In this paper, first, based on landscape ecology theories, we respectively selected indexes from 4 aspects, area, edge, shape, and density, of the landscape type to describe the status of forest landscape patterns, and we established the stability index of landscape pattern (LSBI). Then, based on geo-statistical theories, we divided the forest in the reservoir area into 3990 grids of 4 km × 4 km using network technology and employing ordinary Kriging modelling to make trend surface analyses of the forest resources in the reservoir area. Finally, based on statistics principles, we used sampling theory to systematically extract 227 samples to obtain 7 periods of remote-sensing data from 1990a to 2012a. Then, we classified and extracted the forest in the sampling area using remote sensing, and we analysed each result with an Autoregressive Integrated Moving Average Model (ARIMA) time-series model. The results indicated the following: 1) the landscape structure of the reservoir area was primarily needle-leaved forest, broad-leaved forest and bush forest, and the mixed stands and bamboo stands were secondary;2) the difference of the forest landscape pattern stability in the reservoir area, in all directions, was not significant, but the southern region was slightly more stable;and 3) the stability of the forest landscape pattern in the reservoir area increased from 1990a to 2012a. It kept increasing until 2016a. This study provides a theoretical basis for the reasonable management and decisions about the forest resources in the Three Gorges Reservoir Area. Meanwhile, it also explores methods for relevant research and has practical significance.
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