Twin Cities Metropolitan Area Urban Tree Canopy Assessment (2015) Datasets University Of Minnesota Public content

Description:
A high-resolution (1-meter) tree canopy assessment was completed for the Twin Cities Metropolitan Area. Mapping of existing and potential tree canopy is critical for urban tree management at the landscape level. This classification was created from combined 2015 aerial imagery, LIDAR data, and ancillary thematic layers. These data sets were integrated using an Object-Based Image Analysis (OBIA) approach through multi-resolution image segmentation and an iterative set of classification commands in the form of customized rulesets. eCognition Developer was used to develop the rulesets and produce raster classification products for TCMA. The results were evaluated using randomly placed and independent verified assessment points. The classification product was analyzed at regional scales to compare distributions of tree canopy spatially and at different resolutions. The combination of spectral data and LiDAR through an OBIA method helped to improve the overall accuracy results providing more aesthetically pleasing maps of tree canopy with highly accurate results.
Creator:
Knight, Joe F., Rampi, Lian P., and Host, Trevor K.
Provider:
University of Minnesota
Resource Class:
Datasets
Resource Type:
Raster data and LiDAR
Subject:
Trees and Tree canopies
Theme:
Imagery and Landcover
Temporal Coverage:
2015
Date Issued:
2017-01-03
Spatial Coverage:
Minneapolis-St. Paul-Bloomington, Minnesota and Minnesota
Rights:
https://conservancy.umn.edu/pages/drum/policies/#terms-of-use
License:
http://creativecommons.org/publicdomain/zero/1.0/
Access Rights:
Public
Format:
GeoTIFF
More details at:
http://doi.org/10.13020/D6C016

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