Geography
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Item Multispectral satellite remote sensing approaches for estimating cover crop performance in Maryland and Delaware(2022) THIEME, ALISON; Justice, Chris; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Winter cover crops encompass a range of species planted in late summer and fall for a variety of reasons relating to soil health, nutrient retention, soil compaction, biotic diversity, and erosion prevention. As agricultural intensification continues, the practice of winter cover cropping remains a crucial practice to reduce leaching from agricultural fields. Maryland and Delaware both incentivize cover cropping to meet water quality objectives in the Chesapeake Bay Watershed. These large-scale programs necessitate methods to evaluate cover crop performance over the landscape. Cover crop quantity and quality was measured at 2,700 locations between 2006-2021 with a focus on fields planted to four cereal species: wheat, rye, barley, and triticale. Samples were GPS located and timed with satellite remote sensing observations from SPOT 4, SPOT 5, Landsat 5, Landsat 7, Landsat 8, or Sentinel-2. When paired imagery at 10-30 m spatial resolution , there is a strong relationship between the normalized difference vegetation index (NDVI) and percent ground cover (R2=0.72) as well as NDVI and biomass (as high as R2=0.77). There is also a strong relationship between Δ Red Edge (a combination of 740 nm and 783 nm bands) and nitrogen content (R2=0.75). These equations were applied to Harmonized Landsat Sentinel-2 products and used to estimate cover crop aboveground biomass in ~300,000 ha of Maryland Department of Agricultures and ~60,000 ha of Delaware Association of Conservation Districts enrolled fields from 2019-2021 and grouped by agronomic method. Wintertime and springtime cover crop biomass varied based on planting date, planting method, species, termination date, and termination method. Early planted fields had higher wintertime biomass while fields that delayed termination had higher springtime biomass. Triticale had consistently higher biomass while wheat had the lowest biomass. Fields planted using a drill followed by light tillage or no-till drill had higher biomass, likely due to the better seed-to-soil contact. Fields that were taken to harvest or terminated for on farm use (roller crimped, green chopped) also had higher springtime biomass than other termination methods. Incentives can be used to encourage specific agronomic methods and these findings can be used to inform adaptive management in the Mid-Atlantic Region.Item TOWARDS OBJECT-BASED EVALUATION OF INDIVIDUAL FIRES AT GLOBAL SCALES(2019) Humber, Michael Laurence; Justice, Christopher O; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Fire is a complex biophysical variable that has shaped the land surface for over 400 million years and continues to play important roles in landscape management, atmospheric emissions, and ecology. Our understanding of global fire patterns has improved dramatically in recent decades, coincident with the rise of systematic acquisition and development of global thematic products based on satellite remote sensing. Currently, there are several operational algorithms which map burned area, relying on coarse spatial resolution sensors with high temporal frequencies to identify fire-affected surfaces. While wildfires have been analyzed over large areas at the pixel level, object-based methods can provide more detailed attributes about individual fires such as fire size, severity, and spread rate. This dissertation evaluates burned area products using object-based methods to quantify errors in burn shapes and to extract individual fires from existing datasets. First, a wall-to-wall intercomparison of four publicly available burned area products highlights differences in the spatial and temporal patterns of burning identified by each product. The results of the intercomparison show that the MODIS Collection 6 MCD64A1 Burned Area product mapped the most burned area out of the four products, and all products except the Copernicus Burnt Area product showed agreement with regard to temporal burning patterns. In order to determine the fitness of the MCD64A1 product for mapping fire shapes, a framework for evaluating the shape accuracy of individual fires was developed using existing object-based metrics and a novel metric, the “edge error”. The object-based accuracy assessment demonstrated that MCD64A1 preserves the fire shape well compared to medium resolution data. Based on this result, an algorithm for extracting individual fires from MCD64A1 data was developed which improves upon existing algorithms through its use of an uncertainty-based approach rather than empirically driven approaches. The individual fires extracted by this algorithm were validated against medium resolution data in Canada and Alaska using object-based metrics, and the results indicate the algorithm provides an improvement over similar datasets. Overall, this dissertation demonstrates the capability of coarse resolution burned area products to accurately identify individual fire shapes and sizes. Recommendations for future work include improving the quality assessment of burned area products and continuing research