Geography
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Item Characterizing tree species diversity in the tropics using full-waveform lidar data(2019) Marselis, Suzanne; Dubayah, Ralph; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Tree species diversity is of paramount value to maintain forest health and to ensure that forests are able to provide all vital functions, such as creating oxygen, that are needed for mankind to survive. Most of the world’s tree species grow in the tropical region, but many of them are threatened with extinction due to increasing natural and human-induced pressures on the environment. Mapping tree species diversity in the tropics is of high importance to enable effective conservation management of these highly diverse forests. This dissertation explores a new approach to mapping tree species diversity by using information on the vertical canopy structure derived from full-waveform lidar data. This approach is of particular interest in light of the recently launched Global Ecosystem Dynamics Investigation (GEDI), a full-waveform spaceborne lidar. First, successful derivation of vertical canopy structure metrics is ensured by comparing canopy profiles from airborne lidar data to those from terrestrial lidar. Then, the airborne canopy profiles were used to map five successional vegetation types in Lopé National Park in Gabon, Africa. Second, the relationship between vertical canopy structure and tree species richness was evaluated across four study sites in Gabon, which enabled mapping of tree species richness using canopy structure information from full-waveform lidar. Third, the relationship between canopy structure and tree species richness across the tropics was established using field and lidar data collected in 16 study sites across the tropics. Finally, it was evaluated how the methods and applications developed here could be adapted and used for mapping pan-tropical tree species diversity using future GEDI lidar data products.Item Integrated use of Landsat and Corona data for long-term monitoring of forest cover change and improved representation of its patch size distribution(2016) Song, Danxia; Townshend, John R; Huang, Chengquan; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Forest cover change has profound impact on global carbon cycle, hydrological processes, energy balance, and biodiversity. The primary goal of this dissertation is to improve forest cover change characterization by filling a number of knowledge gaps in forest change studies. These include use of Corona data to extend satellite based forest cover change mapping back to pre-Landsat years in the 1960s, quantification of forest cover change over four decades (1960s – 2005) for a major forested province in China using Corona and Landsat data, and development of more accurate patch size-frequency modeling methods for improved representation of forest disturbances in ecosystem and other spatially explicit models. With comprehensive data coverages in the 1960s, Corona data can be used to extend Landsat-based forest change analysis by up to a decade. The usefulness of such data, however, is hindered by poor geolocation accuracy and lack of multi-spectral bands. In this study, it was demonstrated that combined use of texture features and the advanced support vector machines allowed forest mapping with accuracies of up to 95% using Corona data. Further, a semi-automated method was developed for rapid registration of Corona images with residual errors as low as 100 m. These methods were used to assess the forest cover in the 1960s in Sichuan, a major forest province in China. Together with global forest cover change products derived using Landsat data, these results revealed that the forest cover in Sichuan Province was reduced from 45.19% in the 1960s to 38.98% by 1975 and further down to 28.91% by 1990. It then stayed relatively stable between 1990 and 2005, which contradicted trends reported by inventory data. The turning point between sharp decreases before 1990 and the stable period after 1990 likely reflected transitions in forest policies from focuses on timber production to forest conservation. Representation of forest disturbances in spatially explicit ecosystem models typically relies on patch size-frequency models to allocate an appropriate amount of disturbances to each patch size level. Existing patch size-frequency models, however, do not provide accurate representation of the total disturbance area nor the patch sizes at each frequency level. In this study, a hierarchical method was developed for modeling patch size-frequency distribution. Evaluation of this method over China revealed that it greatly improved the accuracy in representing the patch size at different frequency levels and reduced error in total disturbance area estimation over existing methods from around 40% to less than 10%. The significance of this dissertation is the contribution to improve the characterization of forest cover change by extending the satellite-based forest cover change monitoring back to the 1960s and developing a more accurate patch size distribution model to represent the forest disturbance in ecosystem models. The work in the dissertation has a broader impact beyond developing methods and models, as they provide essential basis to understand the relationship between the long-term change of forest and the socioeconomic transitions. They also improve the capacities of ecosystem and other spatially explicit models to simulate the vegetation dynamics and the resultant biodiversity and carbon dynamics.Item THE UNCERTAINTY OF SPACEBORNE OBSERVATION OF VEGETATION STRUCTURE IN THE TAIGA-TUNDRA ECOTONE: A CASE STUDY IN NORTHERN SIBERIA(2015) Montesano, Paul; Dubayah, Ralph; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The ability to characterize vegetation structure in the taiga-tundra ecotone (TTE) at