Spring NEARC 2018 has ended
Welcome to the interactive web schedule for the 2018 Spring NEARC Conference! For tips on how to navigate this site, visit the "Helpful Info" section. To return to the NEARC website, go to: www.northeastarc.org/spring-nearc.html.

UPDATE AS OF MAY 16: Some of our presenters have made their slides or other resources available to download. Under the "Filter by Type" heading, click on "Presentation Slides Available" to view which ones have been posted. Check back for updates! 

Sign up or log in to bookmark your favorites and sync them to your phone or calendar.

Concurrent Sessions (30 Minutes) [clear filter]
Tuesday, May 8

3:00pm EDT

PRESENTATION: Did You See NBEP's Poster at the Fall Conference? This Is How We Did It. Harmonizing Data Across States to Create Sound and Natural Resource Indicators in a Shared GIS Database
AUTHORS: Eivy Monroy*, Narragansett Bay Estuary Program; Julia Twichell, Narragansett Bay Estuary Program; Anne Kuhn, US EPA Atlantic Ecology Division; Mike A. Charpentier, CSRA; Jessica Cressman, Environmental Data Center URI; Juliet Swigor, MassDEP; Peter August, University of Rhode Island; Paul Jordan, RIDEM; Courtney Schmidt, Narragansett Bay Estuary Program.

ABSTRACT: The poster presented at the 2017 NEARC Fall Conference "2017 State of the Bay and Its Watershed, Mapping Drivers of Change and Variation" was awarded People's Choice and Best Overall. This presentation describes the process and practices related to the results displayed on the poster and documented in 2017 State of Narragansett Bay and Its Watershed report by the Narragansett Bay Estuary Program (NBEP). The Narragansett Bay Watershed is bi-state (MA and RI) and there are obvious challenges for compiling and harmonizing data in a seamless way across political boundaries for which data are not consistent, insufficient, or not comparable in terms of what data is collected, data definition, and temporal and geographic-scale. These challenges are compounded when dealing with an extensive range of environmental indicators. The approach involved three best practices ? partnerships, data selection with a focus on spatial and temporal scales and representativeness, and using proper (and diverse) methods for each indicator (including advanced geospatial tools in ArcMap, and Dasymetric Analysis). The goal of bringing harmonized data together and developing sound science and data management continues with creating data sharing protocols and updating databases. Concrete benefits are visible - NBEP partners representing state, NGO, and academic institutions are requesting and using the improved geospatial and tabular data and results for their own initiatives, outreach and watershed management. Use of data that cuts across political boundaries facilitates better management for a common purpose - the conservation and enhanced environmental management of the bi-state Narragansett Bay and watershed.

Tuesday May 8, 2018 3:00pm - 3:30pm EDT
Room 201

3:30pm EDT

PRESENTATION: Using Gazpacho and ArcGIS to Create Forecast Snowfall Bias, Error, and Composite Maps Stratified by Flow Regime
AUTHORS: Joseph P. Villani, NOAA/National Weather Service Albany, NY

ABSTRACT: In order to evaluate patterns of snowfall forecast error, the Gridded Automated Zonal Precipitation and Complete Hi-Res Output (GAZPACHO) verification program and ArcGIS were used to create maps of observed snowfall, zone-average snowfall and forecast error maps for 56 snowfall events in the National Weather Service Albany, NY County Warning Area (ALY CWA; eastern New York and western New England). Events from the 2013-2017 winter seasons were used for the study. The criteria for an event was when at least advisory level snow fell or advisory level snow was forecast (around 4 inches or greater somewhere in the ALY CWA). Each event was categorized by determining a representative wind direction and speed at 925 and 850 mb. The wind direction categories were 0-90, 90-180, 180-270, and 270-360. The wind speed categories were 0-19 kt, 20-39 kt, and 40 kt or greater. Twelve categories were defined based on the various direction and speed combinations. The winds were derived from Albany, NY (ALY) observed sounding data for each snowfall event. The wind direction and speed (at 0000 or 1200 UTC) closest to the midpoint time of each event was used to categorize each event. Forecast bias, mean absolute error (MAE), and snowfall composite maps were created for each of the twelve wind categories from the 56 total snowfall events using ArcGIS. Since there were 12 wind categories and 56 total snowfall events, some of the categories only contained a few events. However, there were several wind categories with five or more events. Results from a few of the wind categories using 925 mb winds will be presented, with some discernible patterns noted in the forecast bias, MAE and snowfall composite maps. It is hypothesized that some of the larger forecast biases can be attributed to terrain influences based on the over/under forecast of snowfall in favored upslope/downslope areas in the ALY CWA.

Tuesday May 8, 2018 3:30pm - 4:00pm EDT
Room 201

4:00pm EDT

AUTHORS: Peggy Minnis

ABSTRACT: Ten semesters of teaching a free online Desktop GIS class has yielded information about who takes such a course, what the retention of students is, how the students respond to their electronic rewards and how they evaluate the course when they finish.

Tuesday May 8, 2018 4:00pm - 4:30pm EDT
Room 201