The Sensitivity of Mapping Methods to Reference Data Quality: Training Supervised Image Classifications with Imperfect Reference Data

The Sensitivity of Mapping Methods to Reference Data Quality: Training Supervised Image Classifications with Imperfect Reference Data

The accuracy of a map is dependent on the reference dataset used in its construction. Classification analyses used in thematic mapping can, for example, be sensitive to a range of sampling and data quality concerns. With particular focus on the latter, the effects of reference data quality on land c...

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Bibliographic Details
Main Authors: Giles M. Foody, Mahesh Pal, Duccio Rocchini, Carol X. Garzon-Lopez, Lucy Bastin
Format: Article
Language:English
Published: MDPI AG 2016-11-01
Series:ISPRS International Journal of Geo-Information
Subjects:
classification
training
error
accuracy
remote sensing
land cover
Online Access:http://www.mdpi.com/2220-9964/5/11/199

Internet

http://www.mdpi.com/2220-9964/5/11/199

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