[abpavel]

I see a number of issues:

1. no deforestation before July 9th.

2. In 10 days between Aug4 and Aug14 2% of the area was deforested, signifying all forrest will be gone in about 1.5 years. However forrest area in 2015 was almost the same size as reported total. Can't be right. Are you mixing ha and km2 by any chance?

3. No tracking between what is part of Forest Management Act, what are is part of designated production forest, and what is illegal deforestation.

4. No data on loss due to natural causes such as wind, fire, and no data on reforestation numbers.

[imnotanerd]

1. That's the date the bot started tracking. Actually, deforestation data starts in 2015 but I thought it'd be dishonest of the bot to count in deforestation that happened before the bot release. First drafts of the bot worked this way but that behavior was abandoned.

2. What do you mean by 2%? I guarantee I'm not mixing units, the remaining area shown is the remaining forestal area for the country in display, meaning that if the deforestation rhythm keeps that way, Suriname will be completely deforestated in 1.5 years.

3. The GLAD alerts dataset, which the bot takes as data source, don't make any distinction between forestal area of any type, they just track deforestation based on changes comparison in satellite imagery, Landsat 7 & 8 being the main imagery sources.

4. Then again, GLAD alerts does not provide any info on the causes of the deforestation.

I think globalforestswatch.org have an API based around industrial logging that let's you track industry-based deforestation only, but it's based on in-site reports and it's not as reliable as satellite-based GLAD alerts.

[abpavel]

Thanks for the reply. For point 2, the source states that from 2001 to 2019 1.3% of the tree cover was lost [0]. However in the twitter feed the loss is 2% per 10 days.

[0] https://gfw.global/3gm1aRN

[imnotanerd]

You are looking at the forest cover lost in Suriname only for that time period.

The bot gathers global forest cover loss for a given day and compares the aggregated of every country against the selected country from the list.

I thought I made it already pretty clear on the way the statuses are written, how would you write them to make it clear that its global area compared to that country rather as that country area only?

[dna_polymerase]

Point 4 might be irrelevant to the cause and more importantly part of a negative (hard to track) feedback loop. A patch of forest destroyed by human activity might be more susceptible to stronger winds or extreme weather in general.