Hi @wenjing -
Please start a new thread with your questions, and include the entire log file (.txt file) that the model creates in your Workspace. Thanks!
~ Stacie
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@wenjing , would you please attach your logfile from this run so we can take a closer look?
Thanks,
James
@wenjing As @swolny mentioned, it would be very helpful if you could create a new discussion topic with this question (and be sure to include your logfile!). Thanks in advance!
Hello everyone,
I have just started to understand the Carbon sequestration model in InVEST. My question is how to calculate the carbon pool for the input into the model. I have reviewed this thread and found the link to resources, including the User Guide source from Reusch and Gibbs. But it is not accessible. It says “ESS-DIVE Service is unavailable. Please contact us if you have further questions.”
Is there any other means/way to calculate the carbon pool for the LULC classes?
Hi @Tharun -
Looks like we need to update our User Guide. A quick web search finds the Reusch and Gibbs data here.
There are a lot of other, and more recent, global carbon biomass maps and products out there that you could use, either as alternatives to the InVEST carbon model, or to help determine your carbon pools. Generally, we recommend doing a literature search to see if anyone has quantified biomass data for your study area or country, or similar ecosystem types. Sometimes countries will have this information in their REDD documents, if they exist. Or researchers may have done such a study.
~ Stacie
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Hi all
As @swolny mentioned, there are a lot of online datasets / maps available including aboveground / belowground biomass carbon density (linked below) and soil organic carbon content (linked below). So, I think I could use GIS to get an average carbon density for each land use type for the analysis (using clip and dissolve).
What I’m having trouble with is this: the values I see on these global dataset maps are often very different from what I’ve seen in the NBI studies I’m using as references. Two give two examples, referring to the NBI Burkina Faso study: 1) the NBI Burkina Faso technical annex on the NBI website study gives an above ground carbon value of 0 t/ha for urban/built up sources – but when I check the online maps, the value for the same location is 200 t/ha (see map here). 2) Soil carbon values are also very different - I see 16 tonnes/ha looking at the GLOSIS dataset (map here), where the NBI Burkina Faso study says the number should be closer to 60 t/ha.
So, my question is - are the global datasets including something that’s not factored into the NBI carbon pool studies, are the NBI study values somehow incorrect (maybe the table was copied/pasted incorrectly?) or is there something else that I’m missing? Some variation in the numbers is to be expected, but these differences seem so large that there must be something else going on.
Thanks,
Hi @gbf22 -
I have encountered similar findings when trying to compare carbon values from different sources, which most likely use different methods, and provide the data in different formats. Good sources provide their methodology, so you can review it and see if it seems appropriate for your purposes. But still, how to compare, say, remote-sensing data-derived maps with something like field studies?
One recommendation is to use several different sources to illustrate the uncertainty involved with these datasets, for example choosing one with the highest values and one with the lowest, and/or two (or more) from different types of data source (digitally derived versus field studies, or whatever alternative is available that you want to consider). Create results that show and discuss the range of possible values.
Also, i don’t know the methods behind the sources you’re referencing, but if you’re using carbon data that’s already spatial, you could consider not using the Carbon model, but use the sources directly and just add up the different carbon pool layers. That way you won’t lose the spatial differentiation between, say, sparser forest and denser forest, or different types of developed areas that the spatial maps likely provide.
~ Stacie
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