A common approach for quantifying landscape pattern through landscape metrics is to use categorical maps of entire landscape. However, a new interest is to use sampling data where the data are collected for only a small fraction of the entire landscape. In sample based approaches some currently used landscape metrics may not be estimated since these metrics are defined based on mapped data. Shannon’s diversity index is a frequently used metric in landscape pattern analysis. In this study, the performance of the normalized Shannon’s diversity index is demonstrated when using sampled full-coverage maps and then point sampling on the maps. Artificial and real landscapes have been employed for this purpose. The results showed that calculation of the normalized Shannon’s diversity index based on the number of land cover types in the entire classification system is more appropriate than based on the number of land cover types present within landscape. There was a strong and positive correlation between reference and estimated values but the estimator of Shannon’s diversity index was slightly and negatively biased. In conclusion, it is needed to slightly redefine some currently used landscape metrics to accommodate sampling data.