Things to Do in L.A. Tap to enable a layout that focuses on the article. 'No smoking gun': Why Eaton fire report didn't name names or assign blame A resident tries to defend his home from nearby flames during the Eaton fire in Altadena. This is read by an automated voice. Please report any issues or inconsistencies here . A $2-million county report examined botched Eaton fire evacuation alerts but stopped short of naming officials or assigning individual blame.

Things to Do in L.A. Tap to enable a layout that focuses on the article. L.A. County outlines multiple breakdowns that prevented timely evacuations during deadly Eaton fire This is read by an automated voice. Please report any issues or inconsistencies here . The long-awaited report investigating how county officials failed to order timely evacuations for west Altadena as the Eaton fire threatened the community did not assign blame for the botched alerts, instead chalking the issue up to a night of chaos, unprecedented conditions and poor communication. The 132-page report released Thursday seemed to downplay how early the fire threatened west Altadena -- despite 911 calls that reported flames and smoke in the area -- and only once mentioned the 19 people who died in the fire, of which all but one were found in the town's western side.

Multiple unauthorized drones flew above the Palisades fire Friday afternoon, forcing firefighting aircraft to leave the area for safety and angering those working on the front lines, authorities said. These sightings came just a day after a drone collided with a Super Scooper fixed-wing aircraft, grounding the plane for several days of repairs and reducing the number of aircraft available to fight the fire. "This is not just harmless fun. This is incredibly dangerous," said Chris Thomas, public information officer for the Palisades fire. "Seriously, what if that plane had gone down? It could have taken out a row of homes. It could have taken out a school."

Tens of thousands of Californians are turning to a crowdsourced, nonprofit app called Watch Duty for critical, up-to-the-moment disaster updates as deadly fires continue to rage through the state. The app, which uses a mixture of official government and volunteer data to track wildfires, surpassed OpenAI's ChatGPT and Meta's Threads as the most downloaded app on the Apple App Store on Wednesday. Social media users have encouraged residents in affected areas to download the app in order to track the fire's rapid movements and stay aware of possible evacuation orders. Apps like Watch Duty, which have seen a surge in interest in recent years, may become even more important as climate change-related natural disasters intensify in scope and scale. It gives you updates on fires nearby, evacuation notices, and even will show you where an evacuation center is if you need to evacuate!

Traffic prediction during hurricane evacuation is essential for optimizing the use of transportation infrastructures. It can reduce evacuation time by providing information on future congestion in advance. However, evacuation traffic prediction can be challenging as evacuation traffic patterns is significantly different than regular period traffic. A data-driven traffic prediction model is developed in this study by utilizing traffic detector and Facebook movement data during Hurricane Ian, a rapidly intensifying hurricane. We select 766 traffic detectors from Florida's 4 major interstates to collect traffic features. Additionally, we use Facebook movement data collected during Hurricane Ian's evacuation period. The deep-learning model is first trained on regular period (May-August 2022) data to understand regular traffic patterns and then Hurricane Ian's evacuation period data is used as test data. The model achieves 95% accuracy (RMSE = 356) during regular period, but it underperforms with 55% accuracy (RMSE = 1084) during the evacuation period. Then, a transfer learning approach is adopted where a pretrained model is used with additional evacuation related features to predict evacuation period traffic. After transfer learning, the model achieves 89% accuracy (RMSE = 514). Adding Facebook movement data further reduces model's RMSE value to 393 and increases accuracy to 93%. The proposed model is capable to forecast traffic up to 6-hours in advance. Evacuation traffic management officials can use the developed traffic prediction model to anticipate future traffic congestion in advance and take proactive measures to reduce delays during evacuation.

A 6.9 magnitude earthquake struck Hawaii's big island as the volcano forces thousands to evacuate. A 6.9-magnitude earthquake rattled the Big Island of Hawaii on Friday, according to the U.S. Geological Survey, following a recent volcanic eruption. The quake hit roughly 10 miles southwest of Leilani Estates, the USGS reported. It was centered near the south flank of Kilauea volcano, which erupted Thursday and continued to spew lava into Friday. This is in almost exactly the same location at the deadly 1975 M 7.1 earthquake.

The Japanese government Friday eased evacuation orders for towns not seriously contaminated by the 2011 Fukushima Daiichi nuclear power plant disaster. The government lifted evacuation orders for parts of Kawamata, Namie and Iitate, Kyodo News reported. The order also frees a large part of Tomioka on Saturday. The action reduces the evacuation zones by two-thirds but it was unclear whether residents actually would return to their homes because of radiation fears and a lack of amenities like schools. The most seriously contaminated areas remain off-limits.