Rating the quality of post-disaster damage maps: Mapping building damage after the 2010 Haiti earthquake

Post-disaster building damage maps are an important component of the disaster response chain and may be derived from remotely sensed data. The usefulness of the maps is a function of their accuracy and hence information on map accuracy is desirable. The assessment of building damage map accuracy is, however, a challenging task as high quality ground reference data are usually scarce or absent. Here, binary and ordinal level latent class analyses were used to evaluate the accuracy of five maps produced after the 2010 earthquake in Haiti. The quality of the estimates derived from the analyses could be evaluated in this case as a ground data set was available. The results showed that the latent class analyses were able to yield an accurate assessment of the relative accuracy of the maps, allowing maps to be ranked in order of quality. This feature may help disaster relief activities by ensuring the highest quality data are used.