Geography
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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 MAPPING FOREST STRUCTURE AND HABITAT CHARACTERISTICS USING LIDAR AND MULTI-SENSOR FUSION(2011) Swatantran, Anuradha; Dubayah, Ralph; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation explored the combined use of lidar and other remote sensing data for improved forest structure and habitat mapping. The objectives were to quantify aboveground biomass and canopy dynamics and map habitat characteristics with lidar and /or fusion approaches. Structural metrics from lidar and spectral characteristics from hyperspectral data were combined for improving biomass estimates in the Sierra Nevada, California. Addition of hyperspectral metrics only marginally improved biomass estimates from lidar, however, predictions from lidar after species stratification of field data improved by 12%. Spatial predictions from lidar after species stratification of hyperspectral data also had lower errors suggesting this could be viable method for mapping biomass at landscape level. A combined analysis of the two datasets further showed that fusion could have considerably more value in understanding ecosystem and habitat characteristics. The second objective was to quantify canopy height and biomass changes in in the Sierra Nevada using lidar data acquired in 1999 and 2008. Direct change detection showed overall statistically significant positive height change at footprint level (ΔRH100 = 0.69 m, +/- 7.94 m). Across the landscape, ~20 % of height and biomass changes were significant with more than 60% being positive, suggesting regeneration from past disturbances and a small net carbon sink. This study added further evidence to the capabilities of waveform lidar in mapping canopy dynamics while highlighting the need for error analysis and rigorous field validation Lastly, fusion applications for habitat mapping were tested with radar, lidar and multispectral data in the Hubbard Brook Experimental Forest, New Hampshire. A suite of metrics from each dataset was used to predict multi-year presence for eight migratory songbirds with data mining methods. Results showed that fusion improved predictions for all datasets, with more than 25% improvement from radar alone. Spatial predictions from fusion were also consistent with known habitat preferences for the birds demonstrating the potential of multi- sensor fusion in mapping habitat characteristics. The main contribution of this research was an improved understanding of lidar and multi-sensor fusion approaches for applications in carbon science and habitat studies.