MCredd: Monte Carlo uncertainty for Forest and REDD+ related estimations

MonteCarlo simulations for estimating the uncertainty of REDD+ greenhouse gas emissions and removals from forest changes.

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Workflow:

1. Input Monte Carlo model input variables and their characteristics (or raw data and aggregation factors, see v2.0 roadmap)
2. Chose number of repetitions
3. Choose or add custom formulas between input variables.
4. Run Simulations

The app simulate the desired number of repetitions and calculate uncertainty of calculated variables.

Template

input_category / input_name / input_error_type / input_distribution / fixed_value / normal_mu / normal_sigma / others

Input options

Option 1: Input a list of variables and their distribution characteristics:

Ex.

var 1 / normal / mu / sigma / var 2 / normal / mu / sigma / var 3 / fixed / mu / 0 /

Option 2: Input raw data and distribution automatically assigned (for v2.0, distrubution might be better using biological characteristics than stats)

Option 3: Raw data, include tree AGB allometric equations uncertainty

Road map

TBD