Estimation of Timber Biomass
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| Name of Model | Functional form | Parameter estimates | R^2 | ||||
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| a | b | c | p | q | |||
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| Allometric | Y = a × Xb | 1.79 | 1.25 | – | – | – | 0.99 |
| Logistic | Y = a/1 + exp (p – b × X) | -261.01 | -0.01 | – | 5.54 | – | 0.99 |
| Chapman | Y = a × [1 – exp (-b × X)[1/(1 – c)] | 4510.04 | 0.0021 | 0.2249 | – | – | 0.99 |
| Gompertz | Y = a × exp (-b exp (-q × X) | 300.21 | 3.84 | 0.050 | – | – | 0.99 |
| Linear | Y = a + b × X | -11.923 | 4.717 | – | – | – | 0.99 |
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Where,
Y= Total biomass and X= Diameter at breast height (i.e. at the height of 1.37 m from the base of the tree)
Timber Volume Regression Equations for Multipurpose Tree Species
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| S.No. | Tree species | Regression Equations (V = a+bD) | Regression coefficient (r) |
| 1. | Arjun (Terminalia arjuna) | V = -4.96 + 0.16 DV = -0.029 – 10.61 D^2H | r = 0.96r = 0.99 |
| 2. | Mahogony (Swietenia mahagony) | V = -0.37 + 0.073 DV = -1.91 – 10.610 D^2H | r = 0.98r = 0.99 |
| 3. | White siris (Albizia procera) | V = -6.77 + 0.21 DV = 2.87 + 0.35 D^2H | r = 0.96r = 0.66 |
| 4. | Safeda (Eucalyptus tereticornis) | V = -2.64 + 0.138 DV = -0.32 + 0.66 D^2H | r = 0.97r = 0.98 |
| 5. | Shisham (Dalbergia sissoo) | V = -1.17 + 0.068 DV = -2.79 + 0.610 D^2H | r = 0.97r = 0.99 |
| 6. | Karanj (Pongamea pinnata) | V = -1.54 + 0.080 DV = -0.207 + 0.610 D^2H | r = 0.95r = 0.99 |
| 7. | Chah (Acacia lenticularis) | V = -1.808 + 0.104 DV = 0.0011 + 0.610 D^2H | r = 0.98r = 0.99 |
| 8. | Teak (Tectona grandis) | V = -1.31 + 0.074 DV = 0.010 + 0.600 D^2H | r = 0.90r = 0.99 |
| 9. | Chakundi (Cassia siamea) | V = -2.21 + 0.101 DV = -0.0055 + 0.61 D^2H | r = 0.92r = 0.99 |
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Where,
V = Timber volume, D = Diameter at breast height (i.e. at the height of 1.37 m from the base of the tree) and H = Height of the tree
