Fall NEARC 2024

New to NEARC? Join us for a casual overview of the event and how to get the most out of your experience!

Greenman-Pedersen, Inc. (GPI) is a multi-disciplinary civil engineering firm with projects covering the eastern half of the United States. While the information GPI uses to manage clients and projects is stored in an Enterprise Resource Planning (ERP) Software, it is not easily viewable in a map, and therefore unavailable for any spatial analyses.

The Innovation Team at GPI has used the existing ERP data to create an Internal Mapping Application for assisting directors, project managers, engineers, marketing specialists, and other employees to realize various operational efficiencies using previously unmapped data.

This presentation will cover the end-to-end dataflow of the project. Beginning at the initial inputs in the ERP software, and the ETL (Extract, Transform & Load) process where the data is geocoded, cleaned and transformed using a combination of SQL and Python. The data is then securely provided to GPI staff using ArcGIS Online and ArcGIS Enterprise.

While the application is still in beta staff have already begun utilizing the data to enhance their existing workflows, particularly in marketing and branch logistics. Others, such as our corporate safety team, are using it to create completely new workflows which will save significant time and effort in their day-to-day tasks.

ArcGIS Online makes it easy to capture large volumes of data and photos in the field but few out-of-the-box tools exist to neatly convert these data into a traditional report. This presentation will cover the capabilities of the ArcPy and DocxTemplate Python packages towards generating a photo report in a .docx format, a companion photo location map, and hyperlinked spreadsheet for data review. This approach allows for the use of existing Microsoft Word templates in order to match organizational brand standards and enables the end user to make follow-up edits to photo comments and metadata.

Kestrel Land Trust and Green Burial Massachusetts were looking to find a property to establish a conservation cemetery (green burial) in western and/or central Massachusetts. GZA was tasked to conduct a suitability analysis for the conservation cemetery and create a web application to view the results. The GIS analysis was conducted across five counties (Worcester, Hampden, Hampshire, Franklin, and Berkshire) totaling 668,639 land parcels. Using publicly available GIS data, the analysis included identifying criteria for the cemetery site prioritization and used the criteria to establish a baseline and to exclude properties. The selected properties were then ranked based on feasibility characteristics and a suitability score was calculated. A digital web experience application (Experience Builder) was created to showcase the suitability results and allow the clients to view and filter the remaining properties for conservation cemetery site selection. The presentation will provide an overview of the project process, challenges we faced, and take aways.

Soil erosion and slope instability issues are a major concern for New England state Departments of Transportation (DOT), roadway planners, and designers, impacting the cost to maintain transportation networks and other critical infrastructure. Effective screening tools used for modeling, monitoring, and forecasting erosion can aid in assessing erosion and slope failure susceptibility, which is critical for regional operations and planning.

GZA developed a screening-level tool to identify roadways vulnerability to erosion and slope failures based on a number of factors, using the latest GIS Enterprise technology. The work is being performed in collaboration with the New England Transportation Consortium (NETC). The project objective was to develop a multi-scale, multi-season land-based erosion and landslide modeling and monitoring toolkit for infrastructure management for all the New England states (including Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, and Connecticut).

The prototype Esri ArcGIS toolkit was developed for the MaineDOT based on Maine’s state-wide GIS data such as topography, land use, surficial geology, and roadway system inventory. Various environmental parameters were considered as risk factors for roadways, including proximity to surface water body, proximity to the 100-year floodplain, and slope geometric information.

A large set of slope stability simulations were assembled to capture key geotechnical parameters including soil type, material strength, and groundwater depth. This set formed the basis of a “Response Function” that was used to interpolate to all the grid cells in the study area. The end deliverables of this project, i.e., the Esri GIS web viewer, included multiple risk analysis data layers for users to interact with and identify high, medium, and low hazard areas, for screening, analysis, and planning purposes for the Maine DOT.

