Spring NEARC 2022

Please take time to check out the following digital posters:

1. Western CT Regional Open Space Inventory
Tucker Beckett, WestCOG
Over the past year, WestCOG conducted a regional inventory of open space in western Connecticut. This work was conducted with a focus on flood mitigation and municipal engagement with FEMA's Community Rating System (CRS) under a grant from The Nature Conservancy. Drawing from WestCOG's member municipalities and the land trusts within the region, an interactive web map of open space was created to make this data available to the public.
Authors: Beckett, Tucker, Western CT Council of Governments; Trabka, Nick, Western CT Council of Governments

2. Restoration of Our Own Destruction (Best Poster Award Winner!)
Jay Song,   Bridgewater State University
This study focuses on identifying the contamination level of Per- and polyfluoroalkyl substances (PFAS) in each water facility with the population of each city in Massachusetts using a Geographic Information System. This study uses two sets of data.1622 water facilities in Massachusetts are analyzed and marked if they reach over the Maximum Contamination Level (MCL) of 20ng/L. Populations of 351 towns and cities are analyzed and displayed to identify which water facility a larger population use.

3. Weir Siting: An ArcGIS Approach (see PDF below!)
Alina Inchaustegui, Bridgewater State University
GIS will be used to analyze digital elevation data to identify optimal locations for installing two weirs on Great Hill on Bridgewater State University campus. The site locations will be based on characteristics of upland watershed, specifically permeable versus impermeable land area. Weirs will be useful in comparing the waterflow response of a natural versus urbanized area for sustainable development and climate resilience. Hydrology maps will be generated to model potential flood response.

4. Detection of Spatial Association between Lyme Disease and Environmental Factors in New Hampshire
Ana Marquez Pereda, Dartmouth College
In this study, we examined how Lyme Disease varies with certain environmental factors in New Hampshire (NH). On the Lyme Disease (LD) side, we used the data published by the NH Department of Health and Human Service (DHHS), which is town-level, age-adjusted rate data for two 5-year periods: 2004-2009 and 2010-2014. On the environmental side, we considered two factors, landscape fragmentation and surface temperature. The landscape fragmentation was measured based on the United States Geological Survey’s (USGS) National Land Coverage Dataset (NLCD) and the metrics were calculated using the FRAGSTATS software. The surface temperature data are from the USGS Landsat 8-9 Collection 2 (C2) Level 2 Science Product (L2SP). Using ArcGIS, we processed the environmental raster layers into a usable form, first by mosaicking multiple parts into an integrated layer, clipping them to the New Hampshire spatial extent, and converting them into the NH State Plane coordinate system. We then calculated the zonal statistics of those environmental values using the town polygons. Finally, we calculated the correlation coefficient and linear regression between LD and the environmental factors. It appears that LD has spatial associations with some landscape fragmentation metrics and the surface temperature in New Hampshire.


5. Lyme Disease and Landscape Fragmentation in Connecticut
Rena Schwartz, Department of Geography, Dartmouth College
Each year, approximately 30,000 cases of Lyme Disease (LD) in the United States are reported by the Center of Disease Control and Prevention (CDC), and the number has been steadily increasing. Previous studies have shown that landscape fragmentation may impact the risk of LD through an increase in tick and host densities as well as human-tick and human-host interactions. In this study, we detected spatial association of LD to landscape fragmentation using the town-level data in Connecticut (CT). We obtained the yearly town-level LD rate data for the period 1991-2020 from the CT Department of Health. On the landscape side, we used the United States Geological Survey’s (USGS) National Land Coverage Dataset (NLCD) of eight years, including 2001, 2004, 2006, 2008, 2001, 2013, and 2016. Using the land cover data and the FRAGSTATS software, we calculated 48 landscape ecological metrics for 15 land cover types for each year. We then evaluated the LD-landscape association using the population-weighted Pearson’s correlation. This is an expansion of earlier exploration in the states of New Hampshire and Maine. This analysis tests the hypothesis that LD is associated with landscape fragmentation in Connecticut. More specifically, developed land cover classes will have a relatively strong association with LD rates. Confounding factors could include the small numbers problem and cases reported without a town-level spatial association.
Authors: by Rena Schwartz, Joseph Earles, Meifang Li, and Xun Shi (all Department of Geography, Dartmouth College)

6. Lyme Disease and Land Cover in Massachusetts
Joseph Earles, Dartmouth College
Each year, approximately 30,000 cases of Lyme Disease (LD) in the United States are
reported by the Center of Disease Control and Prevention (CDC), and the number has been
steadily increasing. Previous studies have shown that landscape fragmentation may impact the
risk of LD through an increase in tick and host densities as well as human-tick and human-host
interactions. In this study, we detected spatial association of LD to landscape fragmentation
using the town-level data in Massachusetts (MA). We obtained the yearly town-level LD count
data for the period 2010-2014 from the MA Department of Health, and calculated rate using
yearly population estimates from the University of Massachusetts. On the landscape side, we
used the United States Geological Survey’s (USGS) National Land Coverage Dataset (NLCD) of
2011 and 2013. Using the land cover data and the FRAGSTATS software, we calculated 48
landscape ecological metrics for 15 land cover types for each year. We then evaluated the
LD-landscape association using the population-weighted Pearson’s correlation. This is an
expansion of earlier exploration in the states of New Hampshire and Maine. This analysis tests
the hypothesis that LD is associated with landscape fragmentation in Massachusetts. More
specifically, developed land cover classes will have a relatively strong association with LD rates.
Confounding factors could include the small numbers problem and cases reported without a
town-level spatial association.
Authors: Rena Schwartz, Joseph Earles, Meifang Li, and Xun Shi (all Department of Geography, Dartmouth College)