This book offers in-depth coverage of the process of climate change management in African forests, from assessment of woody species diversity to climate change mitigation, including carbon sequestration capacity and carbon taxation. Going beyond merely demonstrating the importance of vegetation in carbon sequestration, the volume also helps in quantifying the contribution of various species in the process.
Focused on tropical vegetation in Africa, specifically the Congo Basin, novel approaches to carbon sequestration capacity and above-ground biomass assessment are presented. The latest methods are highlighted, including remote-sensing technologies, digital image processing and development of classification methodologies for various plants and the assessment of their use in carbon sequestration. The financial implications of different schemes are also discussed.
Extensive case studies offer details on afforestation/reforestation; exploitation and conservation of forests in the context of REDD+; carbon taxation and capacity building; assessing carbon sequestered in mangrove forests; evaluation of marginal forests; and assessment methods based on allometric equations and a generalized coefficient. This book brings together the latest information to meet the needs of researchers and policymakers working at the cutting edge of carbon sequestration and climate change.
1. Carbon sequestration: an assessment method based on allometric
equations and a generalized coefficient Idriss Landry Kouedjou, Robert
Christian Anaba Banimb, Narcisse Talla Tankam, Pierre Marie Mapongmetsem and
Michel Tchotsoua
DOI: 10.53061/HWRT3383
2. A novel technique for carbon sequestration assessment applied to marginal
forests Narcisse Talla Tankam, Janvier Fotsing, Idriss Landry Kouedjou,
Maurice Ndikwé Dourwé, Albert Dipanda and Michel Tchotsoua
DOI: 10.53061/NWVN5171
3. Plant diversity and carbon stocks of estuaries: hotspots in the Atlantic
forests of Cameroon Hubert Mounmemi Kpoumié, Mesmin Tchindjang, Rose Ngo
Makak, Carole Mireille Tchoupou Votio, Tatiana Kengne Nebouet, Cédric Chimi
Djomo and Louis Zapfack
DOI: 10.53061/VRYQ5361
4. Assessment of carbon sequestrated by mangroves based on SAR images: the
littoral coast of Cameroon Janvier Fotsing, Narcisse Talla Tankam, Aminou
Halidou, Alain Tiedeu, Marcel Ngirinshuti and Emmanuel Tonye
DOI: 10.53061/FSWH8220
5. Carbon taxation and motivation of forest owners: alternatives for building
forest capacity against climate change in Rwanda Marcel Ngirinshuti and
Janvier Fotsing
DOI: 10.53061/EOSY2983
6. Method for estimating forest heritage in a region: exploitation and
conservation of Belabos forest in eastern Cameroon in the context of REDD+
Bidjogo Fadimatou Laye and Sylvain Aoudou Doua
DOI: 10.53061/YNPU7390
7. Mitigating the effects of climate change in sub-Saharan Africa:
afforestation/reforestation of sites in northern Cameroon Valery Noiha Noumi,
Victor Awé Djongmo, Louis Zapfack and Pierre Marie Mapongmetsem
DOI: 10.53061/NVSV3422
Narcisse Talla Tankam is a senior lecturer in the Computer Engineering Department of the University Institute of Technology Fotso Victor at the University of Dschang, Cameroon. He has a PhD in Computer Science from the University of Yaounde I in Cameroon and a University Doctorate in Instrumentation and Image Computer Engineering from the University of Burgundy in France. His research activities involve remote sensing including global warming, risks and disaster management, digital image processing, and education technologies including eLearning and AI in education.
Janvier Fotsing is a senior lecturer in the Department of Physics at the Faculty of Science, University of Buea, Cameroon. He has a PhD in electronics with remote sensing speciality from the University of Yaoundé I in Cameroon, and a doctorate in science of education from the University of Cergy-Pontoise in France. His research activities include remote sensing, digital image processing, telecommunication and chaotic systems, data transmission security, education technologies including IoHT, hybrid training, e-Learning and AI in education.
