Wildfires can be detrimental to urban and rural communities, causing impacts in the form of psychological stress, direct physical injury, and smoke-related morbidity and mortality. This study examined the area burned by wildfires over the entire state of California from the years 2000 to 2020 in order to quantify and identify whether burned area and fire frequency differed across Census tracts according to socioeconomic indicators over time. Wildfire data were obtained from the California Fire and Resource Assessment Program (FRAP) and National Interagency Fire Center (NIFC), while demographic data were obtained from the American Community Survey. Results showed a doubling in the number of Census tracts that experienced major wildfires and a near doubling in the number of people residing in wildfire-impacted Census tracts, mostly due to an over 23,000 acre/year increase in the area burned by wildfires over the last two decades. Census tracts with a higher fire frequency and burned area had lower proportions of minority groups on average. However, when considering Native American populations, a greater proportion resided in highly impacted Census tracts. Such Census tracts also had higher proportions of older residents. In general, high-impact Census tracts tended to have higher proportions of low-income residents and lower proportions of high-income residents, as well as lower median household incomes and home values. These findings are important to policymakers and state agencies as it relates to environmental justice and the allocation of resources before, during, and after wildfires in the state of California.

Satellite-based active fire (AF) products provide opportunities for constructing continuous fire progression maps, a critical data set needed for improved fire behavior modeling and fire management.This study aims to investigate the geospatial interpolation techniques in mapping daily fire progression and assess the accuracy of the derived maps from multi-sensor active fire products. We focused on 42 large wildfires in Northern California from 2017 to 2018, where the USDA Forest Service National Infrared Operations (NIROPS) daily fire perimeters were available for comparison.The standard active fire products from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and the combined products were used as inputs. We found that the estimated surfaces generated by the natural neighbor method with the combined MODIS and VIIRS active fire input layers performed the best, with $R^2$ of 0.7 0.31 and RMSE of 1.25 1.21 ( $10^3$ acres) at a daily time scale; the accuracy was higher when assessed at a two day rolling window, e.g., $R^2$ of 0.83 0.20 and RMSE of 0.74 0.94. Relatively higher spatial accuracy was found using the 375m VIIRS active fire product as inputs when interpolated with the natural neighbor method. Furthermore, locational pixel-based comparison showed 61% matched to a single day, and an additional 25% explained within 1 day of the estimation, revealing greater confidence in fire progression estimation at a 2-day moving time interval. This study demonstrated the efficacy and potential improvements of daily fire progression mapping at local and regional scales.

The past two years became the most destructive wildfire years on record in the state of California, including the Mendocino Complex and wind-driven Camp fire in 2018. Strong "Santa Ana" winds fueled fast moving fires which burned into developed areas of Los Angeles in Southern California, while strong offshore "Diablo" winds drove a series of deadly fires Northern California wine country in 2017. These devastating wildfires killed hundreds of people, destroyed thousands of structures, led to evacuation of hundreds of thousands of people, and caused severe air quality problems in downwind urban centers far away from burned areas.