into identifying spatiotemporal patterns in fire size distributions over large areas.Item CHARACTERIZING HYDROLOGICAL PROCESSES WITHIN THE DATA-SCARCE ENVIRONMENT OF THE CONGO BASIN(2019) Munzimi, Yolande; Hansen, Matthew C; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The Congo Basin in Africa is the world’s second largest river basin. Centrally located and with the greatest water resources in Africa, the basin is a vital resource for water and energy supply for a continent with increasing needs for safe water and energy. The Congo Basin’s streams and rivers could be impacted by human activities in the region, notably by land cover and land use change (LCLUC) considering the strong interactions between hydrology and ecosystem processes in the humid tropics. It could impact flow discharge downstream Congo River and hydropower potential at the Inga hydroelectric site, the largest such installation in Africa, located 150km upstream from the river’s mouth. The seasonal rainfall regime, to which the Congo River owes its regular flow regime, play an important role in mediating freshwater resources. An improvement to our baseline information on the Congo’s rainfall and streamflow dynamics allows for a greater quantitative understanding of the basin’s hydrology, necessary for the current and future management of Congo Basin water resources. The hydrometeorological observation network in the Congo Basin is very limited, and this environment of scarce ground data necessitates the use of remotely-sensed data for hydrological modeling. This dissertation reports the use of hydrological modeling supported by remotely-sensed data to 1) characterize precipitation and climate in the Congo Basin, 2) characterize daily streamflow across the basin, 3) assess the hydrological response to LCLUC, including the additional response caused by climatic feedbacks following LCLUC. The study uses rainfall gauge data within the Democratic Republic of Congo (DRC) to re-calibrate a TRMM science product. It then describes a physically-based parameterization of a semi-distributed hydrological model, augmented with a spatially-distributed calibration that enables the model to simulate hydrologic processes in the Congo Basin, including the slowing effect of the basin’s central wetlands, the Cuvette Centrale. Model simulations included scenarios of 25% to 100% conversion of the Basins forest cover to agricultural mosaic and compared simulated flows to those of the current baseline conditions. The dissertation also reports on the estimated impacts of the hydrological response to LCLUC on the river’s hydropower potential. Re-calibration of TRMM improved rainfall accuracy at the gauges by 15% and correctly captured important rainfall patterns such as the ones representative of the highland climate. Model calibration of daily streamflow resulted in a model with high predictive power (Nash–Sutcliffe coefficient of efficiency of 0.70) when compared to Kinshasa gauge downstream Congo River, near its outlet. Model shows realistic seasonal and spatial patterns that can be explained by the ITCZ-driven rainfall patterns in the Congo Basin. Models of the direct effects alone of 25% to 100% forest conversion produce increases in peak flows of 7% to 8%, respectively, relative to the baseline, and decreases in low flow of 1% and 6%, for 75% and 100% forest conversion respectively, relative to the baseline. However, 25% and 50% forest conversion produce increases in low flows of 3% and 1% respectively indicating a possible sensitivity of the hydrological response to the spatial variability of forest conversion. Models of the combined direct and indirect effects of 25% to 100% conversion produce decreases in peak flows of 7% to 5% respectively and decreases in low flow of 8% to 11% respectively. Model estimates of the impacts on hydropower potential range from 11% decrease during dry season to 10% increase during rainy season, with greater impacts (year-round decrease) for increasing LCLUC models including indirect effect. The modeled loss in hydropower potential during dry season reaches -5,797 MW corresponding to the hydropower potential of countries such as Zambia or Angola and of grand projects such as the Grand Ethiopian Renaissance Dam. The dissertation has showed the adequacy of TRMM precipitation products for Congo Basin rainfall regime representation and daily flow estimation particularly in capturing the timing and the seasonality of the flow. The results of these modeling efforts can be useful in research and decision-making contexts and validate the application of satellite-based hydrologic models driven for large, data-scarce river systems such as the Congo Basin by producing reliable baseline information. We recommend a prioritization of further data collection and more gauges installation required to enable further satellite-derived data calibration and models simulations. Likewise, the results from LCLUC analysis support the need for field campaigns to better understand sub-watersheds responses and to improve the calibration of currently used simulation models.Item TOWARDS FINE SCALE CHARACTERIZATION OF GLOBAL URBAN EXTENT, CHANGE AND STRUCTURE(2017) Wang, Panshi; Huang, Chengquan; Liang, Shunlin; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Urbanization