proxy for community level P availability for tree island plants, and prairie tree island plants have less P available than slough tree island plants. In Chapter 2, I showed that the satellite imagery derived normalized difference water index (NDWI) provides a robust indicator of community level canopy water content of these tree islands. NDWI, used as a proxy for water status, was positively related to foliar N isotope ratio, which suggests that water availability is linked to nutrient availability in the tree island hardwood hammock plant communities. These findings are consistent to the chemohydrodynamic nutrient accumulation model. In Chapter 3, I used sap flow sensors on individual trees to provide a real-time measurement of plant transpiration. I showed that tree island plant transpiration is affected by multiple factors including weather fluctuations, marsh water depth regulated by local water management, and canopy structure of different tree islands. Overall, my dissertation establishes a link between tree island plant water use and nutrient accumulation. It could be potentially important for future restoration plan of tree islands and Everglades hydrological management.

Thesis (Ph. D.)--Oregon State University, 2005. / "November 2005." Includes bibliographical references. Also available via Internet.

Rio Grande wild turkey (RGWT) abundance in portions of the Edwards Plateau has declined steadily since the late 1970s as compared to other areas of the Edwards Plateau where populations have exhibited no trend. The reasons for this decline remain unclear. Possible factors include changes in habitat, and increased human population. The overall objective of this study was to identify landscape changes and habitat characteristics that affect RGWT populations using spatial analysis and modeling at multiple spatial scales. Specific objectives for this study included the quantification of flood-induced landscape changes between 1972 and 1995 along the Medina River bottomlands and their impact on RGWT habitat, the quantification of landscape characteristics of stable and declining study sites in the Edwards Plateau, and the development and evaluation of a GIS-based habitat-suitability model for female RGWTs during the breeding season that will allow the assessment of the spatial distribution of adequate habitat in the Edwards Plateau.The analysis of the landscape characteristics along the North Prong Medina River due to flooding in 1978 had a negative impact on RGWT habitat. Changes in the spatial distribution of woody cover in the bottomlands and the removal of woody cover along riparian zones most likely limited habitat use and dispersal of RGWT along the North Prong Medina River. The analysis of landscape characteristics in sites with stable and declining of RGWTs populations showed that disturbance and a high proportion of woody cover were important factors influencing RGWT populations in areas where turkey numbers had declined. Landscape attributes were used as habitat variables to develop a habitat-suitability model for female RGWTs during the breeding season. The model performed well in characterizing high-suitability habitat for adult female RGWT during the breeding season in the study areas. The use of two scales relevant to RGWT provided important information about the high-suitability areas for female RGWT in stable and declining sites in the Edwards Plateau.

Mixed grasslands in south Canada serve a variety of economic, environmental and ecological purposes. Numerical modeling has become a major method used to identify potential grassland ecosystem responses to environment changes and human activities. In recent years, the focus has been on process models because of their high accuracy and ability to describe the interactions among different environmental components and the ecological processes. At present, two commonly-used process models (CENTURY and BIOME-BGC) have significantly improved our understanding of the possible consequences and responses of terrestrial ecosystems under different environmental conditions. However, problems with these models include only using site-based parameters and adopting different assumptions on interactions between plant, environmental conditions and human activities in simulating such complex phenomenon. In light of this shortfall, the overall objective of this research is to integrate remote sensing products into ecosystem process model in order to simulate productivity for the mixed grassland ecosystem in the landscape level. Data used includes 4-years of field measurements and diverse satellite data (System Pour lObservation de la Terre (SPOT) 4 and 5, Landsat TM and ETM, Advanced Very High Resolution Radiometer (AVHRR) imagery). <p>Using wavelet analyses, the study first detects that the dominant spatial scale is controlled by topography and thus determines that 20-30 m is the optimum resolution to capture the vegetation spatial variation for the study area. Second, the performance of the RDVI (Renormalized Difference Vegetation Index), ATSAVI (Adjusted Transformed Soil-Adjusted Vegetation Index), and MCARI2 (Modified Chlorophyll Absorption Ratio Index 2) are slightly better than the other VIs in the groups of ratio-based, soil-line-related, and chlorophyll-corrected VIs, respectively. By incorporating CAI (Cellulose Absorption Index) as a litter factor in ATSAVI, a new VI is developed (L-ATSAVI) and it improves LAI estimation capability by about 10%. Third, vegetation maps are derived from a SPOT 4 image based on the significant relationship between LAI and ATSAVI to aid spatial modeling. Fourth, object-oriented classifier is determined as the best approach, providing ecosystem models with an accurate land cover map. Fifth, the phenology parameters are identified for the study area using 22-year AVHRR data, providing the input variables for spatial modeling. Finally, the performance of popular ecosystem models in simulating grassland vegetation productivity is evaluated using site-based field data, AVHRR NDVI data, and climate data. A new model frame, which integrates remote sensing data with site-based BIOME-BGC model, is developed for the mixed grassland prairie. The developed remote sensing-based process model is able to simulate ecosystem processes at the landscape level and can simulate productivity distribution with 71% accuracy for 2005.

