Estimating heterogeneous wildfire effects using synthetic controls and satellite remote sensing
نویسندگان
چکیده
Wildfires have become one of the biggest natural hazards for environments worldwide. The effects wildfires are heterogeneous, meaning that magnitude their depends on many factors such as geographical region, climate and land cover/vegetation type. Yet, which areas more affected by these events remains unclear. Here we present a novel application Generalized Synthetic Control (GSC) method enables quantification prediction vegetation changes due to through time-series analysis in situ satellite remote sensing data. We apply this medium large (> 1000 acres) California throughout time-span two decades (1996–2016). method's ability estimating counterfactual characteristics burned regions is explored order quantify abrupt system changes. find GSC better at predicting than traditional approach using nearby assess wildfire impacts. evaluate comparing its predictions spectral indices observations during pre-wildfire periods improvements correlation coefficient from R 2 = 0.66 0.93 Normalized Difference Vegetation Index (NDVI), 0.48 0.81 Burn Ratio (NBR), 0.49 0.85 Moisture (NDMI). Results show greater NDVI, NBR, NDMI post-fire classified having lower Burning Index. average, cause 25% initial decrease index (NDVI) larger 80% drop wetness (NBR NDMI) after they occur. also reveals can last decade post-wildfire, some cases never return previous cycles within our study period. dynamical vary across an impact seasonal later years. Lastly, discuss usefulness analyses. • diverse depending factors. controls allow measurement effects. construction hypothetical scenarios provide insightful information. Different types recovery be detected classified.
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ژورنال
عنوان ژورنال: Remote Sensing of Environment
سال: 2021
ISSN: ['0034-4257', '1879-0704']
DOI: https://doi.org/10.1016/j.rse.2021.112649