Do remote sensing classification errors influence landscape metrics?
LANGFORD, BILL 1 and *GERGEL, SARAH E. 2, 1 National Center for Ecological Analysis and Synthesis, Santa Barbara, CA2 Centre for Applied Conservation Research, Vancouver, BC ABSTRACT- Remote sensing imagery is routinely classified into different land cover types and then used as base maps to measure fragmentation using landscape metrics such as mean patch size, number of patches, etc. No classified map, however, is ever completely accurate, and classification errors are often greater at boundaries between cover types. We used a set of replicated synthetic landscapes with varying proportions of habitat and clumpiness to determine whether different maps with the same classification error rates could have different errors in landscape metrics. First, we created a set of simulated correct base landscapes with two cover types, representing a map classified into habitat and background with no error. We then simulated classification errors on these maps to create incorrect or misclassified ma