is a global phenomenon with far-reaching environmental impacts. Monitoring, understanding, and modeling its trends and impacts require accurate, spatially detailed and updatable information on urban extent, change, and structure. In this dissertation, new methods have been developed to map urban extent, sub-pixel impervious surface change (ISC), and vertical structure at national to global scales. First, an innovative multi-level object-based texture classification approach was adopted to overcome spectral confusion between urban and nonurban land cover types. It was designed to be robust and computationally affordable. This method was applied to the 2010 Global Land Survey Landsat data archive to produce a global urban extent map. An initial assessment of this product yielded over 90% overall accuracy and good agreement with other global urban products for the European continent. Second, for sub-pixel ISC mapping, the uncertainty caused by seasonal and phenological variations is one of the greatest challenges. To solve this issue, I developed an iterative training and prediction (ITP) approach and used it to map the ISC of entire India between 2000 and 2010. At 95% confidence, the total ISC for India between 2000 and 2010 was estimated to be 2274.62±7.84 km2. Finally, using an object-based feature extraction approach and the synergy of Landsat and freely available elevation datasets, I produced 30m building height and volume maps for England, which for the first time characterized urban vertical structure at the scale of a country. Overall, the height RMSE was only ±1.61 m for average building height at 30m resolution. And the building volume RMSE was ±1142.3 m3. In summary, based on innovative data processing and information extraction methods, this dissertation seeks to fill in the knowledge gaps in urban science by advancing the fine scale characterization of global urban extent, change, and structure. The methods developed in this dissertation have great potentials for automated monitoring of global urbanization and have broad implications for assessing the environmental impact, disaster vulnerability, and long-term sustainability of urbanization.Item AGRICULTURAL LAND USE, DROUGHT IMPACTS AND VULNERABILITY: A REGIONAL CASE STUDY FOR KARAMOJA, UGANDA(2017) Nakalembe, Catherine Lilian; Justice, Christopher O; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The increasing frequency of extreme climate events brings into question the sustainability of agriculture in marginal lands, especially those already experiencing drought such as the Karamoja region in northeastern Uganda. A significant amount of research often qualitative has been conducted documenting drought and its impact on Karamoja. Taking a mixed methods approach, this study combined remotely-sensed satellite data, national agricultural surveys, census, and field data to expand on empirical knowledge on agricultural drought, land use and human perceptions of drought necessary for comprehensive drought forecasting, monitoring, and management. Results from this study showed that Karamoja is at least twice more vulnerable to drought than any other region in Uganda. This is because of its very low adaptive capacity in part due to high poverty rates and a higher dependency on the natural environment for livelihood. Analysis of satellite data quantified a 229 percent increase in cropland area in Karamoja between 2000 and 2011/12, driven largely by agricultural development programs. Underlying forces (e.g., cropland expansion programs and controlled grazing) originating from land use policy and development programs, more than proximate causes (direct local level actions) remain the major drivers of this expansion. Although the cultivated area has dramatically increased, there is no quantifiable overall increase in yield or per-capita production as evidenced by the recurrent poor food security. This status quo, (poor yields and dependence on food aid) is likely to continue as more land is put to crop cultivation by poor households and meager investments are made in livestock-based livelihood opportunities. The cropland area mask developed in this research facilitated the characterization of drought within agricultural areas. The drought information developed by this study is spatially and temporally explicit, showing differences in severity between years and between districts. Overall Abim District showed the least variation and is the least impacted while, Moroto District had the highest inter-annual variability and was often the most severely impacted. This research presents an approach to predict the number of people who would require food aid during the lean season in Karamoja (December to March) within a reasonable margin of error (less than 10\%) at the peak of the growing season (August/September), although the need for more extensive testing is recognized. The method takes advantage of readily available satellite data and can contribute to planning for a timely and appropriate response. A case study of farmer's perceptions of drought in Moroto District found that many farmers feel helpless and have no control of their future. For the majority of farmers in the district, past experiences of drought do not necessarily impact on future expectations of drought and