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ArticleSuccessful 20 years of community forest management in Guatemala informs an Integrated Community Forest Management pathway to support scaling
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Research increasingly highlights the powerful link between environmental and social challenges and outcomes, and how local communities can be effective guardians of the forest. In the Maya Biosphere Reserve in Guatemala, which Rainforest Alliance supports since more than 20 years, a broad alliance has been made between forest communities, local and national government bodies, companies, as well as academia and implementing partners. This public-private alliance supports the local population in its responsible management of forests, as a powerful tool contributing to peace and social justice, as well as to human development. Impact studies show that the deforestation rate in the forest concessions is near zero, while protected areas and buffer zones nearby suffered high deforestation levels, and that the initiative contributes to all the 17 SDGs. Based on a learning inventory of the Rainforest Alliances’ work in Guatemala and other countries it operates in, we have broaden our approach in order to catalyze long-term transformation at scale. We have developed and tested tools and methods to foster an enabling environment and to support the deployment of viable community-based forest enterprises, implementing sustainable forest management, restoration or reforestation, and providing equitable benefits. We have organized this approach in an Integrated Community Forest Implementation pathway which is presented in more detail in this paper. To deploy this pathway, a unique coalition of corporate stakeholders, forest communities, Indigenous Peoples and regional implementing partners are uniting with the Rainforest Alliance within its Forest Allies Community of Practice. Using the Integrated Community Forest Management approach, we leverage the power of partnerships to protect and restore forests in critical landscapes while also empowering communities and improving livelihoods. Because we believe the best guardians of the forest are those who make their living from it. Keywords: Adaptive and integrated management, Community Forest; Sustainable forest management, Economic Development, Partnerships. ID: 3485602 -
ArticleThe use of Normalized Difference Vegetation Index (NDVI) to assess urban forests dynamics in West Africa: A case study of Mbao Classified Forest, Dakar (Senegal)
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Mbao Classified Forest is the largest urban forest in Dakar. It covers an area of 720 hectares and is the most important green lung of the city. This forest plays a key role in terms of carbon storage and sequestration, air pollution removal, and more generally in ecosystem services provision. Hence it is urgent to monitor the dynamic of this forest over the past twenty years (1998-2018) because a lot of infrastructures including a water pumping station and a highway were established inside during this period. These installations make it subject to encroachments and the risk of depletion that could compromise its existence. The aim of this this paper is to assess urban forest dynamics using artificial intelligence and vegetation indices. To achieve this goal the first step is to perform a forest inventory. We opted for a sampling rate of 0.5%. The area of a plot in the i-Tree Eco inventory is 391 m2 with a radius of 11.16 m, which resulted in a total number of 90 plots. The variables measured for each tree are D.B.H, total height, crown width. The allometric equations were used to compute the above-ground biomass. The NDVI of every plot was computed from Landsat datasets followed by the development of a linear regression model with NDVI as the independent variable and biomass as the dependent variable. Landsat imagery enables the NDVI computation of each plot during the twenty past years and using the regression model, the biomass was determined over this period. Our results provide a sound basis to advocate the safeguarding of Mbao Classified Forest. