Abstract: This paper classified land use and vegetation types of Ningbo with Landsat remote sensing data of 6 times (1974～2009) using 3S methods, extracted the regions of different vegetation types which turn into evergreen broad-leaved forest in each period and calculated transformation rate of every type for evergreen broad-leaved forest. Results showed that physical succession rules and economic benefits are the main causes of evergreen broad-leaved forest dynamic changes in the past 37 years. It is likely to conversed with coniferous and broad-leaved mixed forest and evergreen and deciduous broad-leaved mixed forest without considering human influence. On this basis, we measured the distance between vegetation types turned into evergreen broad-leaved forest in each period and the type remained evergreen broad-leaved forest in the same period, calculated total average value of five periods, and ordered them by vegetation types: coniferous and broad-leaved mixed forest>evergreen and deciduous broad-leaved mixed forest>bamboo>coniferous forest>tea plantations and orchards>shrub>farmland, it is found that seed spread and land use history are key factors which affected direction of degraded evergreen broad-leaved forest community’s secondary succession.

Key words: evergreen broad-leaved forest, remote-sensing classification, community dynamics, Ningbo