Minnesota Land Cover Classification and Impervious Surface Area by Landsat and Lidar: 2013-14 Update

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Persistent link to this item

http://doi.org/10.13020/D6JP4S
https://hdl.handle.net/11299/181555

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Keywords

Landsat

Lidar

object based image classification

land cover

impervious surface area

Collection period

Date completed

2016-01-15

Date updated

Time period coverage

Geographic coverage

Source information

See complete lineage information in the metadata file

Journal Title

Journal ISSN

Volume Title

Title

Minnesota Land Cover Classification and Impervious Surface Area by Landsat and Lidar: 2013-14 Update

Published Date

2016-08-03

Authors

Rampi, Lian P

Knight, Joe F

Bauer, Marvin

Group

Remote Sensing and Geospatial Analysis Laboratory, University of Minnesota

Author Contact

Knight, Joe F
jknight@umn.edu

Type

Dataset
Map
Spatial Data

Abstract

This is a 15-meter raster dataset of a land cover and impervious surface classification for 2013-14, level two classification. The classification was created using a combination of multitemporal Landsat 8 data and LiDAR data with Object-based image analysis. By using objects instead of pixels we were able to utilize multispectral data along with spatial and contextual information of objects such as shape, size, texture and LiDAR-derived metrics to distinguish different land cover types. While OBIA has become the standard procedure for classification of high resolution imagery we found that it works equally well with Landsat imagery. For the objects classified as urban or developed, a regression model relating the Landsat greenness variable to percent impervious was developed to estimate and map the percent impervious surface area at the pixel level.

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License

CC0 1.0 Universal Public Domain Dedication
http://creativecommons.org/publicdomain/zero/1.0/

Publisher

Collections

Data Repository for U of M (DRUM)

Funding information

Funding provided by the Minnesota ENTRF (Environment and Natural Resources Trust) as recommended by the Legislative-Citizens Commission on Minnesota Resources

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Previously Published Citation

Suggested citation

Rampi, Lian P; Knight, Joe F; Bauer, Marvin. (2016). Minnesota Land Cover Classification and Impervious Surface Area by Landsat and Lidar: 2013-14 Update. Retrieved from the Data Repository for the University of Minnesota (DRUM), http://doi.org/10.13020/D6JP4S.

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