TechnicalGIS

#Confusion matrix

2 posts

Bar chart comparing the area of each land cover class in Ireland from WorldCover pixel counting with the error-adjusted estimate and its 95% confidence interval.

Tutorial Remote Sensing

Land cover accuracy assessment in Python: confusion matrix, Olofsson area estimates and sample size

Assess a real land cover map in Python: ESA WorldCover 2021 against 8,597 Eurostat LUCAS 2022 field survey points in Ireland. Build the confusion matrix, compute overall, user's and producer's accuracy, see why kappa is discouraged, and use the Olofsson et al. (2014) stratified estimators to get error-adjusted areas with 95% confidence intervals and to plan a new stratified random sample.

Advanced 20 min read

Two habitat maps of the Dark Peak side by side. Left: the rule-based map from Sentinel-2, with purple blanket bog and lilac heath on the Kinder and Bleaklow plateaux, orange bracken on the valley sides, green grassland and woodland in the valleys and blue reservoirs in the Derwent valley. Right: Living England 2022-23 for the same area, with smoother patches of the same classes.

Tutorial Python Part 1 of 5

Habitat mapping with Sentinel-2 in Python: spectral index rules and an honest accuracy assessment

Map blanket bog, heath, bracken, grassland, woodland, water and built-up land in the Peak District from 2023 Sentinel-2 seasonal composites with an eight-rule spectral index classifier, then assess it properly: a confusion matrix, user's and producer's accuracy, kappa and its caveats, block-bootstrap confidence intervals, and why a random train/test split overstates accuracy.

Beginner 19 min read