many have no long-term adjustment plans. Quite often the majority of the population depends on emergency food assistance, building a culture of dependency. The analysis indicates that factors such as; conflict (insecurity) and interventions by government and international agencies intermingle with culture to have a profound direct influence on farmers' perception of drought amongst communities in Moroto district. This research shows that satellite data can provide the much-needed information to fill the gaps that inhibit long-term drought monitoring, at a significantly lower cost than traditional climate station-based monitoring in data scarce regions like Karamoja. It also points to a way forward for proactive assessment, planning, and response.Item LAND USE AND LAND COVER CHANGE AS A DRIVER OF ECOSYSTEM DEGRADATION ACROSS BIOMES(2016) Noojipady, Praveen; Prince, Stephen D; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The expansion and intensification of agricultural production in human-dominated landscapes threaten efforts to sustain natural ecosystems and maintain agricultural production in a changing climate. Long-term use of agricultural lands, combined with conversion of natural ecosystems for agricultural production, can rapidly degrade the health of remaining natural ecosystems. The fundamental goal of this dissertation was to assess the impacts of anthropogenic degradation on stocks and sequestration of carbon. Although degradation alters a range of ecosystem services, case studies of ecosystem degradation in this dissertation focus on reductions in vegetation productivity, carbon stocks, and the extent of natural forest cover as a result of human activity. Time series of satellite remote sensing data were used to track forest and rangeland degradation in the southwestern United States, forest carbon emissions from cropland expansion in the Brazilian Cerrado, and fire-driven forest conversion for oil palm plantations in Southeast Asia. Three major themes link the regional case studies: expansion and intensification of agricultural production, market demand and certification, and agricultural management in response to climate variability. Conclusions from the dissertation underscore the widespread influence of land management on vegetation productivity and forest carbon stocks. In the Southwest United States, reductions in net primary production on managed lands were higher in forested landscapes than other cover types. In contrast, Native American Indian Reservations, often considered to be more degraded, actually had smaller absolute reductions in net primary productivity during 2000-2011. Multi-year droughts in the southwest present new challenges for managing forests and rangelands, and climate projections suggest dry conditions will intensify in the coming century. In Southeast Asia, industry-led efforts to certify sustainable palm oil production were evaluated using satellite data on fires and forest loss. Rates of fire-driven deforestation and total fire activity declined following certification, highlighting the potential for certification to reduce ignitions during El Niño years and protect remaining fragments of lowland and peat forest. Aligning certification criteria for sustainable palm oil with satellite monitoring capabilities may help accelerate compliance with environmental legislation and market demands for deforestation-free products. In Brazil, government and industry actions to limit Amazon deforestation have largely overlooked the neighboring Cerrado biome. Forest carbon emissions from deforestation for soy expansion in the Cerrado increased substantially after the implementation of the Soy Moratorium in the Brazilian Amazon, partially offsetting recent reductions in Amazon deforestation carbon emissions. The success of policies to support sustainable agricultural production therefore depends on efforts to minimize cross-biome leakage and the ability to monitor compliance and unintended consequences. Solutions for management must also confront the growing influence of climate variability. Time series of satellite data may allow early detection of degradation impacts and support efforts to mitigate the influence of sustained agricultural production on natural systems. Changes in vegetation carbon stocks from ecosystem degradation varied across case studies, underscoring the diverse nature of direct and indirect drivers of degradation across different land use systems. Direct human drivers of ecosystem degradation in the southwest United States from management of livestock grazing resulted in gradual changes in vegetation productivity, whereas mining and oil extraction areas showed large and permanent reductions. Forest carbon emissions from agriculture expansion in the Cerrado were a one-time process, as native vegetation is cleared for cropland expansion. In contrast, the carbon emissions from Southeast Asia’s forest and peatland conversion involve both sudden and gradual processes, as carbon accumulation in oil palm plantations partially compensates for emissions from forest conversion. Overall, this research made contributions to understanding of the regional impacts of human activity and the potential for climate change mitigation from sustainable land use practices in human-dominated