Advancing Forest Degradation and Regeneration Assessment Through Light Detection and Ranging and Hyperspectral Imaging Integration

Author(s)

de Almeida, Catherine Torres ; Galvao, Lenio Soares ; Ometto, Jean Pierre H. B. ; Jacon, Aline Daniele ; Pereira, Francisca Rocha de Souza ; Sato, Luciane Yumie ; Silva-Junior, Celso Henrique Leite ; Brancalion, Pedro H. S. ; de Aragao, Luiz Eduardo Oliveira e Cruz

• Document type: Journal article
• Source: REMOTE SENSING; v. 16, n. 21, p. 26-pg., 2024-11-01.

Abstract

Integrating Light Detection And Ranging (LiDAR) and Hyperspectral Imaging (HSI) enhances the assessment of tropical forest degradation and regeneration, which is crucial for conservation and climate mitigation strategies. This study optimized procedures using combined airborne LiDAR, HSI data, and machine learning algorithms across 12 sites in the Brazilian Amazon, covering various environmental and anthropogenic conditions. Four forest classes (undisturbed, degraded, and two stages of second-growth) were identified using Landsat time series (1984-2017) and auxiliary data. Metrics from 600 samples were analyzed with three classifiers: Random Forest, Stochastic Gradient Boosting, and Support Vector Machine. The combination of LiDAR and HSI data improved classification accuracy by up to 12% compared with single data sources. The most decisive metrics were LiDAR-based upper canopy cover and HSI-based absorption bands in the near-infrared and shortwave infrared. LiDAR produced significantly fewer errors for discriminating second-growth from old-growth forests, while HSI had better performance to discriminate degraded from undisturbed forests. HSI-only models performed similarly to LiDAR-only models (mean F1 of about 75% for both data sources). The results highlight the potential of integrating LiDAR and HSI data to improve our understanding of forest dynamics in the context of nature-based solutions to mitigate climate change impacts. (AU)

• FAPESP's process: 20/06734-0 - Unravelling landscape drivers of forest recovery in a successional perspective
• Grantee: Catherine Torres de Almeida
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• FAPESP's process: 17/22269-2 - Transition to sustainability and agriculture-energy-water nexus: exploring an integrated approach with case studies in the Cerrado and Caatinga
• Grantee: Jean Pierre Henry Balbaud Ometto
• Support Opportunities: Research Program on Global Climate Change - Thematic Grants
• FAPESP's process: 18/15001-6 - ARBOLES: a trait-based understanding of LATAM forest biodiversity and resilience
• Grantee: Luiz Eduardo Oliveira e Cruz de Aragão
• Support Opportunities: Regular Research Grants
• FAPESP's process: 18/18416-2 - Understanding restored forests for benefiting people and nature - NewFor
• Grantee: Pedro Henrique Santin Brancalion
• Support Opportunities: BIOTA-FAPESP Program - Thematic Grants