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Publication Burning Down the Mouse: Fired Up About Historical Maps(2020) Houser, RhondaAt the University of Kansas Libraries, we continue to make steady progress on georeferencing our statewide collection of Sanborn Fire Insurance maps. Sanborn maps were created for towns and cities across the entire United States, and this project covers 241 Kansas towns between the years 1883 and 1922. The maps show property boundaries, building footprints and material, heat source, and more. They also describe in detail local resources such as water supply, and police and firefighting capacity. Sanborn maps are naturally intriguing, facilitating inquiry about how places change across the landscape and over time. For some of the towns, the peak of their population and urban development may be captured on a Sanborn map, due to industries such as farming, livestock, and mining, along with railway building. The presentation will include a brief overview and update on the project, including staff and funding, number of maps and cities completed, and our plans to make the maps available for public and GIS use.Publication Understanding how upgrading the Tomahawk Wastewater Treatment Facility will affect Indian Creek sources of impairment(GIS Day @ KU Planning Committee, 2019-11-13) Wilhelm, Jessica; Wakefield, Rachel; Burgin, AmyPublication Why Public Health Needs GIS?(GIS Day @ KU Planning Committee, 2019-11-13) Wang, FahuiPublication Intelligent Data Analytics and Communication Systems for Disasters(GIS Day @ KU Planning Committee, 2019-11-13) Demir, IbrahimPublication Counting Kansas: GIS in Local 2020 Census Planning(GIS Day @ KU Planning Committee, 2019-11-13) Wedel, XanPublication Determine suitable cooling center locations for heatwave adaptation by analyzing the vulnerable population with AHP and GIS: A case study in the City of Mission, KS(GIS Day @ KU Planning Committee, 2019-11-13) Kato, YurikaPublication An Optimization-based Matching Method and its Application in Merging Administrative Boundary Data(GIS Day @ KU Planning Committee, 2019-11-13) Lei, Ting; Yang, WenjunAs a critical data management task, conflation in GIS aims to determine the corresponding features from different datasets that in reality represent the same entities. This is called feature matching, which is used as a guidance to merge attributes of corresponding features between datasets. Based on the classification of features, there are point, polyline, and polygon matching methods. This study focuses on matching polygons and explores optimization–based matching methods for conflating two datasets.Publication Tracking Long-Term Lake Dynamics(GIS Day @ KU Planning Committee, 2018-11-14) Weekley, David; Li, XingongPublication Site Suitability for Wind Farms in the United States(GIS Day @ KU Planning Committee, 2018-11-14) Schmidt, MarkPublication Potential distribution of a new Bacillus species causing anthrax in African rainforests(GIS Day @ KU Planning Committee, 2018-11-14) Romero-Alvarez, Daniel; Campbell, Lindsay P.; Peterson, A. TownsendPublication CRI-MAP (Crime Mapping): Spatial and Temporal Analysis Of Crime Data Using Kernel Density Estimation(GIS Day @ KU Planning Committee, 2018-11-14) Mohan, PriyadharshiniPublication Present and past ecological niche models for the Great Tit (Parus major)(GIS Day @ KU Planning Committee, 2018-11-14) Machado-Stredel, Fernando; Song, Gang; Zhang, Ruiying; Alström, Per; Qu, Yanhua; Qiao, Huijie; Mays, Herman; Ericson, Per G.; Fjeldså, Jon; Lei, Fumin; Peterson, A. TownsendPublication Feral Cat Colony Location Identification in Lawrence, KS(GIS Day @ KU Planning Committee, 2018-11-14) Kennedy, ChristianPublication Comparing Land use changes of the watersheds of Lake Azuei -Trou Caiman and Lago Enriquillo - Raguna del Rincon by utilizing Google Earth Engine(GIS Day @ KU Planning Committee, 2018-11-14) Kato, YurikaLake Azuei is the largest lake in Haiti and is contributing a vital source for a livelihood in the area. The lake swollen this decade similarly with Lago Enriquillo, There are possibility of urbanization impacts, earthquake-induced groundwater change, climate change induced precipitation change or extreme weather. The purpose of the study is to reveal the impact of deforestation in lake water body change by comparing lakes in Haiti and the Dominican Republic. I utilized AWEI nsh to deliver the water body changes from 1987-2018 with the changes in Land use maps (1984, 1991, 2002, 2003, 2013 and 2018) to see how both watersheds experienced differently. From the results, there are significant lake level rises in Lake Azuei (21% from 1990-2013) and Lago Enriquillo (101% from 2003-2013) started around 2005-7. Trou Caiman decreased its waterbody by 43% from 1992 to 2015. No trend that can be detected in Raguna del Rincon. There is an interconnectivity between Lake Azuei and Trou Caiman throughout the study period. Inversely, Lago Enriquillo and Raguna del Rincon did not show any relationships. In land cover changes, baresoil was increased over time in both Haiti (20% increase) and Dominican Republic (5% increase). Dominican Republic did not show dramatic change, but grassland transformed into baresoil. On the other hand, Haiti experienced the greater expansion of baresoil transformed from grassland, forest, and urban. The Dominican Republic basin have land cover change somewhat less pattern, while Haiti has experienced significant increasing trends in baresoil and urban and decreasing trends in grass and forest land over time. There is a possibility of human intervention which might have affected the lake level change such as clogged canals in Lake AzueiPublication Sample Data and Training Modules for Cleaning Biodiversity Information(GIS Day @ KU Planning Committee, 2018-11-14) Cobos, Marlon E.; Jiménez, Laura; Nuñez-Penichet, Claudia; Romero-Alvarez, Daniel; Simões, MariannaThe recent appreciation of rapid global losses of biodiversity has created a growing demand for quick and reliable access to high-quality primary biodiversity data, essential for conservation and evolutionary science, among other applications. As a consequence, biodiversity databases have become increasingly available, allowing large-scale assessment of patterns and processes influencing the evolution of life on Earth. However, data quantity is often compromised by low data quality, and, even though working with plenty of records could be tempting, building ecological models with inaccurate data mislead researchers in driving conclusions about reality. The most common types of errors in biodiversity data are those related to georeferencing, which vary from obvious to barely noticeable, making them challenging to recognize. Fortunately, Geographic Information Systems (GIS) have increasingly allowed identification of georeferencing mistakes. Here, we provide a hands-on exercise for data cleaning that allows easy and prompt detection of inaccurate information. We focus on the use of GIS software for fixing problems related to the geographic coordinates of the data, such as changes in the order or the sign of latitude-longitude values, and records placed outside the study region, or outside continents.Publication Paying the Pipe(line)r: Equity Assessment of Hazardous Liquid Accidents and Indigenous American Land(GIS Day @ KU Planning Committee, 2018-11-14) Grote, KatiePublication GIS Application in Underground & Submarine Transmission(GIS Day @ KU Planning Committee, 2018-11-14) Rong, ForestPublication The use of Open-Source GIS Technologies at the National Weather Service - Central Region Headquarters(GIS Day @ KU Planning Committee, 2018-11-14) Walawender, BrianPublication Rivers, Satellites, and Mass Conservation: Changing the way we think about ungauged basins(GIS Day @ KU Planning Committee, 2018-11-14) Gleason, ColinPublication 1491 meets 2001: Comprehending past Native American impacts to forested landscapes using GIS and other 21st century tools(GIS Day @ KU Planning Committee, 2018-11-14) Tulowiecki, Steve