landscapes.Item Estimation of Pan-Tropical Deforestation and Implications for Conservation(2015) KIM, DOHYUNG; Townshend, John R; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Reducing tropical deforestation has been a primary focus for the implementation of policies that are aimed at biodiversity conservation, and reducing greenhouse gas emissions, as tropical forests have, biologically, the richest ecosystem on Earth, tropical deforestation is one of the largest sources of anthropogenic carbon emission into the atmosphere, and preventing it is the most inexpensive option, in order to reduce carbon emissions and conserve biodiversity. To set the effective policies and conservation plans to reduce emission from tropical deforestation, the evaluation of effectiveness of both the current and previous efforts for conservation is critical. The three studies in this dissertation describe the development of the methods to accurately monitor pan-tropical forest cover change, using satellite remote sensing data, and their integration with the econometrics approach, to evaluate the effectiveness of the tropical forest conservation practices. The dissertation contributes a method for long-term, global forest cover change estimation from Landsat, and the methods are applied to report the first, pan-tropical forest cover change trends, between the 1990s and the 2000s. The global forest cover change product from 1990 to 2000, which was produced, based on the developed methods which are evaluated to have an overall accuracy of 88%. The results demonstrate that tropical deforestation has accelerated between the 1990s and the 2000s by 62%, which contradicts the assertions of it being decelerating. The results further show that the increased deforestation rate between the 1990s and the 2000s is significantly correlated with the increases in Gross Domestic Product (GDP) growth rate, agricultural production growth, and urban population growth between the two decades. Protected Areas (PA), throughout the tropics, avoided 83,000 ± 22,000 km2 of the deforestation during the 2000s. The effectiveness of international aid can be suppressed by weak governance and the lack of forest change monitoring capacity of each country. The conclusions of this dissertation provide a historical baseline for the estimates of tropical forest cover change, and for the evaluation of effectiveness of such conservation efforts.Item Lidar Remote Sensing of Vertical Foliage Profile and Leaf Area Index(2015) Tang, Hao; Dubayah, Ralph; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Leaf Area Index (LAI) and Vertical Foliage Profile (VFP) are among the most important forest structural parameters, and characterization of those parameters in high biomass forests remains a major challenge in passive remote sensing due to signal saturation problem. Recently an active remote sensing technology, light detection and ranging (lidar), has shown a great promise in this task recognizing its accuracy in measuring aboveground biomass and canopy height. This dissertation further expands current application of lidar on ecosystem monitoring, and explores the capacity of deriving LAI and VFP from lidar data in particular. The overall goal of this study is to derive large scale forest LAI and VFP using data from the Geoscience Laser Altimeter System (GLAS) on board of ICESat, and provide a framework of validating such LAI products from plot level to global scale. To achieve this goal, a physically based Geometry Optical and Radiative Transfer (GORT) model was first developed using high quality airborne waveform lidar data over a tropical rainforest in La Selva, Costa Rica. The excellent agreement between lidar data and field destructively sampled data demonstrated the effectiveness of the Lidar-LAI model and suggested large footprint waveform lidar can provide accurate vertical LAI profile estimates that do not saturate even at the highest possible LAI levels. Next, an intercomparative study of ground-based, airborne and spaceborne retrievals of total LAI was conducted over the conifer-dominated forests of Sierra Nevada in California. Good relationships were discovered in their comparisons, following a scaling-up validation strategy where ground-based LAI observations were related to aircraft observations of LAI, which in turn were used to validate GLAS LAI derived from coincident data. Successful implementation of this strategy can pave the way for the future recovery of vertical LAI profiles globally. LAI and VFP products were then derived over both the entire state of California and Contiguous United States as an efficacy demonstration of the method. These products were the first ever attempts to obtain large scale estimates of LAI and VFP from lidar observations. Such forest structural measurement can be used not only to quantify carbon stock and flux of terrestrial ecosystem, but also to provide spatial information of specie abundance in biodiversity. Results from this study can also greatly help broaden scientific applications of future spaceborne lidar missions (e.g. ICESat-2 and GEDI).Item Advancing Indonesian Forest Resource Monitoring Using Multi-Source Remotely Sensed Imagery(2014) Margono, Belinda Arunarwati; Hansen, Matthew C; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Tropical