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Title:

A Cluster Graph Approach to Land Cover Classification Boosting

Document type:
Zeitschriftenaufsatz
Author(s):
Hughes, Lloyd H. ; Streicher , Simon ; Chuprikova , Ekaterina; Preez, Johan D.
Abstract:
When it comes to land cover classification, the process of deriving the land classes is complex due to possible errors in algorithms, spatio-temporal heterogeneity of the Earth observation data, variation in availability and quality of reference data, or a combination of these. This article proposes a probabilistic graphical model approach, in the form of a cluster graph, to boost geospatial classifications and produce a more accurate and robust classification and uncertainty product. Cluster gr...     »
Journal title:
Data
Year:
2019
Journal volume:
4
Journal issue:
1
Fulltext / DOI:
doi:10.3390/data4010010
WWW:
https://www.mdpi.com/2306-5729/4/1/10
Publisher:
MDPI AG
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