[FRIAM] Anticipate wildfires using machine learning

[cody dooderson]

I might be entering into this conversation out of context. I have seen
a lot of forest fire conversations on FRIAM but have been too lazy to read
them. Also I am not an ecologist.
I disagree that wildfires are *always* the last step before
desertification. Forests go through cycles, often called ecological
successions, and often successions include fire. A lot of experts agree
that frequent low intensity wildfires promote biodiversity. The western
United States has been effectively putting out wildfires for about the last
century, which led to dense monocultures that are prime for large
destructive fires. It is believed that before our intervention the forests
were thinner and burned more often. Historic fires were lower intensity and
burned in more of a mosaic pattern. That mosaic pattern of burned
landscapes is a significant contributor to biodiversity. A mature forest
harbors different kinds of organisms than does a freshly burned one or one
in an intermediate stage of growth. When there is a mosaic pattern of say
grassland and mature forest, the forest is usually much more diverse. When
a forest is more diverse it is healthier, usually.

Cody Smith


On Sun, Jun 13, 2021 at 7:30 AM Jochen Fromm <jofr at cas-group.net> wrote:

> Wildfires are the last step before desertification. We need to prevent it
> confine them. Is it possible to increase the accuracy of wildfire
> predictions using machine learning?
>
> https://towardsdatascience.com/anticipating-wildfires-with-machine-learning-tools-5eb43b450d36
>
> -J.
>
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