Abstract:This paper systematically explains the nonlinear effects of the classification errors of remotely sensed data on the errors of landscape indices. The explanations are made mainly through hypothetical examples and case studies, including the global and regional land use data. On one hand, remote sensing technology meet the needs of landscape ecology by providing necessary land use and land cover data; on the other hand, remote sensing technology varies so sophistically that all the land use and land cover da...