BIOMASS ANALYSIS METHOD IN A FOREST FRAGMENT OF PINUS UNCINATA

Santana, Sidney Henrique Campelo de; Sastres, Luis Fernando Sánchez; Navarro, Salvador Hernandéz; Silva, Elisabeth Regina Alves Cavalcanti; Laurentino, Maria Lucielle Silva; Galvíncio, Josiclêda Domiciano

Acessibilidade / Reportar erro

Brasil

Español English

sumário « anterior atual seguinte »

Sumário

Article • Mercator (Fortaleza) 20 • 2021 • https://doi.org/10.4215/rm2021.e20001 copy

BIOMASS ANALYSIS METHOD IN A FOREST FRAGMENT OF PINUS UNCINATA

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

The forests have a vital role in carbon capture from the atmosphere. Thus, this work has as its main objective to quantify and analyze biomass of a forest fragment of a Pinus uncinata that belongs to Alinyà Mountain Natural Space, through of Light Detection and Ranging (LIDAR) data tools. The natural area is located in the County of Figòls y Alinyà, in the Lleida province, located in Catalonia-Spain. In this sense, using the LIDAR data, the Digital Terrain Models were generated, and relevant statistical calculations were made to subsequently calculate the forest biomass. The linear regression models for biomass had a satisfactory correlation with the inventory data for 2 of the 5 areas considered. In this sense, it was possible to estimate these forest variables for the study area. The calculation of forest biomass by LIDAR data resulted in 9.138.6 tons to an area of 69.04 ha, while the inventory calculations resulted in 11.638.4 tons.

Keywords:
Forest Variables; Natural Resources; Remote Sensing; LiDAR

Zone	Forest Biomass	Max. Elevation
1a	6.87 tons	14.36 m
1b	5.22 tons	11.00 m
1c	4.89 tons	12.16 m
1d	6.31 tons	13.92 m
3c	9.04 tons	16.03 m

Forest Biomass Model	Equations
Correlations Residual standard error = 0.753 Multiple R-squared = 0.825 Adjusted R-squared = 0.693	$Forest biomass = - 8.420533 - (17.284783 * Elev . mean) + (0.090872 * FCC) + (3.321942 * Elev . Kurtosis) + (4.383122 * Elev . p 70) + (3.582299 * Elev . p 50) - (1.322206 * Elev . p 95) + (4.407623 * Elev . p 05) + (3.959646 * Elev . p 75) + (2.871198 * Elev . p 90) - (1.757112 * Elev . p 01) + (0.002919 * All returns above mean) + (6.719745 * Canopy relief ratio) (1)$
Carbon Content Model
Correlations Residual standard error = 0,389 Multiple R-squared = 0,817 Adjusted R-squared = 0,680	$Carbon content = - 4, 5731132 + (1, 8312510 * Elev . Kurtosis) - (9, 6776788 * Elev . mean) - (0, 5139935 * Elev . P 01) + (2, 1626610 * Elev . P 05) + (2, 2162177 * Elev . P 50) + (2, 7347885 * Elev . P 70) + (1, 7112347 * Elev . P 75) + (1, 7414060 * Elev * . P 90) - (0, 7976353 * Elev . P 95) + (0, 0450736 * FCC) + (0, 0015026 * All returns above mean) + (2, 9105467 * Canopy relief ratio) (2)$

Zone points	Forest Biomass Inventory	Forest Biomass Model	Basal Area Inventory	Basal Area Model	Carbon Stock Inventory	Carbon Stock Model
1a1	8,53	8,33	2,16	2,21	4,40	4,49
1a2	5,93	6,02	1,57	1,63	3,30	3,37
1a3	7,82	6,98	2,11	1,90	4,28	3,84
1a4	6,00	6,53	1,65	1,72	3,34	3,51
1a5	7,60	7,26	2,06	1,97	4,16	3,98
1a6	4,81	5,08	1,35	1,45	2,73	2,92
1a7	6,65	7,39	1,80	2,00	3,67	4,06
1a8	5,98	6,68	1,64	1,84	3,33	3,76
1a9	7,38	8,29	1,98	2,28	4,05	4,62
1a10	4,71	4,00	1,32	1,19	2,68	2,42
1a11	6,37	5,92	1,73	1,70	3,53	3,44
1a12	8,34	7,32	2,22	2,03	4,54	4,15
1a13	9,16	8,69	2,44	2,31	4,97	4,69
1d2	5,90	6,20	1,71	1,77	3,46	3,58
1d3	6,26	5,72	1,80	1,63	3,65	3,28
1d4	4,26	5,51	1,31	1,58	2,61	3,18
1d5	4,00	4,51	1,24	1,38	2,48	2,76
1d6	8,31	8,59	2,31	2,34	4,71	4,74
1d7	4,96	4,97	1,48	1,47	2,98	2,95
1d8	5,74	6,72	1,68	1,90	3,38	3,86
1d9	5,82	5,43	1,68	1,54	3,42	3,10
1d10	6,30	5,77	1,81	1,62	3,67	3,31
1d11	8,79	8,55	2,45	2,36	4,95	4,79
1d12	6,89	6,77	1,97	1,92	3,97	3,88
1d13	6,64	6,38	1,90	1,79	3,84	3,63
1d14	7,92	7,76	2,22	2,1 1	4,51	4,31
1d15	6,05	6,01	1,57	1,61	3,12	3,22
1d16	7,14	6,77	2,04	1,98	4,10	3,99
1d17	6,03	6,17	1,76	1,74	3,53	3,51

Universidade Federal do Ceará UFC - Campi do Pici, Bloco 911, 60440-900 Fortaleza, Ceará, Brasil, Tel.: (55 85) 3366 9855, Fax: (55 85) 3366 9864 - Fortaleza - CE - Brazil
E-mail: edantas@ufc.br

Acompanhe os números deste periódico no seu leitor de RSS

[1] (*)CORRESPONDING AUTHOR: Address: UFPE. Depart. de Ciências Geográficas, Cidade Universitária, CEP: 50670901, Recife (PE), Brasil. Phone:(81) 21267375. E-mail: sidneysantana.geo@gmail.com