Indicators of the forest management in areas under concession regime in the Amazon with the use of Laser Aerotransportado
technology
Name: QUETÍLA SOUZA BARROS
Publication date: 15/03/2021
Advisor:
Name |
Role |
|---|---|
| ADRIANO RIBEIRO DE MENDONÇA | Advisor * |
Examining board:
| Name |
Role |
|---|---|
| ADRIANO RIBEIRO DE MENDONÇA | Advisor * |
| GILSON FERNANDES DA SILVA | Internal Examiner * |
Summary: The aim of this work was to propose and evaluate the applicability of indicators of Reduced Impact Forest Management (IR), raised using Airborne Laser Technology (LiDAR) in areas under concession regime of exploitation in Amazon. Five Annual Production Units (APUs) were studied in the Forest Management Unit (FMU) III. These locations were flown over by LiDAR in 2014 and 2015 (UPA 5). Digital Models of Terrain (DTMs), surface (DSM), and Canopy Height (CHM) were made for each UPA. The proposed indicators were: dominant and codominant trees, gaps detection, impacts in the understory, profile vertical canopy (PVC), permanent preservation areas (PPA) and restrictive areas. Dominant and codominant trees were located by CHM
reclassification, with the remove of heights less than 30 m. Reduction in canopy area caused by selective logging was observed by subtracting the proportion of dominant and codominant trees before and after logging. Canopy gaps were delimited with a height threshold of five meters and a dimension of 10 m², and changes were observed before and after logging. The impacts design on the understory was based on the creation of the Relative Density Model (RDM), with a resolution of one meter. Buffer zones were made to quantify the impacts of logging by infrastructure and trees gaps.
PVC parameters γ and β for were obtained from the normalized point cloud, with a 50 m window, using Weibull 2 function parameters. PPAs were calculated in three approaches: in the field by the concessionaire, using LiDAR data: manual vectoring and iii) automatic segmentation. Buffers of 30 meters were made around the watercourses and 50 meters from the springs. Restrictive areas were considered to be sites with a slope equal to or greater than 15%. There was a reduction of 3.95% in the occurrence of the higher crown in the canopy after logging. The values of λ were higher in APU 1 (2.34), with a long history of logging. The highest percentages of the area with (3.44%) and Gini coefficient (0.42), were visualized at APU 5 in 2015, right after the logging. APUs 4 in 2014 and 5 in 2015 had higher levels of impacts on the understory (15.73 and 17.10%). The means of parameters γ and β of the understory and canopy, was not correlated to 5% with factors of selective exploration (time, logging intensity, impacts, sampled area, Gini coefficient and γ). The impacts vestiges of logging in PPAs (0.01 to 0.03%) and restrictive were low (0.05%). The selective logging did not cause major changes in the canopy; there was a visible reduction in impacts on the understory after two years of exploration; there was no exploration in PPAs and restricted areas. The indicators derived from LiDAR showed a high potential for monitoring areas managed in the Amazon.
Keywords: Reduced impact logging; Amazon rainforest; Remote sensing; LiDAR.
