Precision conservation—projects at the right place, the right scale, the right size, the right time, and making sure they are working—is going to redefine how landscape conservation is approached. Instead of sweeping acquisitions or all-encompassing legislation, we can use the latest high-resolution datasets to conduct advanced geospatial analysis that allows us to better target and implement on-the-ground a...
The Conservation Innovation Center is the technology shop of the Chesapeake Conservancy that offers assistance related to geographic information systems (GIS) and similar mapping technologies. CIC staff are trained and qualified to produce high-resolution datasets, conduct complex geospatial analyses, and develop user-friendly desktop and web applications. These products and services act as decision-support tools that increase an organization’s capacity to plan, prioritize, and implement conservation and restoration work.
The CIC works with organizations of all types and sizes, including land trusts, community watershed organizations, soil and water conservation districts, private environmental firms, and local, state, and federal agencies. No matter who we work with, we emphasize the importance of understanding each organization’s unique challenges and designing customized solutions. We strive to help our partners integrate geospatial data and analyses into their work to effectively overcome these challenges. In addition to developing new products, we also conduct hands-on training, host workshops, and create customized user’s guides.
For more information, contact us at [email protected]
Data Generation Services
The CIC provides a variety of data generation services to help your organization generate, collect, or transform the information you need to be successful.
Imagery Analysis translates raw aerial and satellite imagery into usable data that can categorize the landscape and help make decisions about where and how to work.
The Conservation Innovation Center helps partners understand what imagery is available, determine what is best suited for your project, and can provide a full suite of image analysis services that help you get the information you need to make informed management decisions at all scales, from watershed wide to project specific, including:
• Supervised, Unsupervised, and Object Based Land Cover Classifications
• High Resolution Land Cover Generation
• Satellite and aerial image interpretation and feature extraction
• Change Detection and time-series analysis
• NDVI and vegetative health analysis
• Data Acquisition, cleaning, and mosaicing
• Geo-referencing and correcting scanned images and maps
Lidar elevation data can be leveraged to understand the landscape in three dimensions, leading to a greater understanding of how a system works
Managers need to be able to model the landscape with a high degree of precision to understand how small changes in project design or location can create dramatic differences in a project’s effectiveness. Starting with hundreds of millions of points, LIDAR can be processed into a variety of high-resolution products that provide this detail including :
• “Bare Earth” Digital Elevation Models (DEMs) and “First Return” Digital Surface Models (DSMs)
• Normalized Digital Surface Models (nDSMs) depicting canopy and building heights
• Hydrologically conditioned DEMs for hydrologic modeling
• Flow Direction, Flow Accumulation, and Concentrated Flow Path Mapping
• Slope, aspect, and other surface modeling
Data cleaning and processing can enable an organization to base decisions about future projects on the most current information.
Legacy data, collected in spreadsheets, access databases, or even on paper, can hold critical insights for project planning and design, but only if they can be integrated into today’s systems. The CIC has developed methods to clean, format, and integrate a variety of data sources so that it works for your process including:
• Formatting, standardizing, and remapping fields between datasets
• QA/QC’ing data to ensure consistency, quality, and accuracy of datasets
• Mapping spatial data that currently exists only in tabular form
