Monitoring 2019 Forest Fires in Southeastern Australia with GNSS Technique

Jinyun Guo,Xin Liu,Chengming Li,Rui Hou,Xin Jin,Maosheng Zhou,Hao Gao

doi:10.3390/rs13030386

Abstract

From late 2019 to early 2020, forest fires in southeastern Australia caused huge economic losses and huge environmental pollution. Monitoring forest fires has become increasingly important. A new method of fire detection using the difference between global navigation satellite system (GNSS)-derived precipitable water vapor and radiosonde-derived precipitable water vapor (ΔPWV) is proposed. To study the feasibility of the new method, the relationship is studied between particulate matter 10 (PM10) (2.5 to 10 microns particulate matter) and ΔPWV based on Global Positioning System (GPS) data, radiosonde data, and PM10 data from 1 June 2019 to 1 June 2020 in southeastern Australia. The results show that before the forest fire, ΔPWV and PM10 were smaller and less fluctuating. When the forest fire happened, ΔPWV and PM10 were increasing. Then after the forest fire, PM10 became small with relatively smooth fluctuations, but ΔPWV was larger and more fluctuating. Correlation between the 15-day moving standard deviation (STD) time series of ΔPWV and PM10 after the fire was significantly higher than that before the fire. This study shows that ΔPWV is effective in monitoring forest fires based on GNSS technique before and during forest fires in climates with more uniform precipitation, and using ΔPWV to detect forest fires based on GNSS needs to be further investigated in climates with more precipitation and severe climate change.

Highlights

Introduction6 million hectares [1]
The Gospers fire breaking out in Australia at the end of 2019 is thought to be the largest point-of-ignition fire in Australian history, with the total burned area approaching6 million hectares [1]
Solar radiation had the most influence on the spatial pattern of fire occurrence, and climate variables were the dominant factors for the density of fire occurrence [5]

Summary

Introduction

6 million hectares [1] This is almost seven times the size of the area burned in 2019 in the Amazon [2]. Fires cause significant economic losses and produce large amounts of smoke and soot during the burning process and lead to significant ecological losses [3], making it increasingly important to study how to detect forest fires. Forests are the protector of the earth, and forest fires generally happen in remote areas [4], often caused by human activities, such as smoking and barbecuing. Drones and remote sensing have been used to quickly monitor fires [7]. Electronic radar monitoring system, automatic monitoring system, and other monitoring systems have been developed to monitor forest fires [8]. Zhang et al [9] developed the machine-vision-based watchtower system to replace

Objectives

Methods

Conclusion