Forest Fires: Three Phases Where the Internet of Things (IoT) Can Be Useful

The consequences of forest fires go beyond what most people consider. When a forest or scrubland burns, it’s not just the vegetation that is lost and the animals that are endangered. The quality of the air, water resources, and the stability of sloping areas can also be compromised.

This is evident in the fires that periodically ravage countries such as the United States, Australia, or the Mediterranean region. In fact, their effects can be felt for months or even years after the fires. What can we do to reduce these consequences?

What is a forest fire?

Understanding what a forest fire is straightforward. However, we believe it’s important to provide a brief overview of what will be the focus of our article.

A forest fire is defined as an uncontrolled fire that affects a natural area. This area can be covered by trees, shrubs, or grassland, to name a few examples (1).

Three essential factors must come together for a fire to start:

  • Fuel
  • Oxygen from the air
  • A source of heat

The absence of any of these elements results in the extinction or non-initiation of a forest fire.

Causes of forest fires

In addition to the aforementioned requirements, the probability of a fire starting and spreading also depends on other factors such as vegetation properties, moisture levels, and weather conditions. However, it is the presence of a heat source, which triggers the risk.

In this regard, fires can have their origin in:

  • Natural causes, such as lightning strikes (accounting for around 4% of fires).
  • Anthropogenic causes, in which human activity plays a fundamental role (accounting for around 95%).

Of the latter, approximately 45-50% are considered deliberate or intentional fires.

Key statistics of forest fires in Spain

To provide some additional context, let’s take a look at the main statistics of forest fires in Spain.

For example, in 2019, according to data from the Ministry of Agriculture, Fisheries, and Food (2), there were over 7,000 fire incidents (fires affecting an area of <1 hectare) and over 3,500 wildfires (fires affecting an area of ≥1 hectare). These figures, although provisional, represent a 10.66% decrease compared to the average of the last decade.

How to reduce the consequences of forest fires with the Internet of Things (IoT)

Now that we have a better understanding of our protagonist, how can we harness wireless technology to become our ally and reduce the impact of forest fires?

To provide some structure to the presentation of different solutions, we will divide them into phases. We will distinguish an initial phase of an ignition event, an active fire stage, and a final phase of extinguished fire. It’s worth noting, however, that some of the devices mentioned can be used interchangeably throughout the different stages, either individually or as a complement to other equipment.

Prevention phase or ignition event

Environmental conditions play a significant role in determining the risk of a forest fire. In fact, one of the biggest concerns for firefighting teams is the so-called “30-30-30 rule.” This rule, which increases the likelihood of a fire, is characterized by:

  • Relative humidity ≤30%
  • Temperature of 30ºC or higher
  • Wind speed of 30 km/h or higher

However, despite these factors contributing to the “perfect storm,” their simultaneous occurrence has only been observed in 36.7% of major forest fires (over 500 hectares burned) recorded between 2007 and 2016.

Nevertheless, monitoring hyper-local climate variables is a crucial measure to consider. Soil moisture sensors, for example, can be an important device as dryness is a parameter that can indicate the risk of fire. Similarly, weather stations can help create weather models and forecasts. These equipment, for instance, are a key element in the wildfire mitigation plan of the utility company Southern California Edison.

In addition, prompt detection of a fire is crucial for rapid extinguishment. Therefore, the use of ground-based sensors or cameras that can alert to a possible fire is essential. Their operation can also be complemented with drones, for example.

Active fire phase

One of the aspects that is severely affected during a fire is the air quality. This problem not only impacts the inhabitants of nearby areas but also the firefighting personnel. In fact, the effects on the respiratory system can persist for up to a year, as demonstrated by a US research study.

Therefore, an increasing number of studies suggest a connection between the particulate matter (PM10 and PM2.5) generated during a fire and health issues. In this regard, two recent studies highlight this potential link:

  • An analysis correlating an increase in heart failure cases with exposure to fire smoke, published in the Journal of the American Heart Association.
  • A study establishing a connection between the pollution resulting from fires and the incidence of influenza months later.