The objective of this Ph.D. project is to investigate Arctic middle atmosphere chemistry using solar infrared absorption spectroscopy. These measurements were made at the Polar Environment Atmospheric Research Laboratory (PEARL) at Eureka, Nunavut, which is operated by the Canadian Network for the Detection of Atmospheric Change (CANDAC). This research is part of the CANDAC/PEARL Arctic Middle Atmosphere Chemistry theme and aims to improve our understanding of the processes controlling the stratospheric ozone budget using measurements of the concentrations of stratospheric constituents. The instrument, a Bruker IFS 125HR Fourier transform infrared (FTIR) spectrometer, has been specifically designed for high-resolution measurements over a broad spectral range and has been used to measure reactive species, source gases, reservoirs, and dynamical tracers at PEARL since August 2006. The first part of this research focuses on the optimization of ozone retrievals, for which 22 microwindows were studied and compared. The spectral region from 1000 to 1005 cm-1 was found to be the most sensitive in both the stratosphere and troposphere, giving the highest number of independent pieces of information and the smallest total error for retrievals at Eureka. iii Similar studies were performed in coordination with the Network for the Detection of Atmospheric Composition Change for nine other species, with the goal of improving and harmonizing the retrieval parameters among all Infrared Working Group sites. Previous satellite validation exercises have identified the highly variable polar conditions of the spring period to be a challenge. In this work, comparisons between the 125HR and ACE-FTS (Atmospheric Chemistry Experiment-Fourier transform spectrometer) from 2007 to 2010 have been used to develop strict criteria that allow the ground and satellite-based instruments to be confidently compared. After applying these criteria, the differences between the two instruments were generally small and in good agreement with previous ground-based FTIR/ACE-FTS comparisons. No clear bias was seen from year-to-year, and, in all cases, the difference between the measurements was within one standard deviation. The mean biases between the ACE-FTS and 125HR partial columns for 2007-2010 were -5.61 to 1.11%, -0.23 to 4.86%, -15.33 to -2.86%, -4.77 to 1.09%, and -0.34 to 5.23% for O3, HCl, ClONO2, HNO3, and HF, respectively. The 125HR measurements and three atmospheric models (CMAM-DAS, GEM-BACH, and SLIMCAT) were used to derive an NOy partial column data product for Eureka. This data product includes the five primary species NO, NO2, HNO3, N2O5, and ClONO2 and was used to study the seasonal and interannual variability of NOy from 2007 to 2010. The NOy 15-40 km partial column was found to be approximately constant through the sunlit part of the year, with greater variability during the spring. The mean partial column averaged for the spring period was (2.5±0.2)x1016 molec cm-2, while for the summer, it was (2.3±0.1)x1016 molec cm-2. The springtime evolution of NOy and its constituent nitrogen species, was also examined for all four years. The variability of the 5-NOy partial column was seen to be dominated by that of HNO3. iv The evolution of the individual nitrogen species was found to be consistent with the current understanding of the chemical and dynamical processes that occur in the polar stratosphere. Unusually low ozone columns were measured at Eureka from mid-February to late March 2011 and compared to the previous 14 years of measurements by the 125HR and its predecessor, Environment Canada’s Bomem DA8. The normalized O3/HF, HCl/HF, and HNO3/HF ratios, for which the effects of dynamics have been reduced, also showed record minima over this period. The SLIMCAT chemical transport model was used to quantify chemical ozone loss using the passive subtraction method. Chemical ozone depletion inside the vortex above Eureka was estimated to be 35%, which is the largest observed there in the past 15 years.

This thesis addresses the problem of refocusing smeared SAR images caused by ionosphere phase scintillation noise. A SAR data is smeared when the received signal experiences phase irregularities due to platform orbit deviation, target movement, or, in this thesis, ionospheric scintillation noise due to trans-ionosphere propagation is analyzed. A SAR simulator is constructed to generate stripmap and spotlight data that satisfy theoretically predicted performances under ideal conditions. The simulator is incorporated with ionospheric phase scintillation models to analyze the broadening effect on system’s PSF. Degraded simulation spotlight data are used to test the proposed compensation algorithm. This thesis proposes a two-dimensional polynomial phase fitting algorithm to compensate scintillation noise. This work discusses some requirements of the scene in order to carry out the compensation and what is gained and lost in the process. A successful application of the proposed algorithm to TerraSAR-X data is also presented.