Geography Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/2773

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    Estimation of land surface radiation budget from MODIS data
    (2008-08-04) Kim, Hye-Yun; Liang, Shunlin; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Land Surface Radiation Budget (SRB) is responsible for the available energy between the Earth and atmosphere system. Net radiation is the driving force for the transportation and exchange of all matter at the interface between the Earth's surface and the atmosphere, and therefore, significantly affects the climatic forming and change. Accurate estimation of shortwave net radiation (Sn), cloudy-sky allwave net radiation (Rn), and daily integrated Sn at high spatial resolution is essential in regional and global land surface models. The current SRB products have fine temporal and coarse spatial resolutions not suitable for land applications. New hybrid algorithm for Sn estimation has been developed in this study. Sn is estimated from MODIS data under both clear- and cloudy-sky conditions without requiring coarser resolution ancillary data. Therefore, estimated Sn retains the spatial resolution of the raw input data. Surface all-wave (both shortwave and longwave) net radiation (Rn) controls the input of latent and sensible heat flux into the atmosphere over the Earth's surface. Meteorological datasets are spatially limited and satellite data have the advantage of global spatial coverage; however, difficulty in accurately estimating cloudy-sky longwave net radiation (Ln) undermines efforts to estimate cloudy-sky all-wave net radiation. This study presents methods for estimating cloudy-sky Rn using Sn and other surface variables at 1 km spatial resolution. Daily integrated Sn is closely related to carbon, water and energy flux simulations. A daily integrated Sn product with a 1-km spatial resolution supports recent high resolution numerical climate and ecosystem simulations. This study describes a method for estimating daily integrated Sn in 1 km resolution based on instantaneous Sn data. All these algorithms have been validated using seven sites of a SURFace RADiation budget observing network (SURFRAD) in United States, instantaneous Sn is also compared with GEWEX/SRB and ISCCP data. The new hybrid algorithm developed in the study can be easily implemented to generate operational global products. These finer spatial resolution datasets capture the specific sequence of the redistribution of the available energy at the Earth's surface; therefore, they support recent high resolution land surface models.
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    IMPACT OF CLIMATE CHANGE ON WILDLAND FIRE THREAT TO THE AMUR TIGER AND ITS HABITAT
    (2008-05-09) Loboda, Tatiana V; Justice, Christopher O; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Global biodiversity is increasingly threatened by combined pressures from human- and climate-related environmental change. Projected climate change indicates that these trends are likely to continue and may accelerate by the end of this century leading to large scale modification of species habitats. Such modification will be amplified by an increase in catastrophic natural events such as wildland fire - one of the dominant disturbance agents in boreal and temperate forests of the Russian Far East (RFE). In the RFE, large fire events lead to abrupt, extensive, and long-term conversion of forests to open landscapes, thus considerably impacting the habitat of the critically endangered Amur tiger (Panthera tigris altaica). A remotely sensed data-driven regional fire threat model (FTM) is developed to assess current and projected fire threat to the Amur tiger under scenarios of climate change. The FTM is parameterized to account for regional specifics of fire occurrence in the RFE and fire impacts on the Amur tigers, their main prey, and their habitat. Fire regimes are shown to be strongly influenced by anthropogenic use of fire and the monsoonal climate of the RFE, with large fire seasons observed during uncharacteristically dry years. Even with a large proportion of human ignition sources and periodic extreme events, fire currently poses a limited threat to the Amur tiger meta-population. The observed peaks in high fire threat conditions are localized in space and time and are likely to impact a small number of individual tigers. Under the wide range of the IPCC climate change scenarios, no considerable change in fire danger is expected by the mid-21st century. However, by the end of the 21st century under the A2 (regional self-reliance) scenario of the IPCC Special Report on Emissions, fire danger over the southern part of the RFE is predicted to increase by nearly 15%. An overlap of areas of likely increase in fire danger with areas of highest tiger habitat quality results in a 20% mean yearly increase in fire threat with a mean monthly increase of ~40% in August. The results have implications for conservation strategies aimed at securing long-term habitat availability.
