Geography

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THE EFFECTS OF CHANGES IN LAND COVER AND LAND USE ON NUTRIENT LOADINGS TO THE CHESAPEAKE BAY USING FORECASTS OF URBANIZATION
(2009) Roberts, Allen Derrick; Prince, Stephen D.; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This dissertation examined the effects of land cover and land use (LC/LU) change on nutrient loadings (mass for a specified time) to the Chesapeake Bay, after future projections of urbanization were applied. This was accomplished by quantifying the comprehensive impacts of landscape on nutrients throughout the watershed. In order to quantify forecasted impacts of future development and LC/LU change, the current (2000) effects of landscape composition and configuration on total nitrogen (TN) and total phosphorus (TP) were examined. The effects of cover types were examined not only at catchment scales, but within riparian stream buffer to quantify the effects of spatial arrangement. Using the SPAtially Referenced Regressions On Watershed Attributes (SPARROW) model, several compositional and configurational metrics at both scales were significantly correlated to nutrient genesis and transport and helped estimate loadings to the Chesapeake Bay with slightly better accuracy and precision. Remotely sensed forecasts of future (2030) urbanization were integrated into SPARROW using these metrics to project TN and TP loadings into the future. After estimation of these metrics and other LC/LU-based sources, it was found that overall nutrient transport to the Chesapeake Bay will decrease due to agricultural land losses and fertilizer reductions. Although point and non-point source urban loadings increased in the watershed, these gains were not enough to negate decreased agricultural impacts. In catchments forecasted to undergo urban sprawl conditions by 2030, the response of TN locally generated within catchments varied. The forecasted placement of smaller patches of development within agricultural lands of higher nutrient production was correlated to projected losses. However, shifting forecasted growth onto or adjacent to existing development, not agricultural lands, resulted in projected gains. This indicated the importance of forecasted spatial arrangement to projected TN runoff from the watershed. In conclusion, comprehensive landscape analysis resulted in differences in simulations of current and future nutrient loadings to the Chesapeake Bay, as a result of urbanization and LC/LU change. With eutrophication from excess nutrients being the primary challenge to the estuary, information gained from the estimation of these effects could improve the future management and regulation of the Chesapeake Bay.
AN APPROACH TO ESTIMATE GLOBAL BIOMASS BURNING EMISSIONS OF ORGANIC AND BLACK CARBON FROM MODIS FIRE RADIATIVE POWER
(2009) Ellicott, Evan Andrew; Justice, Christopher O; Vermote, Eric; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Biomass burning is an important global phenomenon affecting atmospheric composition with significant implications for climatic forcing. Wildland fire is the main global source of fine primary carbonaceous aerosols in the form of organic carbon (OC) and black carbon (BC), but uncertainty in aerosol emission estimates from biomass burning is still rather large. Application of satellite based measures of fire radiative power (FRP) has been demonstrated to offer an alternative approach to estimate biomass consumed with the potential to estimate the associated emissions from fires. To date, though, no study has derived integrated FRP (referred to as fire radiative energy or FRE) at a global scale, in part due to limitations in temporal or spatial resolution of satellite sensors. The main objective of this research was to quantify global biomass burning emissions of organic and black carbon aerosols and the corresponding effect on planetary radiative forcing. The approach is based on the geophysical relationship between the flux of FRE emitted, biomass consumed, and aerosol emissions. Aqua and Terra MODIS observations were used to estimate FRE using a simple model to parameterize the fire diurnal cycle based on the long term ratio between Terra and Aqua MODIS FRP and cases of diurnal satellite measurements of FRP made by the geostationary sensor SEVIRI, precessing sensor VIRS, and high latitude (and thus high overpass frequency) observations by MODIS. Investigation of the atmospheric attenuation of MODIS channels using a parametric model based on the MODTRAN radiative transfer model indicates a small bias in FRE estimates which was accounted for. Accuracy assessment shows that the FRE estimates are precise (R2 = 0.85), but may be underestimated. Global estimates of FRE show that Africa and South America dominate biomass burning, accounting for nearly 70% of the annual FRE generated. The relationship between FRE and OCBC estimates made with a new MODIS-derived inversion product of daily integrated biomass burning aerosol emissions was explored. The slope of the relationship within each of several biomes yielded a FRE-based emission factor. The biome specific emission factors and FRE monthly data were used to estimate OCBC emissions from fires on a global basis for 2001 to 2007. The annual average was 17.23 Tg which was comparable to previously published values, but slightly lower. The result in terms of global radiative forcing suggests a cooling effect at both the top-of-atmosphere (TOA) and surface approaching almost -0.5 K which implies that biomass burning aerosols could dampen the warming effect of green house gas emissions. An error budget was developed to explore the sources and total uncertainty in the OCBC estimation. The results yielded an uncertainty value of 58% with specific components of the process warranting future consideration and improvement. The uncertainty estimate does not demonstrate a significant improvement over current methods to estimate biomass burning aerosols, but given the simplicity of the approach should allow for refinements to be made with relative ease.