The innovative approach developed for this project is applicable to other states or even regions and adaptable for future improvements such as inclusion of climate change considerations.

The Cape Cod shoreline is vulnerable to erosion, coastal storm flooding, and sea level rise. Current regulations, including the Massachusetts State Building Code, are based on FEMA Special Flood Hazard Areas as delineated on Flood Insurance Rate Maps. These are developed based on historical flood data and do not consider a future with rising sea levels and intensifying coastal storms. As sea levels continue to rise and storms become more frequent and severe, the limitations of relying on outdated FEMA maps become increasingly apparent. This underscores an urgent need to revise regulations to account for future flood risks.

To address this need, the Cape Cod Commission has designed model bylaws around a concept called the Coastal Resilience Zone. These coastal resiliency regulations allow for flexibility by encouraging Towns to select the best available data to identify future flooding. This ‘best data’ may be the Massachusetts Coastal Flood Risk Model (MCFRM), or an updated model as more reliable data become available. In all cases, applicants must meet current flood resistant construction standards as set in the State Building Code.

As staff developed the resiliency regulations, it soon became apparent that the available MCFRM data and the current enforceable construction standard did not exist in formats that could easily be compared. Learn how we solved this problem by creating design flood elevation layers and see how they fit into a larger suite of Cape Cod Commission map tools that help to illustrate the potential effects of historic and future floods.

Municipalities across the county are combining their local GIS data with federal FAA data to help safely integrate UAVs into their community. Drone enabled cities are seeing public safety, economic development and utility department benefits. This presentation aims to explain the integration framework necessary to achieve these benefits, and to highlight communities that are operating ahead of the curve.

Severe flood events had major impacts on Vermont in July 2023 and July 2024. The UVM UAS Team carried out more than 350 missions in support of rapid response and long-term recovery efforts after these events, deploying a wide range of UAS platforms and sensors to capture critical and timely data. This presentation will discuss the benefits, applications, challenges, and lessons learned from these efforts to inform the future of how UAS technology can be best applied to the next severe weather events in the Northeast, as well as the opportunities for training emergency responders and geospatial professionals on how to begin to use UAS to aid their efforts.

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The University of Vermont is a core-member of the FAA’s ASSURE research center of excellence, which focuses on the integration of UAS into the national airspace. Within ASSURE, UVM’s research focus areas have centered around the application of UAS technology for disaster and emergency response. UVM’s UAS program began in the years following the impacts of Tropical Storm Irene in 2011 and has remained at the forefront of using these technologies to enhance the efficiency for disaster response. UVM was the first organization in the country to respond to a train derailment with UAS and has captured data of tornados, microburst, ice jams, floods, and landslides throughout the state.

From checklists and risk assessments to selecting (and employing!) emergency landing sites to the importance of pre-flighting to how (and when!) to safely fly from the seat of your pants this presentation discusses some of the many lessons learned in well over a decade of commercial drone flying. Presented in easy-to-swallow bites, these lessons are easy to take, adapt, and work into your protocols and procedures. These lessons will provide good value for beginners just starting out, as well as seasoned veteran pilots. At the very least, you can learn how to recover from obliterating your drone in front of a client and still complete the project.

As communities and states modernize their electrical grids to overcome power outages due to energy sources or extreme weather events, emphasis should be placed on equity and resilience. In collaboration with the Vermont Electric Power Company and the University of Vermont College of Engineering and Mathematical Sciences, the Spatial Analysis Lab is supporting the mission of energy resiliency and equity focused on rural Vermont. This project is in collaboration with multiple utility distributions across the state. The wider-project's intent is to support resilience and equity of Vermont’s electrical grid by using geospatial data to fill pressing informational gaps by developing models that utility providers can use to improve energy resiliency in the face of climate change and increasing extreme weather. Specifically, the lab is mapping utility electrical infrastructure information from 2023 statewide Q1 LiDAR data. This presentation will cover the series of techniques used to classify the LiDAR point clouds and custom surface model development. Techniques included such as ERSI's pretrained GEOAI models and active learning to further train LiDAR classification models. With this research, the lab will provide utilities with highly accurate vector data that can be used for utility maintenance and preparedness. This project is funded by the Leahy Institute for Rural Partnerships.