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    Fire Dynamics and Woody Cover Changes in the Serengeti-Mara Ecosystem 2000 to 2005 - A Remote Sensing Approach
    (2007-01-21) Dempewolf, Jan; DeFries, Ruth; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The Serengeti-Mara savanna environment in East Africa is characterized by changing levels of woody cover and a dynamic fire regime. The relative proportion of woodland to grassland savanna affects animal habitat, biodiversity, and carbon storage, and is regulated by factors such as the fire regime (frequency, intensity, seasonality), and precipitation. The main objectives of this dissertation are to determine recent changes in woody cover at a regional scale and identify fire regimes and climate associated with these changes. Understanding these relationships is important for the assessment of future trajectories of woody cover under changing climate. Required spatially coherent data layers can only be obtained at the regional scale through the analysis of remote sensing data. Woody cover changes between 2000 and 2005 were derived from field data and a time series of MODIS satellite imagery at 500 m spatial resolution. Data layers on the controlling variables (fire frequency, seasonality, intensity and rainfall) were developed using a combination of remote sensing and model-based approaches. Burned areas were mapped using daily MODIS imagery at 250 m resolution. Outputs were used to make the requisite layers depicting fire frequency and seasonality. Fire intensity was derived using a model based on empirical relationships, mainly estimating fire fuel load as a function of rainfall and grazing. The combined data layers were analyzed using regression and decision tree techniques. Results suggest woody cover in central and northern Serengeti National Park continued to increase after 2000. Woody cover decreases were strongest in the wider Maswa Game Reserve area (MSW) under low precipitation conditions and late season burning. Woody cover losses in burned areas were also higher in the low fire frequency region of the Maasai Mara National Reserve (MNR). Fire seasonality was the most important fire regime parameter controlling woody cover in burned woodland savanna areas while fire intensity was most relevant for grassland savanna areas. Continued late season burning in drought years might cause further decrease of woody cover in MSW. MNR is expected to continue to be dominated by grassland savanna at similar fire frequency and browsing levels.
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    Effects of scale and spatial variability on hydraulic geometry in the Potomac River Basin
    (2006-02-01) Read, Chung Hye Kim; Thompson, Derek; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Scale issues in hydrology arise because different hydrological processes are dominant at different regional scales. Recent hydrological research suggests that the geographic scale (size) of watersheds may influence the behavior of hydraulic geometry exponents (b and f, but not m values) of stream channels. Hence, the working hypothesis of this study is that variations of hydraulic geometry exponents are not random, but that there are systematic changes as a function of geographic scale as well as of water basin and channel physical and environmental characteristics (predictor variables). To support this analysis, 43 subbasins in the Potomac River Basin ranging in size from 0.38 square miles to 1,642 square miles and representing a broad spatial diversity of predictor variables within the watershed were selected for study. Research goals were to attempt, via empirical correlations, to discern relationships between a geographic scale factor and b, f, and m values, to investigate the roles of predictor variables on b, f, and m values, and their statistical significance, and to identify the most influential predictor variables and the complexity of fluvial physical processes via stepwise multi-variable regressions. Statistical evidence was found that there is a relationship between geographic scale and hydraulic geometry exponents. In every selected predictor variable case, investigation of the correlations between b, f, and m with a single selected predictor variable in a scale context resulted in a noticeable improvement over the correlations of the hydraulic exponents with each individual predictor variable alone. The research shows that, under higher discharges, the behavior of b, f, and m mainly result in higher m and f, with a slight increase in cross-sectional area (f with negative b) in a scale context.
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    MODELING OF SEASONAL TRACE GAS AND PARTICULATE EMISSIONS FROM VEGETATION FIRES IN SOUTHERN AFRICA
    (2004-04-29) Korontzi, Stefania; Justice, Christopher O; Geography
    Fire is widespread in southern African savannas with important implications for tropical and global atmospheric chemistry. However, previous regional emission studies have not fully accounted for the variability of the emissions throughout the burning season and the associated impacts on emissions quantification. The main aim of this study is to address this gap. The complexity of the emissions process is described using a spatially and temporally explicit modeling approach that integrates recently published satellite-driven fuel load amounts, satellite burned area products, and empirically derived parameterizations of combustion completeness and emission factors. To represent fire behavior characteristics, land cover is classified into grasslands and woodlands, using a satellite-derived percent tree cover product. The combustion completeness is modeled as a function of grass fuel moisture and the emission factors as a function of grass fuel moisture in grasslands and fuel mixture in woodlands. Fuel moisture is derived from a fuel load model and by using satellite vegetation index time series. A sensitivity analysis with respect to three satellite burned area products reveals large differences in emissions due to differences in their amounts and spatial distribution. The analysis at the regional scale shows, that early burning in grasslands may lead to higher amounts of products of incomplete combustion despite the lower amounts of fuel consumed, compared with late dry season burning. In contrast, early burning in woodlands results in lower emissions because less fuel gets consumed. These seasonal emissions trends become more pronounced when the fuels are wetter. Burning in woodlands dominates the regional emissions budgets. Emissions estimates for various atmospheric species, many of which are modeled for the first time, are reported and compared with other regional sources of pyrogenic emissions and global biomass burning and fossil fuel emissions. The modeled estimates for 2000 are (in Tg): 537 CO<sub>2</sub>, 23.2 CO, 0.726 CH<sub>4</sub>, 0.661 NMHC, 2.4 particulates (< 2.5 micron), 1.0 NO<sub>x</sub> and account for significant fractions of regional emissions from all pyrogenic sources. Especially high is the previously undetermined contribution of Oxygenated Volatile Organic Compounds (1.8 Tg). The methodology and results have direct implications for national reporting of savanna fire emissions.