Twin Cities Metropolitan Area 1-Meter Land Cover Classification (Impervious Surface Focused)

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Collection period

Date completed

2016-06-30

Date updated

Time period coverage

2011 - 2015

Geographic coverage

-94.03 -92.71 45.44 44.46

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Title

Twin Cities Metropolitan Area 1-Meter Land Cover Classification (Impervious Surface Focused)

Published Date

2016-08-01

Author Contact

Knight, Joe F
jknight@umn.edu

Type

Dataset
Map
Spatial Data

Abstract

A high-resolution (1-meter) land cover classification raster dataset was completed for three different geographic areas in Minnesota: Duluth, Rochester, and the seven-county Twin Cities Metropolitan area. This classification was created using high-resolution multispectral National Agriculture Imagery Program (NAIP) leaf-on imagery (2015), spring leaf-off imagery (2011- 2014), Multispectral derived indices, LiDAR data, LiDAR derived products, and other thematic ancillary data including the updated National Wetlands Inventory, LiDAR building footprints, airport, OpenStreetMap roads and railroads centerlines. These data sets were integrated using an Object-Based Image Analysis (OBIA) approach to classify 12 land cover classes: Deciduous Tree Canopy, Coniferous Tree Canopy, Buildings, Bare Soil, other Paved surface, Extraction, Row Crop, Grass/Shrub, Lakes, Rivers, Emergent Wetland, Forest and Shrub Wetland. We mapped the 12 classes by using an OBIA approach through the creation of customized rule sets for each area. We used the Cognition Network Language (CNL) within the software eCognition Developer to develop the customized rule sets. The eCognition Server was used to execute a batch and parallel processing which greatly reduced the amount of time to produce the classification. The classification results were evaluated for each area using independent stratified randomly generated points. Accuracy assessment estimators included overall accuracies, producers accuracy, users accuracy, and kappa coefficient. The combination of spectral data and LiDAR through an OBIA method helped to improve the overall accuracy results providing more aesthetically pleasing maps of land cover classes with highly accurate results.

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Previously Published Citation

Suggested citation

Host, Trevor K; Rampi, Lian P; Knight, Joe F. (2016). Twin Cities Metropolitan Area 1-Meter Land Cover Classification (Impervious Surface Focused). Retrieved from the Data Repository for the University of Minnesota (DRUM), http://doi.org/10.13020/D6959B.
View/Download file
File View/OpenDescriptionSize
tcma_lc_finalv1.zipCompressed ZIP file of the Twin Cities Metro Area 1-Meter Land Cover Classification data454.19 MB
TCMA_1m_LandCover_Metadata.htmlMetadata for TCMA 1-Meter Land Cover Classification in HTML Format31.99 KB
TCMA_1m_LandCover_Metadata.xmlMetadata for TCMA 1-Meter Land Cover Classification in XML Format49.02 KB
Map_and_Legend.pdfTCMA Overview Map and Legend1.59 MB
Classification scheme for Level 1 and 2 land cover classes.pdfClassification Scheme70.46 KB

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