Geography Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2773
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Item DYNAMICS OF GLOBAL SURFACE WATER 1999 - PRESENT(2021) Pickens, Amy; Hansen, Matthew C; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Inland surface waters are critical to life, supplying fresh water and habitat, but are constantly in flux. There have been considerable advances in surface water monitoring over the last decade, though the extent of surface water has not been well-quantified per international reporting standards. Global characterizations of change have been primarily bi-temporal. This is problematic due to significant areas with multi-year cycles of wet and dry periods or anomalous high water or drought years. Many areas also exhibit strong seasonal fluctuations, such as floodplains and other natural wetlands. This dissertation aims to characterize open surface water extent dynamics by employing all of the Landsat archive 1999-present, and to report area estimates with associated uncertainty measures as required by policy guidelines. From 1999 to 2018, the extent of permanent water (in liquid or ice state) was 2.93 (standard error ±0.09) million km2, representing only 60.82 (±1.93)% of the total area that had water for some duration of the period. The unidirectional loss and gain areas were relatively small, accounting for only 1.10 (±0.23)% and 2.87 (±0.58)% of total water area, respectively. The area that transitioned multiple times between water and land states on an annual scale was over four times larger (19.74 (±2.16)%), totaling 0.95 (±0.10) million km2, establishing the need to evaluate the time-series from the entire period to assess change dynamics. From a seasonal perspective, June has over double the amount of open surface water as January, with 3.91 (±0.19) million km2 and 1.59 (±0.21) million km2, respectively. This is due to the vast network of lakes and rivers across the high-latitudes of the northern hemisphere that freeze over during the winter, with a maximum extent of ice over areas of permanent and seasonal water in February, totaling 2.49 (±0.25) million km2. This is the first global study to estimate the areas of extent and change with associated uncertainty measures and evaluate the seasonal dynamics of surface water and ice in a combined analysis. The methods developed here provide a framework for continuing to evaluate past trends and monitoring current dynamics of surface water and ice.Item Improved quantification of forest cover change and implications for the carbon cycle(2015) Song, Xiaopeng; Townshend, John R; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Changes in forest cover significantly affect the global carbon cycle, the hydrological cycle and biodiversity richness. This dissertation explores the potential of satellite-derived land cover datasets in quantifying changes in global forest cover and carbon stock. The research involved the following three components: 1) improving forest cover characterization, 2) developing advanced methods for detecting forest cover change (FCC) and 3) estimating the amount and trend of forest carbon change. The first component sought to improve global forest cover characterization through data fusion. Multiple global land cover maps have been generated, which collectively represent our current best knowledge of global land cover, but substantial discrepancies were found in their depiction of forest. I demonstrated that the extent and density of forest cover could be much better characterized by integrating existing datasets. However, these independent map products cannot be directly compared to quantify FCC, because post-classification change detection requires significant consistency in land cover definition, satellite data source and classification procedure. The yearly vegetation continuous field (VCF) product derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) provides a prototype that fulfills such requirement. The second component was intended to explore the features of this time series dataset in change analysis. A new algorithm called VCF-based Change Analysis was developed that can explicitly characterize the timing and intensity of FCC. The efficiency and robustness of this algorithm stem from two realistic assumptions—the spatial rarity and the temporal continuity of land cover change/modification. The developed method was applied to continental scales for mapping forest disturbance hotspots. The third component of the research combined MODIS-based deforestation indicators, a Landsat sample and a biomass dataset to estimate annual carbon emissions from deforestation with a regional focus on the Amazon basin. I found that deforestation emissions varied considerably not only across regions but also from year to year. Moreover, deforestation has been progressively encroaching into higher biomass lands in the Amazon interior. These observed deforestation and emission dynamics are expected to provide scientific support to policies on reducing emissions from deforestation and forest degradation (REDD+). The generated panel data are also of great value for evaluating forest protection policies.