Each fall, Western Arctic caribou migrate across frozen Northern Alaskan rivers to reach wintering grounds. Regional climate changes have altered ice and vegetation phenology dynamics throughout caribou habitats, preventing caribou from crossing rivers and successfully calving. Caribou cannot cross partially frozen rivers and require healthy vegetation in the spring to calve. The Massachusetts NASA DEVELOP Team partnered with the National Park Service in Alaska to analyze changes in river ice formation and terrestrial vegetation. Landsat 8 and 9 Operational Land Imagery, Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Sentinel 1-Synthetic Aperture Radar (SAR) C-band, and Sentinel 2A/B Multispectral Instrument imagery were used to assess ecological conditions relevant to caribou survival. The timing and duration of ice formation was assessed using the Normalized Difference Infrared Index (NDII), Relative Difference River Ice (RDRI), and Vertical-Vertical/Vertical-Horizontal (VV/VH) backscatter values based on the spectral and surface characteristics of rivers. Similarly, phenology cycles were quantified using the Nadir Bidirectional Reflectance Distribution Function Adjusted Reflectance (NBAR) for Normalized Difference Vegetation Index (NDVI) time-series data. The team produced annual freezing timelines, time series plots and maps, and composite imagery at various caribou locations to analyze annual changes. This research compared various optical and radar remote sensing methods in detecting high ice extent and high-quality vegetation over remote Alaska regions where in situ measurements are often infeasible. These study results can help evaluate spatiotemporal migratory shifts and contextualize recent shifting population dynamics.

Current, accurate land cover information is a common foundational data set that can be used to address a wide range of management issues, from flooding risk and natural infrastructure to policy evaluation and land use planning. Knowing what exists on the ground (and how it has changed through time) gives planners more information, and the better that data, the better our understanding.

For more than two decades, NOAA’s Office for Coastal Management has been producing consistent, accurate land cover and change information for the coastal U.S through its Coastal Change Analysis Program (C-CAP), with the goal of continually updating these maps every 5 years. In recent years, NOAA has been working to establish an operational higher resolution land cover product line, allowing for local and site-specific applications. This work has been possible because of the wealth of available imagery and lidar data, improved software and hardware capabilities, and artificial intelligence classification techniques.

This presentation will review the products that have been released for most coastal areas, nationally, plans for additional data and updates, as well as focus on our most recent products (just released) for the state of Maine. We will speak to the methods, accuracy, and potential applications of that data, as well as the partnership NOAA had with the state to fund this mapping.

Monarch butterfly populations are drastically declining due to habitat loss and the species may soon become federally listed. The Monarch Candidate Conservation Agreement with Assurances (CCAA) is a collaborative initiative between the University of Illinois at Chicago (UIC), the United States Fish and Wildlife Service (USFWS), and over 50 entities from the energy and transportation sectors. This agreement provides regulatory predictability for enrolled partners and aims to benefit monarch butterflies through the implementation of existing vegetation management practices on energy and transportation lands that results in a net benefit to monarch butterflies.

This presentation will demonstrate the use of Geographic Information Systems (GIS) and mobile data collection technologies throughout the CCAA application, enrollment, and field monitoring processes. Key topics will include an introduction to the CCAA initiative, illustrative client case studies, methodology for compiling and analyzing spatial datasets, and techniques for conducting spatial analysis of roadway networks and utility corridors to identify potential enrolled and adoptable lands. Additionally, we will discuss ground truthing methods and post-enrollment habitat monitoring procedures. Using these technological methods, these projects take an active and comprehensive effort to protect and restore vital habitats for monarch butterflies across vast areas of the United States.

