Two questions about the tutorial

[sbanchero]

Hi!
I've two questions about the tutorial and the AGBD calculation.

1. The document [1] and [2] specify that par[1] is always the intercept term but in the tutorial 3_gedi_l4a_exploring_data.ipynb say: The variable par gives model coefficients - the first element of the list is always the slope of the linear model. Which is the correct one?

2. Also, I have another question regarding the use of the existing model in ANCILLARY / model_data. For example, in the DBT_NAm case if the vertors are:
   predictor_id: [1 2 0 0 0 0 0 0]
   rh_index: [50 98 0 0 0 0 0 0]
   par: [-120.77709198 5.50771856 6.80801821 0. 0. ]

How use the information to make the model equation? The vectors index starts from 0 or 1?

Follow both [1] or [2] is some confusing the order of the parameters because I don't understand how I should combine the rh values as only have two values 1 and 2 within the prediction_id for rh50 and rh98 respectively but tree par coefficients.

I understand that a possible way can be:
AGBD = -120.77709198 + 5.50771856 * rh50 + 6.80801821 * rh98^2

Is this correct?

I hope my explanation has been understood.

Thank you very much for the tutorials.
Best regards
Santiago

[1] https://daac.ornl.gov/daacdata/gedi/GEDI_L4A_AGB_Density/comp/GEDI_L4A_Common_Queries.pdf
[2] https://daac.ornl.gov/GEDI/guides/GEDI_L4A_AGB_Density.html

[rupesh2]

HI @sbanchero , 1) par[1] should be the "intercept"; it is now updated in the tutorial description. 2) The equation for DBT_NAm should be AGBD = -120.77709197998047 + 5.507718563079834 x RH_50 + 6.808018207550049 x RH_98. predictor_id provides here mapping between rh_index and par. Also, note that both predictor and response variables, in this case, are transformed (sqrt).

[sbanchero]

Hi @rupesh2 ,
Thank you very much for your answer