Title
The Sensitivity of Mapping Methods to Reference Data Quality: Training Supervised Image Classifications with Imperfect Reference Data.
Abstract
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 cover classifications from airborne thematic mapper data are explored. Variations in sampling intensity and effort are highlighted in a dataset that is widely used in mapping and modelling studies; these may need accounting for in analyses. The quality of the labelling in the reference dataset was also a key variable influencing mapping accuracy. Accuracy varied with the amount and nature of mislabelled training cases with the nature of the effects varying between classifiers. The largest impacts on accuracy occurred when mislabelling involved confusion between similar classes. Accuracy was also typically negatively related to the magnitude of mislabelled cases and the support vector machine (SVM), which has been claimed to be relatively insensitive to training data error, was the most sensitive of the set of classifiers investigated, with overall classification accuracy declining by 8% (significant at 95% level of confidence) with the use of a training set containing 20% mislabelled cases.
Year
DOI
Venue
2016
10.3390/ijgi5110199
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Keywords
Field
DocType
classification,training,error,accuracy,remote sensing,land cover
Reference data (financial markets),Data mining,Thematic Mapper,Data quality,Imperfect,Pattern recognition,Support vector machine,Artificial intelligence,Sampling (statistics),Thematic map,Geography,Land cover
Journal
Volume
Issue
ISSN
5
11
2220-9964
Citations 
PageRank 
References 
1
0.37
0
Authors
5
Name
Order
Citations
PageRank
Giles M. Foody137439.06
Mahesh Pal2948.50
Duccio Rocchini313419.99
Carol X. Garzon-Lopez410.37
Lucy Bastin516417.19