Banca de QUALIFICAÇÃO: AFONSO HENRIQUE MORAES OLIVEIRA

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : AFONSO HENRIQUE MORAES OLIVEIRA
DATE: 15/07/2024
TIME: 15:00
LOCAL: UFOPA e remotamente
TITLE:

MONITORING OF FOREST MANAGEMENT IN THE AMAZON BY REMOTE SENSING: STRATEGIES, CHALLENGES AND INNOVATIVE SOLUTIONS

KEY WORDS:

Selective logging, change detection, monitoring system, forest management, forest degradation.

PAGES: 81
BIG AREA: Ciências Agrárias
AREA: Recursos Florestais e Engenharia Florestal
SUBÁREA: Manejo Florestal
SPECIALTY: Fotointerpretação Florestal
SUMMARY:

Deforestation by clear cutting promotes the complete removal of vegetation, with forest management being a selective timber extraction strategy in which changes under the forest canopy are minimized and often undetectable. Inappropriate and illegal exploitation of forests can lead to environmental degradation, habitat loss and increased greenhouse gas emissions. Among the strategies to assess whether these actions are being carried out in accordance with the Brazilian Forest Code and the socio-environmental regulations in force in the country, it is necessary to monitor the process. The process is challenging, as it involves identifying whether areas designated for preservation are being maintained and/or whether areas that allow conservation actions such as forest management have indicators of sustainable management of natural resources. Remote sensing has evolved in the inclusion of new sensors, as well as in terms of spatio-temporal scale, and can assist in monitoring in different sectors, such as areas with management plans. The objective was to evaluate the exploration process in a forest management unit to allow the preparation of the flowchart that feeds the remote sensing monitoring system, in federal concession areas. The work was structured into chapters, and firstly (chapter 1) a systematic literature review was carried out using databases to point out the advancement of knowledge about selective logging and forest degradation in the Amazon using remote sensing. Data available in two repositories (Scopus and Web of Science) were collected and organized in MS Excel spreadsheets and processed in R Studio (Bibliometrix Library). It was found that there was a significant increase in the number of publications over the last two decades, reflecting the growing interest and importance of the topic. Emerging themes highlight the use of advanced technologies such as high spatial and temporal resolution satellite imagery and machine learning for detecting and monitoring exploration areas. Next (chapter 2), the objective was to evaluate the dynamics of selective timber exploitation and the spatial and temporal variability of the intensity of exploitation present in the management plans in a federal concession area. Forest inventory data, topographic elevation and satellite images from the PlanetScope constellation were integrated into a geographic information system (GIS) environment to identify how the intensity of forest exploitation can vary throughout an annual production unit (UPA). The results indicate that within the same UPA there is a gradient of variation in exploitation intensity, with intensely explored areas and little explored areas. It was observed that around 75% of the cells were below 30 m³ ha-¹, which is the maximum volume allowed by law, however another 25% showed exploitation above 30 m³ ha-¹, with two cells experiencing an intensity of exploration between 90 and 105 m³ ha-¹. These results suggest that even though it is in an area subjected to reduced impact exploitation (EIA), high intensities of exploitation cause major disturbances in the forest canopy, which can eventually be interpreted as forest degradation by current monitoring systems. To support the development of a system to support monitoring in federal forest management plans in the Amazon, a flowchart was developed for monitoring in federal forest management plans in the Amazon (chapter 3). The integration of field data and remote sensing allowed the creation of an accessible platform for different stakeholders, including governments, NGOs and local communities, promoting transparency in forest management activities. The system provides real-time data and detailed analysis that has assisted forest managers and government authorities in making informed decisions about interventions needed to improve the sustainability and conservation of forest resources. The capacity for continuous and real-time monitoring allows for the early identification of illegal activities and forest degradation, enabling proactive actions to mitigate damage. The system helps ensure that forest management plans meet sustainability criteria, contributing to the preservation of biodiversity and the sustainable use of natural resources. The platform facilitates the involvement of local communities in monitoring and managing forest resources, strengthening participatory governance and environmental responsibility. These results highlight the effectiveness of the support system in improving forest management practices in the Amazon, demonstrating its potential as an essential tool for the conservation and sustainable management of tropical forests.

COMMITTEE MEMBERS:
Interna - ***.720.282-** - LUCIETA GUERREIRO MARTORANO - EMBRAPA
Interno - 1776327 - THIAGO ALMEIDA VIEIRA
Interno - 2143267 - JOSE MAX BARBOSA DE OLIVEIRA JUNIOR
Externo à Instituição - LUIZ EDUARDO OLIVEIRA E CRUZ DE ARAGAO
Externo à Instituição - CARLOS TADEU DOS SANTOS DIAS - UFC