International Scholarly Research Notices

Research Article

Modeling Develops to Estimate Leaf Area and Leaf Biomass of Lagerstroemia speciosa in West Vanugach Reserve Forest of Bangladesh

Table 3

Different models tested for the estimation of leaf area (, m²) and leaf biomass (, kg) with diameter at breast height (DBH, cm) and tree height (, m) of L. speciosa species.


Model	Estimated coefficients				RMSE		Adjusted	FI	AICc	BIC	CF	Durbin Watson
Model					RMSE		Adjusted	FI	AICc	BIC	CF	Durbin Watson

M₁	2.36383 ± 2.76814	5.33557 ± 0.08891		3602	18.59	0.9452	0.9449	0.64	1836.22	1846.22	—	1.807
M₂	−132.85 ± 13.52	22.74 ± 1.06		460	44.36	0.6877	0.6862	3.21	2203.20	2213.21	—	0.753
M₃	32.165522 ± 1.982558	0.313651 ± 0.004419		5037	15.84	0.9602	0.9600	0.59	1768.75	1778.75	—	1.411
M₄	−44.6109 ± 5.1513	4.4608 ± 0.1128	5.7255 ± 0.5637	2733	15.24	0.9633	0.9630	0.52	1753.26	1766.59	—	1.736
M₅	−11.235989 ± 5.19719	6.465311 ± 0.378365	−0.018144 ± 0.005913	1878	18.23	0.9475	0.9470	0.74	1828.91	1842.23	—	1.767
M₆	−9.5289 ± 34.0715	0.2453 ± 5.8305	0.9602 ± 0.2450	253	42.91	0.7092	0.7064	2.95	2190.20	2203.53	—	0.813
M₇	1.57067 ± 0.05028	1.03390 ± 0.01563		4378	0.1301	0.9544	0.9542	0.53	−257.78	−247.77	1.0084	2.014
M₈	0.03719 ± 0.18967	1.93313 ± 0.07582		650	0.3006	0.7567	0.7555	2.62	95.66	105.67	1.0462	0.854
M₉	0.681579 ± 0.052864	0.736374 ± 0.009257		6328	0.1090	0.9680	0.9679	0.43	−332.53	−322.52	1.0059	1.520
M₁₀	0.93516 ± 0.06836	0.83960 ± 0.02101	0.50296 ± 0.04413	3604	0.1023	0.9720	0.9717	0.36	−358.13	−344.80	1.0052	2.003
M₁₁	1.57067 ± 0.05028	1.03390 ± 0.01563	−0.002271 ± 0.0062	4378	0.1301	0.9544	0.9542	0.68	−257.75	−247.77	1.0084	2.014
M₁₂	0.03719 ± 0.18967	1.93313 ± 0.07582	0.00373 ± 0.05283	650	0.3006	0.7567	0.7555	2.41	95.70	105.67	1.0462	0.854
M₁₃	0.389894 ± 0.240441	0.495224 ± 0.007723		4112	1.615	0.9516	0.9514	0.64	805.08	815.08	—	1.933
M₁₄	−11.0649 ± 1.3503	2.0227 ± 0.1059		364	4.431	0.6358	0.6341	3.33	1231.05	1241.06	—	0.875
M₁₅	3.3471251 ± 0.237553	0.0286013 ± 0.00052		2917	1.899	0.9332	0.9328	0.86	873.37	883.37	—	1.227
M₁₆	−2.23654 ± 0.50829	0.44631 ± 0.01113	0.32012 ± 0.05562	2389	1.503	0.9583	0.9579	0.59	775.93	789.26	—	1.914
M₁₇	−0.411165 ± 0.456914	0.5617675 ± 0.03326	−0.0010687 ± 0.00051	2090	1.603	0.9526	0.9521	0.62	802.87	816.19	—	1.934
M₁₈	−4.26959 ± 3.48979	0.78302 ± 0.59719	0.05291 ± 0.02509	187	4.395	0.6435	0.6400	3.51	1228.62	1241.95	—	0.903
M₁₉	−0.73397 ± 0.05330	1.01654 ± 0.01656		3766	0.1379	0.9474	0.9472	0.54	−233.16	−223.15	1.0095	1.626
M₂₀	−2.22910 ± 0.19082	1.89560 ± 0.07628		617	0.3025	0.7472	0.7459	2.69	98.21	108.21	1.0468	1.062
M₂₁	−1.6049 ± 0.0588	0.7234 ± 0.0103		4938	0.1212	0.9594	0.9592	0.56	−287.66	−277.65	1.0073	1.708
M₂₂	−1.34008 ± 0.07665	0.83123 ± 0.02357	0.47969 ± 0.04948	2768	0.1147	0.9638	0.9634	0.47	−309.79	−296.46	1.0066	1.971
M₂₃	−0.73397 ± 0.05330	1.01654 ± 0.01656	−0.00421 ± 0.00284	3766	0.1379	0.9474	0.9472	0.52	−233.13	−223.15	1.0095	1.626
M₂₄	−2.22910 ± 0.19082	1.89560 ± 0.07628	0.04858 ± 0.03842	617	0.3025	0.7472	0.7459	2.24	98.24	108.21	1.0468	1.062

RMSE: root mean squared error, FI: Furnival’s index, AICc: corrected akaike information criterion, BIC: Bayesian information criterion, and CF: correction factor.