Wildfires are major disturbances that can leave lasting impacts on the ecosystem, biodiversity, and our society. Just this past year, over 4 million acres of land were burned across California, making the 2020 fire season the largest ever recorded in the state. Using three indices derived from satellite data, NDVI, EVI, and GPP, the post-fire recovery values in the indices were analyzed, and the results were used to determine whether vegetation type could affect the recovery. Three fires from the 2004 fire season in Alaska were selected to mimic the forest ecosystems in California without direct disturbances from human activities. MODIS-derived images were extracted from the Earth Explorer database every year from 2000-2018 and individually processed in QGIS to calculate NDVI, EVI, and GPP. The data of pre-fire areas from 2000-2003 was averaged and used as a control and reference area. NDVI and EVI values in post-fire recovery were extremely similar in areas with dense conifer populations and took an average of 8 years to recover, while GPP values show quicker recovery at only 3 years. Results also demonstrate that an area with a balance of 46% shrubs and 40% conifers recovered much faster, at around 3 years for all indices, in comparison to areas with 76% dense conifer populations. Using only one index is not enough for the most accurate results and it is critical to implement a variety of remote-sensing techniques in forest planning and recovery.