Image texture is becoming more and more important with the increasing spatial resolution of optical satellite images. However, it is a very complex spatial attribute that can vary significantly with solar/viewing geometries, topographic conditions, and the object of interest as well as its location. Besides, the selection of texture variables and the set of their corresponding input parameters, for instance, window sizes, inter-pixel distances, directions and quantization levels, determine the efficiency of image texture. How to apply texture variables and optimize their combination is worth further studying. Therefore, we firstly reviewed the latest researches and applications of image texture in forest classification, inversion of stand structure parameters, and estimation of forest biomass and carbon storage, and prospected the potential of image texture in the remote sensing of forestry from different aspects. In addition, we summarized the critical problems in the current research field based on the selection and optimal combination of texture variables and their input parameters. Some suggestions have also been proposed for further effective applications of image texture in the field of forestry.