Geography

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Subject: search.filters.subject.land cover and land use change

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    Sample-Based Estimation of Tree Cover Change in Haiti Using Aerial Photography: Substantial Increase in Tree Cover between 2002 and 2010
    (MDPI, 2021-09-14) Rodrigues-Eklund, Gabriela; Hansen, Matthew C.; Tyukavina, Alexandra; Stehman, Stephen V.; Hubacek, Klaus; Baiocchi, Giovanni
    Recent studies have used high resolution imagery to estimate tree cover and changes in natural forest cover in Haiti. However, there is still no rigorous quantification of tree cover change accounting for planted or managed trees, which are very important in Haiti’s farming systems. We estimated net tree cover change, gross loss, and gross gain in Haiti between 2002 and 2010 from a stratified random sample of 400 pixels with a systematic sub-sample of 25 points. Using 30 cm and 1 m resolution images, we classified land cover at each point, with any point touching a woody plant higher than 5 m classified as tree crown. We found a net increase in tree crown cover equivalent to 5.0 ± 2.3% (95% confidence interval) of Haiti’s land area. Gross gains and losses amounted to 9.0 ± 2.1% and 4.0 ± 1.3% of the territory, respectively. These results challenge, for the first time with empirical evidence, the predominant narrative that portrays Haiti as experiencing ongoing forest or tree cover loss. The net gain in tree cover quantified here represents a 35% increase from 2002 to 2010. Further research is needed to determine the drivers of this substantial net gain in tree cover at the national scale.
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    Forest Cover Dynamics of Shifting Cultivation in the Democratic Republic of Congo
    (2018) Molinario, Giuseppe Maria; Hansen, Matthew C; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This dissertation is focused on contextualizing spatio-temporally forest cover loss in the DRC for the period 2000-2015 as it relates to the shifting cultivation dynamic and the rural complex mosaic. Impacts of forest loss on forest ecosystems, carbon release and biodiversity habitat differ depending on where and when it occurs relative to the rural complex. This was done by mapping the rural complex and disaggregating forest cover loss due to cyclical, livelihood shifting cultivation within three areas: 1) the baseline established rural complex (ERC) for 2000 and new 2000-2015 primary forest loss occurring as either 2) rural complex expansion (RCE) or 3) isolated forest perforations (IFP) further into core forest. Finally the influence of large-scale commercial land uses on forest cover loss is also assessed, from a spatial perspective. Between 2000 and 2010 the rural complex grew by 10% from 12% to 13% of the DRC’s land area, at an average yearly rate of 1%, while perforated forest grew by 74%, from 0.8% to 1.5% of DRC’s land area in 2010 at an average yearly rate of 0.7%. Core forest decreased by -3.8% at an average yearly rate of -0.4% per year, from 38% to 36.6% of the 2010 land area. Of particular concern is the nearly doubling of perforated forest, representing greater spatial intrusion of forest clearing within core forest areas. The land cover and land use (LCLU) components of the ERC were estimated by photo-interpreting high resolution imagery selected using a simple random sampling scheme. In the ERC 76% of land was already actively used for shifting cultivation. Therefore, together with remnant patches of primary forest (11%), an estimated 87% of the ERC was available for future shifting cultivation. Assuming a 4.6% clearing rate, this allowed estimating a ~18 year reuse rate of land in the ERC. Only 2% of the ERC area was occupied by large-scale commercial land use. This led to positing that commercial land uses might be more prevalent further away from settlements into core forest, where lower population density leads to less competition for natural resources. This hypothesis was tested by extending the probabilistic sampling analysis to new primary forest cover loss occurring outside of the ERC during the period 2000-2015. The map of the rural complex developed in Chapter 2 was validated, confirming larger proportions of primary forest and smaller proportions of shifting cultivation further away from the ERC and into core forest areas. LCLU proportions were established for both the RCE and IFP areas. Finally a concentric buffer distance analysis around sample points was used to quantify large-scale commercial land uses at the landscape scale, such as logging, mining and plantations that might be influencing shifting cultivation-driven forest cover loss. In the RCE the proportion of commercial land use was 0.4%, whereas it was 0.5% in IFPs; less than the proportion of commercial land use found in the ERC (2%). At the same time, results of the concentric buffer distance analysis show that 12% of sample points in the RCE and 9% of sample points in the IFP had commercial land uses within 5km. Commercial land uses are possibly more prevalent closer to the ERC because while there is more competition for land, there are also roads and communities that allow for the transportation of goods and provide labor. These results support the conclusion that large scale LCLU change dynamics in the DRC, such as commercial operations for export, are currently dwarfed by the reliance of rural populations on shifting cultivation. The vast majority of forest cover loss in the DRC remains due to smallholder farming not associated with commercial land uses. However, large-scale agroindustry or resource extraction activities lead to increased forest loss as their worker populations and communities rely on shifting cultivation for food, materials and energy. The spatial analysis of the rural complex allows us to peer into the future of forests in the DRC, as where isolated perforations lead, the rural complex soon follows and as the rural complex expands, so do commercial land uses.
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    A Spatial-Temporal Analysis of Wetland Loss and Section 404 Permitting on the Delmarva Peninsula from 1980 to to 2010
    (2017) Stubbs, Quentin A.; Yeo, In-Young; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Geospatial approaches for wetland change analyses have emphasized the evaluation of landscape change on a local level, but have often neglected to examine and integrate regional trends and patterns of land use and land cover change as well as the impacts of wetland management policies. This study attempts to bridge the gaps by integrating a geospatial assessment of land cover change and a geostatistical analysis of the physical and anthropogenic drivers of wetland change. The aim is to demonstrate how urban development, conservation, and climate change policy decisions influenced wetland change trends and patterns on the Delmarva Peninsula from 1980 to 2010. Historical data on the nine counties on the Delmarva Peninsula illustrated the dynamism of population growth, sprawl, and different wetland management strategies. Data sets from the National Oceanic and Atmospheric Administration, the Chesapeake Bay Program, the U.S. Army Corps of Engineers, the U.S. Fish and Wildlife Service, and the U.S. Census Bureau, and other sources were gathered and assessed. A land cover database was developed and analyzed using geospatial techniques, such as cross tabulation matrices and hot spot density analyses, in order to quantify and locate land cover change between 1984 and 2010. The results highlighted that anthropogenic drivers such as urbanization and agriculture were associated with the loss of wetlands in coastal areas as well as in upland, forested, suburban areas that were at low risk to flooding, but required deforestation in order to expand residential and commercial development. The greatest quantity and percentage of loss occurred between 1992 and 2001, and it was likely the result of increases in tourism and suburban sprawl (e.g., the Housing Boom and roadway expansion). The majority of wetland loss tapered off in 2000, except on coastal areas suffering from sea level rise and shoreline erosion. The results also reinforced the need to address the negative impacts from certain activities related to agriculture and silviculture, which are exempt from Section 404 of the Clean Water Act, have on wetlands. Physical drivers and processes like inundation from sea level rise and soil erosion from surface runoff force communities to simultaneously adapt to multiple drivers of wetland loss and alteration. This study supports the hypothesis that an increase in development and wetland permitting indicates an increased a risk of wetland loss. In the end, the study demonstrates that geostatistical modelling techniques can be used to predict wetland loss, and that model performance and accuracy can be improved by reducing the multicollinearity of independent variables. Planners and policymakers can use these models to better understand the wetland locations that are at greatest risk to loss, as well as the drivers and landscape conditions that have the greatest influence on the probability of wetland loss.