1. A forest fire smoke detection method using random forest classification, the method detecting forest fire smoke from frames consecutively captured by video imaging equipment, the forest fire smoke detection method comprising: (a) setting a first reference value that is a reference required to classify candidate blocks; (b) with respect to a plurality of consecutively captured frames, comparing images between the frames, setting each block, in which a number of pixels, motions of which have been identified, is equal to or greater than the first reference value, as a candidate block, and selecting a keyframe from among frames that each include one or more candidate blocks; (c) comparing the selected keyframe with at least one frame previous to the keyframe and then extracting a plurality of feature vectors from the candidate blocks; (d) causing the extracted feature vectors to be learned using different random forest algorithms; (e) accumulating probabilities output to terminal nodes for classes generated as a result of the learning, and then generating two first cumulative probability histograms, each having a size identical to a number of the classes; (f) averaging the two first cumulative probability histograms for the individual classes, and then generating a second cumulative probability histogram; and (g) determining a detected state of each candidate block depending on a class having a highest probability among the classes constituting the generated second cumulative probability histogram.