forest clearing threatens the sustainability of critically important global ecosystems services, including climate regulation and biodiversity. Indonesia is home to the world's third largest tropical forest and second highest rate of deforestation; as such, it plays an important role in both increasing greenhouse gas emissions and loss of biodiversity. In this study, a method is implemented for quantifying Indonesian primary forest loss by landform, including wetlands. A hybrid approach is performed for quantifying the extent and change of primary forest as intact and degraded types using a per-pixel supervised classification mapping followed by a GIS-based fragmentation analysis. The method was prototyped in Sumatra, and later employed for the entirety of Indonesia, and can be replicated across the tropics in support of REDD+ (Reducing Emissions from Deforestation and forest Degradation) initiatives. Mapping of Indonesia's wetlands was performed using cloud-free Landsat image mosaics, ALOS-PALSAR imagery and topographic indices derived from the SRTM. Results quantify an increasing rate of primary forest loss over Indonesia from 2000 to 2012. Of the 15.79 Mha of gross forest cover loss for Indonesia reported by Hansen et al. (2013) over this period, 38% or 6.02 Mha occurred within primary intact or degraded forests, and increased on average by 47,600 ha per year. By 2012, primary forest loss in Indonesia was estimated to be higher than Brazil (0.84 Mha to 0.47 Mha). Almost all clearing of primary forests (>90%) occurred within degraded types, meaning logging preceded conversion processes. Proportional loss of primary forests in wetlands increased with more intensive clearing of wetland forests in Sumatra compared to Kalimantan or Papua, reflecting a near-exhaustion of easily accessible lowland forests in Sumatra. Kalimantan had a more balanced ratio of wetland and lowland primary forest loss, indicating a less advanced state of natural forest transition. Papua was found to have a more nascent stage of forest exploitation with much of the clearing related to logging activities, largely road construction. Loss within official forest-land uses that restrict or prohibit clearing totaled 40% of all loss within national forest-land, another indication of a dwindling resource. Methods demonstrated in this study depict national scale primary forest change in Indonesia, a theme that until this study has not been quantified at high spatial (30m) and temporal (annual) resolutions. The increasing loss of Indonesian primary forests found in this study has significant implications for climate change mitigation and biodiversity conservation efforts.Item ASSESSING THE RELATIONSHIPS BETWEEN VERTICAL STRUCTURE, BIODIVERSITY, AND SUCCESSION IN A FOREST ECOSYSTEM USING LIDAR REMOTE SENSING(2014) Whitehurst, Amanda Sharon; Dubayah, Ralph O; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This thesis used lidar remote sensing to explore the role of vertical structure in forest ecosystem dynamics. In particular, relationship between the vertical distribution, biodiversity, and succession was examined in Hubbard Brook Experimental Forest, NH (HBEF). The first objective was to develop metrics characterizing vertical foliage distribution or canopy layering. Two novel metrics (canopy layer structure categories and number of foliage profile layers) were created, allowing canopy layering to be mapped HBEF. The canopy layer structure metric categorizes areas by comparing the amount of vegetation in under, mid, and overstories. The number of foliage profile layers is related to peaks in the foliage area profile, representing area of dense of "clumped" foliage. Both these metrics varied with canopy height and elevation, areas with taller trees and lower elevations tended to have more foliage profile layers and were classified as categories with a dominant overstory. The second objective was to examine the relationship between vertical canopy structure and avian species diversity. Multiple vertical structure metrics were derived for 370 bird plots in HBEF. Foliage height diversity (FHD) varied greatly in relation to bird species diversity. Of the foliage distribution metrics, vegetation ratio and number of foliage profile layers explained the most variability in bird species diversity. The lidar metric of height at median return (HOME) had the strongest correlation with bird species diversity (r = - 0.56). This study showed a moderate correlation between bird species diversity and foliage distribution metrics. It further supports previous studies which question the applicability of FHD. Finally, change in vertical structure in HBEF was examined using lidar data from 1999 and 2009. Due to significant change in canopy height, canopy cover, vegetation ratio and understory cover during the time period, it was determined that HBEF had not reached steady-state. Recently disturbed areas had significantly higher canopy height growth than undisturbed areas, despite being at higher elevations. This research presents standardized metrics for the characterization and mapping of canopy foliage distribution. It also provides ecological links between lidar metrics and ecological concepts to enabling these measurements of forest structure to be applied in other areas.