The New York Natural Heritage Program (NYNHP), a partnership between the New York State Department of Environmental Conservation (NYS DEC) and the State University of New York College of Environmental Science and Forestry (SUNY-ESF), developed and currently maintains the Invasive Species Tiers ( “the Tiers”), which guide management prioritization for hundreds of invasives species with high invasive potential across New York State. Each year, NYNHP runs a spatial analysis to aggregate hundreds of thousands of species observation occurrences for invasive species in and near the state to generate population counts by species, which are then ranked to guide management decisions. After final expert review, the resulting Tier values are published to a public interactive data table which provides links to species distribution maps within iMapInvasives, as well as links to regional views by Tier Value.
This presentation will cover:
1)A brief background of iMapInvasives and community biodiversity data collection platforms,
2)The process by which the Tiers are generated,
3)How these results are shared,
and
4)The impact of the Tiers on invasive species management action and decisions.

NYNHP Invasive Species Tiers:
https://www.nynhp.org/invasives/species-tiers-table/
NYNHP Invasive Species Tier Maps by PRISM:
https://www.nynhp.org/invasives/species-tiers-maps/

The Town of Branford, a Connecticut coastal community bordering Long Island Sound, was looking to update their Natural Resources Inventory (NRI) that had traditionally been a very long, encyclopedic document. The Town had a limited budget with which to update the NRI using the same methods as before; therefore, GZA proposed developing a digital web experience application (Experience Builder) to make the NRI a more interactive experience where the user can search the maps for locations of interest, turn on and off layers, print custom maps, and click web links for more information. This NRI relies heavily on mapping to tell the story while having short summary text with links to organizations that provide more in-depth information on the topic. This web experience utilized publicly available GIS data that is live-linked to the original dataset so that it will automatically incorporate future updates. Additionally, the NRI is more widely accessible to the public where it can be viewed on multiple devices including a laptop, tablet, or phone. This web experience can be used by Town officials and the general public, and also acts as a teaching tool for classrooms to learn more about the natural resources within the Town of Branford. The presentation will provide an overview of the project process, take aways, and discuss future uses of Experience Builder.

In 2022 the Connecticut GIS Office, began collecting parcel and CAMA data from Councils of Governments (COGs). In previous years the information was gathered and packed in zip files for public use. In 2023 the GIS office created the first rendition of a statewide parcel layer from the years collection and published this data in the CT Geodata Portal. The state of Connecticut has been making strides to improve the parcel and CAMA data collection process as well as the parcel and CAMA data itself. This talk will dig into the challenges, findings and future of the Connecticut Parcel and CAMA collection.

This past spring, the City of Boston’s Analytics Team collaborated with the Boston Transportation Department (BTD) to determine where 100 new Bluebike stations (Boston’s bikeshare system) should be placed throughout the city, and why they should go in that location. This project is set to grow Boston’s bikeshare network by 40%- a major impact to the city to expand mobility options for residents.

The Analytics team worked together to apply data science methods and geospatial analysis to make station location recommendations, utilizing data such as job and population density, and ridership and station status. The Bluebikes data was translated into informative metrics such as station trip volumes, instances when stations were empty or full, and a pair of metrics- lost trips and lost returns- that highlighted areas of the city that are not able to meet the existing demand for starting a trip or ending a trip. The team used this data to identify locations with strong latent demand for bike share and to maximize the percentage of households in Boston within close proximity to a Bluebikes station.

In order to provide BTD with specific locations, the team utilized a geospatial suitability modeling approach, inputting dock, population, and job density data, and the new lost trip/return metrics into the model. The suitability modeling was done in two groupings- once for ‘expansion’ stations and one for ‘infill’ stations.
The groups had differences in data inputs as well as how the data was weighted and transformed, due to different priorities for the purpose of that station placement. Once the weights and transforms were applied, the team selected the highest scoring locations (with a minimum buffer distance between existing and proposed stations). Currently, BTD is siting the Analytics Team’s proposed station expansion locations, with plans to begin installation within the next year.

