Spatial accuracy measures of soft classification in land cover

What:
Poster
When:
Thursday Sep 29   03:30 PM to 05:30 PM (2 hours)
Tags:
Accuracy assessmentGeographically weighted modelSoft classification
Discussion:
0
Accuracy of land cover maps is important for map users. The soft classification of land cover has been developed for avoiding mixed pixel problem, however the proportional map is traditionally assessed only by a global measure, such as R-squared and root mean square error (RMSE), lacking local information of accuracy. We developed a way of local measures of accuracy employed by a geographically weighted (GW) model. GW-Rsquared and GW- RMSE are locally assessed a soft classification map of urban agglomeration as a case study. Lower accuracies are found at the edge of urban boundary surrounding the core of the urban area and such local information is valuable for a deeper understanding of spatial accuracy.
Participant
Kyoto Univeristy
Participant
University of Leeds

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