Uncertainty analysis of forest above-ground biomass increments in southern Qilian Mountains
| Autor: | Feilong Ling, Min Yan, Hong Jiang, Xin Tian, Zongtao Han |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0106 biological sciences
Above ground Biomass (ecology) 010504 meteorology & atmospheric sciences Monte Carlo method Environmental science Soil science Sensitivity (control systems) 010603 evolutionary biology 01 natural sciences Uncertainty analysis 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | IGARSS |
| DOI: | 10.1109/igarss.2016.7730154 |
| Popis: | This study showed the potential for using Monte Carlo method for uncertainty analyses based on multi-parameter remote sensing data or incorporated models. The Monte Carlo method, involves using random numbers and probability to solve problems, is a simple but useful tool for uncertainty analyses with complex models. In this study, the uncertainties of the inter-annual and the overall forest AGB increments in the QMs form 2000 to 2012 were analyzed based on the Monte Carlo method. The sensitivity analysis showed that the modeled NPPs (SE npp ) contributed the most uncertainty to the inter-annual forest AGB dynamics. Furthermore, multi-source data and incorporated model fusion methods should be adopted to reduce model output uncertainties. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|