loader image

Ecopia AI enhances land use insights with new agricultural data layers

Reading Time: 2 minutes

Ecopia AI has announced the release of new agricultural land use vector data, enhancing the 3D Nationwide Land Cover dataset with unprecedented detail. These planimetric vector data layers will empower government agencies to conduct more comprehensive geospatial analytics, including water usage, tax assessment, land development, runoff calculations, and other detailed analysis workflows.

Launched in 2022, the 3D Nationwide Land Cover dataset includes 14 high-precision 2D data layers classifying various land use types and height-attributed (3D) feature classes for buildings, trees, and bridges. Derived from high-resolution geospatial imagery from Ecopia’s global partner network, these standard data layers support diverse mapping and analytics applications across the United States, such as stormwater management, public safety, natural hazard mitigation, and urban/community planning.

With the introduction of these additional land use data layers, organizations can further classify ‘grass’ and ‘agriculture’ features into more specialized categories. Ecopia’s AI-based mapping systems can now distinguish ‘grass’ as either ‘developed open space’ or ‘wild grass,’ while ‘agriculture’ features can be identified as either ‘pasture’ or ‘cultivated crops.’ A sample of this data for Brown County, Wisconsin, is available for exploration here.

Practical and accessible land cover databases

Traditional methods for producing detailed planimetric land use data involve manual digitization and classification of geospatial imagery, which are labour-intensive, costly, and can take over a year for a single city. As government organizations increasingly rely on geospatial data for critical decisions, these methods are impractical, especially with rapid urban development requiring up-to-date information.

Ecopia’s AI-based mapping systems can extract high-precision land use vector data from geospatial imagery in weeks. This efficiency enables government agencies to create and maintain accurate land cover databases across entire jurisdictions, ensuring decisions are based on current, real-world conditions, and preventing misallocation of resources and funding.

The four new planimetric layers produced by Ecopia further align the company’s data offerings to similar environmental datasets produced by the US government, including the USGS’s National Land Cover Database and NOAA’s Coastal Change Analysis Program (C-CAP) data. Earlier this year, Ecopia’s AI-powered mapping systems increased the resolution of C-CAP data by 900x (from 30 metres to 1 metre), providing open access to high-resolution land cover across 1.5M square miles of US coastal communities. This technical alignment with other authoritative datasets commonly used for geospatial analytics also complements recent investments in the USDA’s National Agriculture Imagery Program (NAIP), providing deeper insights for government agencies to leverage in various environmental stewardship initiatives.

“Ecopia is thrilled to launch four new data layers to power unprecedented visibility into land use across the US,” said Brandon Palin, senior director of Public Sector and International Development at Ecopia. “Vector data with this level of detail has long been too resource-intensive or expensive for government organizations to produce at scale, and we are proud to leverage our advanced AI-powered systems to provide stakeholders with the geospatial insights needed to make informed decisions related to climate resilience, land use planning, urban development, and more critical initiatives.”

Ecopia AI’s agricultural land use vector data adds a new level of detail to the 3D Nationwide Land Cover dataset. (Image courtesy: Ecopia AI)

Source link

share this article
  • This field is for validation purposes and should be left unchanged.

Subscribe to receive the latest business and industry news in your inbox.

  • This field is for validation purposes and should be left unchanged.

latest from the industry
Lidar news

Whitepaper

  • This field is for validation purposes and should be left unchanged.

  • This field is for validation purposes and should be left unchanged.

Use