College of Behavioral & Social Sciences

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    Validation of Land Cover Maps in China Using a Sampling-Based Labeling Approach
    (MDPI, 2015-08-18) Bai, Yan; Feng, Min; Jiang, Hao; Wang, Juanle; Liu, Yingzhen
    This paper presents a rigorous validation of five widely used global land cover products, i.e., GLCC (Global Land Cover Characterization), UMd (University of Maryland land cover product), GLC2000 (Global Land Cover 2000 project data), MODIS LC (Moderate Resolution Imaging Spectro-radiometer Land Cover product) and GlobCover (GLOBCOVER land cover product), and a national land cover map GLCD-2005 (Geodata Land Cover Dataset for year 2005) against an independent reference data set over China. The land cover reference data sets in three epochs (1990, 2000, and 2005) were collected on a web-based prototype system using a sampling-based labeling approach. Results show that, in China, the highest overall accuracy is observed in GLCD-2005 (72.3%), followed by MODIS LC (68.9%), GLC2000 (65.2%), GlobCover (57.7%) and GLCC (57.2%), while UMd has the lowest accuracy (48.6%); all of the products performed best in representing “Trees” and “Others”, well with “Grassland” and “Cropland”, but problematic with “Water” and “Urban” across China in general. Moreover, in respect of GLCD-2005, there are significant accuracy differences across seven geographical locations of China, ranging from 46.3% in the Southwest, 77.5% in the South, 79.2% in the Northwest, 80.8% in the North, 81.8% in the Northeast, 82.6% in the Central, to 89.0% in the East. This study indicates that a regionally focused land cover map would in fact be more accurate than extracting the same region from a globally produced map.
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    Landsat Analysis Ready Data for Global Land Cover and Land Cover Change Mapping
    (MDPI, 2020-01-29) Potapov, Peter; Hansen, Matthew C.; Kommareddy, Indrani; Kommareddy, Anil; Turubanova, Svetlana; Pickens, Amy; Adusei, Bernard; Tyukavina, Alexandra; Ying, Qing
    The multi-decadal Landsat data record is a unique tool for global land cover and land use change analysis. However, the large volume of the Landsat image archive and inconsistent coverage of clear-sky observations hamper land cover monitoring at large geographic extent. Here, we present a consistently processed and temporally aggregated Landsat Analysis Ready Data produced by the Global Land Analysis and Discovery team at the University of Maryland (GLAD ARD) suitable for national to global empirical land cover mapping and change detection. The GLAD ARD represent a 16-day time-series of tiled Landsat normalized surface reflectance from 1997 to present, updated annually, and designed for land cover monitoring at global to local scales. A set of tools for multi-temporal data processing and characterization using machine learning provided with GLAD ARD serves as an end-to-end solution for Landsat-based natural resource assessment and monitoring. The GLAD ARD data and tools have been implemented at the national, regional, and global extent for water, forest, and crop mapping. The GLAD ARD data and tools are available at the GLAD website for free access.
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    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.