A promising daytime smoke plume detection for a land-based early forest fire detection system is proposed. The visible video imagery from a land-based monitoring camera is processed to detect the smoke which likely rises in an early stage of a forest fire. Unlike the fire core and its surrounding heat which are detected via day/night infrared imaging, the relatively cold smoke plume can only be captured in the visible spectrum of light. The smoke plume is detected via exploitation of its temporal signature. This is accomplished via Principal Component Transformation (PCT) operations on consecutive sequences of visible video frames followed by spatial filtering of one of the resulting low-order Principal Component (PC) images. It is shown that the blue channel of the Red, Green, Blue (RGB) color camera is most effective in detecting the smoke plume. Smoke plume is clearly detected and isolated via simple blurring, thresholding, and median filtering of one of the resulting low-order principle component (PC) images. The robustness of this PCA-based method relative to simple temporal frame differencing and use of color, i.e., visible spectral signature of smoke, are discussed. Various parameters of the system including the required observation time and number of frames to retain for PCT, selection of which low-order PC to use, and types and sizes of the filters applied to the selected PC image to detect and isolate the smoke plume, are discussed.