Zoning types of mountain forest restoration in the upper Min River supported by image auto-recognition system

Abstract

Image auto-recognition system is a processing platform for extracting the grid data of characteristic element from original map and converting grid data to vector data. Selecting five maps about precipitation, evaporation, vegetation, soil erosion, and human activities, this paper applied images auto-recognition system and GIS technique to define and distinguish the boundary between natural restoration, human reconstruction and arid zone in the Upper Reaches of Min River. The results show that: images auto-recognition system efficiently extracted the grid data of characteristic element from original landscape patterns, and converted the grid data to vector data accurately. component; images auto-recognition system, forest restoration, the Upper Reaches of Min River, Zoning, GIS, map element vectorization INTRODUCTION