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.
Idenfitying and Understanding North American Carbon Cycle Perturbations from Natural and Anthropogenic Disturbances
(2008-05-05) Neigh, Christopher Sean; Townshend, John R.G.; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Carbon dioxide accumulating in our atmosphere is one of the most important environmental threats of our time. Humans and changing climate, separately or in concert, have affected global vegetation, biogeochemical cycles, biophysical processes, and primary production. Recent studies have found temporary carbon stores in North American vegetation due to land-cover land-use change, but have yet to characterize regional mechanisms across the continent. This research implemented multi-resolution remote sensing data, coupled with ecosystem simulations, to determine the importance of fine-scale disturbance in our understanding of dynamics that drove and/or perturbed carbon sequestration in North America from 1982 through 2005. The research involved three components: 1) identified large regions with natural and anthropogenic vegetation disturbances; 2) determined causes of disturbances with high-spatial resolution data and mapped associative fine-scale land cover dynamics; and 3) used prior empirical observations in simulations to quantify mechanisms that altered carbon pathways. Investigation of normalized difference vegetation index data from the NOAA series of Advanced Very High Resolution Radiometers found regions in North America that experienced marked increases in photosynthetic capacity at various times from 1982 to 2005. Inspection of anomalies with multi-resolution data from Landsat, IKONOS, aerial photography, and ancillary data revealed a wide range of causes: climatic influences; severe drought and subsequent recovery; irrigated agriculture expansion; insect outbreaks followed by logging and subsequent regeneration; and forest fires with subsequent regeneration. Fine-scale land cover change dynamics were included in Carnegie-Ames-Stanford approach simulations to enhance replication of carbon cycle processes found in empirical observations. Integration of multi-resolution remote sensing data, with carbon ecosystem process modeling, improved regional understanding and accounting of dynamic fine-scale spatial-temporal North American ecosystem carbon balance by a total of ~10 − 250 teragrams of carbon. Coarse resolution simulations could fail to identify important local scale drivers which impact regional carbon balance.
Towards an integrated system for vegetation fire monitoring in the Amazon basin
(2008-04-25) Schroeder, Wilfrid; Justice, Christopher; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Biomass burning is a major environmental problem in Amazonia. Satellite fire detections represent the primary source of information for fire alert systems, decision makers, emissions modeling groups and the scientific community in general. Those various users create a growing demand for good quality fire data of higher spatial and temporal resolution that can only be achieved via integration of multiple satellite fire detection products. The main objective of this dissertation was to develop an integrated fire product capable of improved monitoring and characterization of fire activity in Brazilian Amazonia. Two major active fire detection algorithms based on MODIS and GOES data were used to meet the users demand for fire information. Large differences involving the performance of the MODIS and GOES fire products required the quantification of omission and commission errors in order to allow for appropriate treatment of individual detections produced by each data set. Relatively small omission errors due to cloud obscuration were estimated for Brazilian Amazonia. Regional climate conditions result in reduced cloud coverage in areas of high fire activity during the peak of the dry season, therefore minimizing the effects of cloud obscuration on fire detection omission errors. Clear sky omission and commission errors were largely dependent on the vegetation and background conditions. Relatively large commission errors occurring in high percentage tree cover areas suggested that fire detection algorithms must either be regionalized or incorporate additional tests to provide more consistent fire information across a broader range of surface conditions. Integration of MODIS and GOES fire products using a physical parameter describing fire energy (i.e., fire radiative power) was proven difficult due to limitations involving the interplay between sensor characteristics and the types of fires that occur in Amazonia. As part of this research, a new integrated product was generated based on binary fire detection information derived from MODIS and GOES data, incorporating adjustments to reduce commission and omission errors and optimizing the complementarities among individual detections. These findings made a significant contribution to fire monitoring science in Amazonia and could play an important role in the development of future fire detection algorithms for tropical regions.
Identifying landslide hazards in a tropical mountain environment, using geomorphologic and probabilistic approaches
(2007-12-17) Roa, Jose G; Kearney, Michael S.; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
The objective of this study is the performance, assessing, comparison and validation of a set of three landslide hazard maps: The geomorphological, the multicriteria evaluation (MCE) and the probabilistic (weights of evidence); in order to evaluate its accuracy, advantages and limitations, and finally state its reliability. These approaches were tested in a tropical mountain environment located in the central Venezuelan Andes. The scale of this study is regional. A landslide inventory map was generated through aerial-photointerpretation and by the processing of two sets of Landsat imagery via contrast-widening color composite, given as result the outline of 493 landslide polygons, then given the main role played for a digital elevation model (DEM) as data input, a DEM for the study area was built through remotely sensed data obtained from the shuttle radar topographical mission (SRTM) and optical stereographic imagery provided by the advanced spaceborne thermal emission and reflection radiometer (ASTER) system. Because of the comparative nature of this study, these data was preliminary processed via density analysis in order to establish a common background on the landsliding process - passive factors relationship, which was used later to set up the criteria applied in the geomorphological and multicriteria evaluation (MCE) approaches. As a way of validation, the accuracy and error rate of the three landslide hazard maps were performed by its comparison to the landslide inventory map. It was concluded that although the geomorphological approach achieved a better landslide predictive power for this study area at a regional scale, the remaining procedures can play a complementary role, for example the MCE plays a crucial role in an early assessment of landslide hazard which highlights the needs and improving necessary to achieve a better probabilistic approach, which can be later incorporated in a more objective geomorphological assessment. Results also showed that any methodology can be improved and even empowered by the development of better and more integrated standards for factor maps collection rather that the simplification of them, in that way, further studies at regional scale must explore the remotely sensed imagery capacities for generation of data bases addressing regional susceptibility to landsliding process.