This situation could pose a problem in the current context (April 2020) when a significant part of the planet is trying to curb the spread of the COVID-19 coronavirus. Preliminary studies suggest a potential link between suspended particulate matter and increased mortality, creating uncertainty for firefighting services, as reported by the Vancouver Sun in March.

Therefore, low-cost sensors for monitoring air quality could be an option to consider. This would provide information to the nearby population and firefighting teams. Additionally, the installation of a weather vane and an anemometer would allow for tracking the transport of particles through the wind, as well as the wind speed, which is one of the factors that significantly influence the spread of a fire.

Extinguished fire phase

The most visible effect after a fire is the elimination of aboveground vegetation. In most cases, seeds, bulbs, and roots are preserved, allowing for forest regeneration over time. However, the initial months are critical as the bare soil is exposed to meteorological variables.

This circumstance can lead to two significant problems:

  • The impact of ash and soil runoff on aquatic ecosystems and the quality of drinking water.
  • An increase in the risk of floods and landslides or mudslides.

For this phase, the most useful IoT devices could be those related to real-time monitoring of water quality. Important parameters to control, for example, would be water turbidity and dissolved oxygen levels. Regarding the risk of floods or landslides, the establishment of an early warning system could reduce the consequences of both phenomena.

Conclusion

The maxim that “fires are extinguished in winter” by conditioning and cleaning susceptible natural areas is common in the forestry field.

However, zero risk does not exist, as fire is “part of many natural ecosystems.” Therefore, one way to minimize its consequences is to monitor the factors that can trigger a fire, act promptly, and control the resulting consequences.

If technology can assist in this task, Arantec believes it is worth considering.

Sources consulted:

  • (1) SMA, S. L. (2010). Evita el fuego– la diversidad es vida: manual de orientación para docentes. Ministerio de Medio Ambiente, Medio Rural y Marino. Disponible en https://www.mapa.gob.es/es/desarrollo-rural/temas/politica-forestal/dossier_tecnico_tcm30-153331.pdf
  • (2) Subdirección General de Política Forestal (2020). Los incendios forestales en España: avance informativo 1 de enero-31 de diciembre de 2019. Ministerio de Agricultura, Pesca y Alimentación. Disponible en https://www.mapa.gob.es/es/desarrollo-rural/estadisticas/iiff_2019_ed02_con_portada_tcm30-537398.pdf
  • (3) Chaparro, D., Vall-llossera, M., Piles, M., Camps, A., & Rudiger, C. (2015). Low soil moisture and high temperatures as indicators for forest fire occurrence and extent across the Iberian Peninsula. 2015 IEEE International Geoscience And Remote Sensing Symposium (IGARSS). doi: 10.1109/igarss.2015.7326530
  • (4) Southern California Edison (2020). 2020‐2022 Wildfire Mitigation Plan. Disponible en https://www.sce.com/sites/default/files/AEM/SCE%202020-2022%20Wildfire%20Mitigation%20Plan.pdf
  • (5) Hristov, G., Raychev, J., Kinaneva, D., & Zahariev, P. (2018). Emerging Methods for Early Detection of Forest Fires Using Unmanned Aerial Vehicles and Lorawan Sensor Networks. 2018 28Th EAEEIE Annual Conference (EAEEIE). doi: 10.1109/eaeeie.2018.8534245
  • (6) Jones, C., Rappold, A., Vargo, J., Cascio, W., Kharrazi, M., McNally, B., & Hoshiko, S. (2020). Out‐of‐hospital cardiac arrests and wildfire‐related particulate matter during 2015–2017 California wildfires. Journal Of The American Heart Association, 9(8). doi: 10.1161/jaha.119.014125
  • (7) Landguth, E., Holden, Z., Graham, J., Stark, B., Mokhtari, E., & Kaleczyc, E. et al. (2020). The delayed effect of wildfire season particulate matter on subsequent influenza season in a mountain west region of the USA. Environment International, 139, 105668. doi: 10.1016/j.envint.2020.105668
  • (8) Exposure to air pollution and COVID-19 mortality in the United States. Xiao Wu, Rachel C. Nethery, Benjamin M. Sabath, Danielle Braun, Francesca Dominici. medRxiv 2020.04.05.20054502; doi: https://doi.org/10.1101/2020.04.05.20054502

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