The California Camp Fire is California’s deadliest fire to date, largely a result of dry fuel and weather conditions, drought, and directional winds. As I aimed to apply remote sensing to the enhancement and expedition of wildfire detection, this research investigates the implementation of commercial satellite shortwave infrared (SWIR) multispectral imagery (MSI) for precise geo-location of active wildfires through heavy smoke clouds over affected regions. Utilizing ENVI and data collected by DigitalGlobe’s WorldView-3 satellite, which has an 8-band SWIR MSI sensor with a peak spatial resolution of 3.7 meters, I was able to identify the exact locations of the wildfires and track their movement through dense smoke from November 15 to 20. Particularly, I derived class images based on regions of interest where the detected radiance of Band 8 was over a value of 500 mW/cm²-sr-nm, a minimum threshold determined by analysis of a Band 8 radiance histogram. I further employed ArcGIS’ ArcMap to provide geospatial registering of the data, displaying the SWIR MSI false-color with RGB from Bands 8, 2, and 1, respectively, and the accompanying wildfire class images. Additionally, I affirmed that Band 8 is the optimal band for detection due to its greatest sensitivity, or the ratio of intensity of the fire and non-fire pixels. Ultimately, this research illuminated the significance of SWIR MSI for high-accuracy detection of wildfires through smoke in the context of the California Camp Fire, with global implications for enabling emergency response teams to rapidly determine the extent of a wildfire.