Detection, Evaluation, and Analysis of Global Fire Activity Using MODIS Data
(2006-04-26) Giglio, Louis; Justice, Christopher O; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Global biomass burning plays a significant role in regional and global climate change, and spaceborne sensors offer the only practical way to monitor fire activity at these scales. This dissertation primarily concerns the development, evaluation, and use of the NASA Terra and Aqua MODIS instruments for fire monitoring. MODIS is the first satellite sensor designed specifically for global monitoring of fires. An improved operational fire detection algorithm was developed for the MODIS instrument. This algorithm offers a sensitivity to small, cool fires and minimizes false alarm rates. To support the accuracy assessment of the MODIS global fire product, an operational fire detection algorithm was developed and evaluated for the ASTER instrument, which provides higher resolution observations coincident with the Terra MODIS. The unique data set of multi-year MODIS day and night fire observations was used to analyze the global distribution of biomass burning using five different temporal metrics which included, for the first time, mean fire radiative power, a measure of fire intensity. The metrics show the planetary extent, seasonality, and interannual variability of fire. Recognizing differences in fire activity between morning and afternoon overpasses, the impact of the diurnal cycle of fire activity was addressed using seven years of fire data from the VIRS sensor on-board the TRMM satellite. A strong diurnal cycle was found in all regions, with the time of peak burning varying between approximately 13:00 and 18:30 local time. Given interest in area burned among atmospheric chemical transport and carbon cycle modelers, a data set was developed utilizing the MODIS global fire and vegetation cover products to estimate monthly burned area at 1-degree spatial resolution. The methods, products and results presented in this thesis provide the global change research and fire management communities with products for global fire monitoring and are currently being used in the development of the next generation of operational satellite fire monitoring systems.
Canopy Fuels Inventory and Mapping Using Large-Footprint Lidar
(2005-12-05) Peterson, Birgit; Dubayah, Ralph; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This dissertation explores the efficacy of large-footprint, waveform-digitizing lidar for the inventory and mapping of canopy fuels for utilization in fire behavior simulation models. Because of its ability to measure the vertical structure of forest canopies lidar is uniquely suited among remote sensing instruments to observe the canopy structure characteristics relevant to fuels characterization and may help address the lack of high-quality fuels data for many regions, especially in more remote areas. Lidar data were collected by the Laser Vegetation Imaging Sensor (LVIS) over the Sierra National Forest in California. Various waveform metrics were calculated from the waveforms. Field data were collected at 135 plots co-located with a subset of the lidar footprints. The field data were used to calculate ground-based observations of canopy bulk density (CBD) and canopy base height (CBH). These observed values of CBD and CBH were used as dependent variables in a series of regression analyses using the derived lidar metrics as independent variables. Comparisons of observed and predicted resulted in an r2 of 0.71 for CBD and an r2 of 0.59 for CBH. These regression models were then used to generate grids of CBD and CBH from all of the lidar waveform data in the study area. These grids, along with lidar-derived grids of canopy height, were then used as inputs to the FARSITE (Fire Area Simulator-Model) fire behavior model in a series of simulations. Comparisons between conventionally derived and lidar-based model inputs showed differences between the two sets of data. Specifically, the lidar-derived inputs contained much more spatial heterogeneity. Outputs from FARSITE using the lidar-derived inputs were also compared to outputs using input maps of CBD and CBH generated from field observations. There were significant differences between the two sets of outputs, especially in the frequency and spatial distribution of crown fire. Experiments in manipulating the effective resolution of the lidar-based inputs confirmed that FARSITE outputs are affected by the spatial variability of the input data. Furthermore, a sensitivity analysis demonstrated that FARSITE is sensitive to potential errors in the canopy structure input grids. The results of this dissertation show that lidar can be used effectively to predict CBD and CBH for the purpose of fire behavior modeling and that investment in these lidar-based canopy structure data is worthwhile, especially for forests characterized by significant heterogeneity. This work affirms that lidar is a useful tool for future canopy fuels inventory and mapping.
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 CO2, 23.2 CO, 0.726 CH4, 0.661 NMHC, 2.4 particulates (< 2.5 micron), 1.0 NOx 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.

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