Assessing Forest Cover and CO₂ Emissions in Portuguese-Speaking Countries and China: A Comparative Remote Sensing Approach
Main Article Content
Keywords
Forest dynamics, Time series, Carbon sequestration, Lusophony, Landsat collection
Abstract
This study provides an integrated comparative assessment of forest cover dynamics and CO₂ emissions across Portuguese-speaking countries and China from 2001 to 2024, using satellite-based datasets derived from Hansen’s Global Forest Change and Global Forest Watch. The analysis combines Landsat-derived forest metrics with CO₂ emission estimates to characterise temporal trends and spatial heterogeneity in forest change processes.
Results reveal pronounced geographical contrasts. Brazil and China together account for nearly 99% of total aboveground carbon stocks and more than 80% of CO₂ emissions associated with forest cover loss. In Brazil, emissions are primarily driven by continued deforestation and forest degradation in tropical biomes, whereas China’s extensive reforestation and afforestation programmes have partially offset earlier losses, contributing to net carbon gains in several regions.
In sub-Saharan Africa, Angola and Mozambique exhibit moderate but persistent forest decline, driven by agricultural expansion, charcoal production, and recurrent fire disturbances. By contrast, smaller island states such as São Tomé and Príncipe, Cape Verde, and Timor-Leste show negligible forest loss, reflecting relatively stable land-use patterns, albeit with limited forest extent. Portugal represents an intermediate case, where wildfire-related losses constitute the dominant driver of forest cover change.
Overall, these patterns demonstrate that large tropical and subtropical countries play a disproportionate role in regional and global forest–carbon balances. Strengthening land-use governance, promoting sustainable forest management, and expanding reforestation programmes are essential to maintaining carbon sequestration capacity and mitigating climate-related risks across Lusophone and Asian contexts.
The findings underscore the importance of harmonised monitoring systems and coordinated policy frameworks to achieve long-term forest sustainability and emission reduction targets.
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Isaú Alfredo B. Quissindo, Universidade José Eduardo dos Santos
Docente Assistente na Faculdade de Ciências Agrárias da José Eduardo dos Santos University (Angola) e doutorando no Department of Environmental Remote Sensing and Geoinformatics da University of Trier (Alemanha). A sua investigação centra-se em sistemas de informação geográfica e deteção remota aplicados à monitorização e gestão de recursos naturais, incluindo deep learning para imagens de satélite, mapeamento florestal, avaliação de incêndios e agricultura de precisão.