In Vermont, development projects that require historic preservation consultation for federal and state undertakings often necessitate detailed field surveys of buildings and structures, accompanied by comprehensive map exhibits. VHB Preservation Planners consult for an array of clients including municipalities and state transportation agencies, tackling projects ranging broadly in scale from individual buildings to statewide surveys.

This presentation will showcase recent advancements in historic preservation GIS deliverables, emphasizing the use of ArcGIS Experience Builder, and exploring how mobile data collection tools such as ArcGIS Field Maps and Survey123 have improved field data collection in historic preservation. Notable projects involving large-scale field surveys, including the BUILD Grant Mitigation - Rail: Historic Bridge Mitigation Survey, the Town of Brandon Preservation Survey, and the Middlebury Village Historic District Survey and National Register Nomination Update, will be highlighted.

The presentation will demonstrate efficiencies achieved during field survey data collected using Field Maps and the benefits of automated reporting capabilities integrated with the Vermont Architectural Resource Inventory form adapted for Survey123. Additionally, the presentation will highlight the dynamic map deliverables made possible by Experience Builder, underscoring their value in presenting and managing historic preservation data.

As the movement away from “car-only” design continues and more communities integrate Complete Streets planning and design, there is a challenge to collect the detailed data required to scale up from community engagement to actionable, biddable projects. The Town of Barrington, RI recently completed a comprehensive field assessment of its roadways using crowd-sourced data collected via a Survey123 webform. The project provided cost-effective data collection, but also provided public education and coalition building for increased advocacy and implementability. The fieldwork also resulted in Level of User Stress Assessment leading to prioritized capital investment.

The Survey123 form empowers trained volunteers to gather critical data about roadway characteristics, contributing to improved identification of gaps in existing transportation networks and prioritizing projects to improve multimodal transportation infrastructure. Volunteers used the form to record information on:

•Roadway features: Number of lanes, presence and condition of sidewalks and bike lanes
•Traffic conditions: Vehicle speed, traffic volume
•User experience: Perceived stress levels for cyclists and pedestrians

This crowdsourced data, aided by intentional cartographic choices for public engagement, provides valuable insights into the safety and usability of roadways for diverse users. By identifying areas with high stress levels or inadequate facilities, municipal planners and transportation authorities can prioritize improvements, ultimately creating safer and more accessible streets for residents and taxpayers.

In May of 2023, we launched the New Hampshire Zoning Atlas – only the third statewide zoning atlas in a nationwide movement to create a National Zoning Atlas. After wrangling zoning maps and regulations for 269 jurisdictions, the data had to be stitched together into a cohesive statewide zoning layer and analyzed to make some (hopefully) insightful conclusions on zoning’s effect on housing in NH. One of the challenges was how best to tell the story of zoning in NH (spoiler, using a StoryMap), and how to build an interactive viewer for users to explore the data in a meaningful way (spoiler 2 – Experience Builder). Join me for a behind the scenes look at putting the StoryMap and NH atlas together and brief demo of the final product, plus an update on planned improvements moving forward.

Parcel data management can be an efficient and enjoyable process with ArcGIS Pro! This presentation will demonstrate using ArcGIS Pro and esri's Parcel Fabric to work with land record datasets effectively. Workflows and tips & tricks will be discussed for two distinct approaches: (1) use of a simple geodatabase model and (2) use of the parcel fabric. Topology and attribute rules will be covered, as well as using a map series to produce tax maps. The presentation will also cover esri’s latest Parcel Fabric record-driven workflows, its flexible data model, automatic history, and tools unique to the Parcel Fabric dataset. The continued improvements to ArcGIS Pro have made custom tax mapping tools obsolete. Find out why ArcGIS Pro is becoming the standard for land-data management!