fine spatial scales is critical given its heterogeneity and the central role of its patterns on ecological processes in the high northern latitudes and global change scenarios. This research focuses on quantifying the uncertainty of TTE forest structure observations from remote sensing at fine spatial scales. I first quantify the uncertainty of forest biomass estimates from current airborne and spaceborne active remote sensing systems and a planned spaceborne LiDAR (ICESat-2) across sparse forest gradients. At plot-scales, current spaceborne models of biomass either explain less than a third of model variation or have biomass estimate uncertainties ranging from 50-100%. Simulations of returns from the planned ICESat-2 for a similar gradient show the uncertainty of near-term estimates vary according to the ground length along which returns are collected. The 50m length optimized the resolution of forest structure, for which there is a trade-off between horizontal precision of the measurement and vertical structure detail. At this scale biomass error ranges from 20-50%, which precludes identifying actual differences in aboveground live biomass density at 10 Mg•ha-1 intervals. These broad plot-scale uncertainties in structure from current and planned sensors provided the basis for examining a data integration technique with multiple sensors to measure the structure of sparse TTE forests. Spaceborne estimates of canopy height used complementary surface elevation measurements from passive optical and LiDAR to provide a means for directly measuring TTE forest height from spaceborne sensors. This spaceborne approach to estimating forest height was deployed to assess the spaceborne potential for examining the patterns of TTE forest structure explained with a conceptual biogeographic model linking TTE patterns and its dynamics. A patch-based analysis was used to scale estimates of TTE forest structure from multiple sensors and provided a means to simultaneously examine the horizontal and vertical structure of groups of TTE trees. The uncertainty of forest patch height estimates provides focus for improving spaceborne depictions of TTE structure patterns associated with recent change that may explain the variability of this change and the vulnerability of TTE forest structure.Item Impacts of Conflict on Land Use and Land Cover in the Imatong Mountain Region of South Sudan and Northern Uganda(2012) Gorsevski, Virginia; Kasischke, Eric S; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The Imatong Mountain region of South Sudan makes up the northern most part of the Afromontane conservation `biodiversity hotspot' due to the numerous species of plants and animals found here, some of which are endemic. At the same time, this area (including the nearby Dongotana Hills and the Agoro-Agu region of northern Uganda) has witnessed decades of armed conflict resulting from the Sudan Civil War and the presence of the Ugandan Lord's Resistance Army (LRA). The objective of my research was to investigate the impact of war on land use and land cover using a combination of satellite remote sensing data and semi-structured interviews with local informants. Specifically, I sought to 1) assess and compare changes in forest cover and location during both war and peace; 2) compare trends in fire activity with human population patterns; and 3) investigate the underlying causes influencing land use patterns related to war. I did this by using a Disturbance Index (DI), which isolates un-vegetated spectral signatures associated with deforestation, on Landsat TM and ETM+ data in order to compare changes in forest cover during conflict and post-conflict years, mapping the location and frequency of fires in subsets of the greater study area using MODIS active fire data, and by analyzing and summarizing information derived from interviews with key informants. I found that the rate of forest recovery was significantly higher than the rate of disturbance both during and after wartime in and around the Imatong Central Forest Reserve (ICFR) and that change in net forest cover remained largely unchanged for the two time periods. In contrast, the nearby Dongotana Hills experienced relatively high rates of disturbance during both periods; however, post war period losses were largely offset by gains in forest cover, potentially indicating opposing patterns in human population movements and land use activities within these two areas. For the Agoro-Agu Forest Reserve (AFR) region northern Uganda, the rate of forest recovery was much higher during the second period, coinciding with the time people began leaving overcrowded Internally Displaced Persons (IDP) camps. I also found that fire activity largely corresponded to coarse-scale human population trends on the South Sudan and northern Uganda side of the border in that post-war fire activity decreased for all areas in South Sudan and northern Uganda except for areas near the larger towns and villages of South Sudan, where people have begun to resettle. Fires occurred most frequently in woodlands on the South Sudan side, while the greatest increase in post-war, northern Ugandan fires occurred in croplands and the forested area around the Agoro-Agu reserve, Interviews with key informants revealed that while some people fled the area during the war, many others remained in the forest to hide; however, their impact on the forests during and after the conflict has been minimal; in contrast, those interviewed believed that wildlife has been largely depleted due to the widespread access to firearms and lack of regulations and enforcement. This study demonstrates the utility of using a multi-disciplinary approach to examine aspects of forest dynamics and fire activity related to human activities and conflict and as such contributes to the nascent but growing body of research on armed conflict and the environment.