Forest Fire Patterns and Lightning-Caused Forest Fire Detection in Heilongjiang Province of China Using Satellite Data

Abstract

Large forest fires can cause significant damage to forest ecosystems and threaten human life and property. Heilongjiang Province is a major forested area in China with the highest number and concentration of lightning-caused forest fires in the country. This study examined the spatial and temporal distribution patterns of forest fires in Heilongjiang Province, as well as the ability of satellite remote sensing to detect these fires using VIIRS 375 m fire point data, ground history forest fire point data, and land cover dataset. The study also investigated the occurrence patterns of lightning-caused forest fires and the factors affecting satellite identification of these fires through case studies. Results show that April has the highest annual number of forest fires, with 77.6% of forest fires being caused by lightning. However, less than 30% of forest fires can be effectively detected by satellites, and lightning-caused forest fires account for less than 15% of all fires. There is a significant negative correlation between the two. Lightning-caused forest fires are concentrated in the Daxing’an Mountains between May and July, and are difficult to monitor by satellites due to cloud cover and lack of satellite transit. Overall, the trend observed in the number of forest fire pixels that are monitored by satellite remote sensing systems is generally indicative of the trends in the actual number of forest fires. However, lightning-caused forest fires are the primary cause of forest fires in Heilongjiang Province, and satellite remote sensing is relatively weak in monitoring these fires due to weather conditions and the timing of satellite transit.

Enhancing Fire Monitoring Method over Peatlands and Non-Peatlands in Indonesia Using Visible Infrared Imaging Radiometer Suite Data

“…This study, for comparison purposes, used field data, as was the case in the present study. In the above-mentioned study, VIIRS-375 data could detect no more than 30% POD [68]. This also shows that the global algorithm has a better ability to detect forest and land fires in Indonesia.…”

Lightning-Induced Wildfires: An Overview

“…Also, past reports indicate that lightning strikes are the main cause of grassland fires in Inner Mongolia [12]. From 2012 to 2020, lightning caused nearly 77.6% of the wildfires in the Heilongjiang Province of China, mostly occurring in April [13]. In Muli County in Sichuan Province, lightning strikes contributed to nearly 47% of wildland fire accidents from 2005 to 2008 [14,15].…”

Real-time forest fire detection, monitoring, and alert system using Arduino

“…Contemporary forest fire monitoring systems primarily involve satellite imagery, although such monitoring is not done in real-time and requires manual analysis by authorities. This approach has several inherent disadvantages, notably its inability to rapidly detect forest fires and assess the fire risk in these vulnerable regions [7], [8]. Satellite-based monitoring is further compromised by adverse weather conditions, rendering it relatively inaccurate and unreliable due to its dependence on weather patterns.…”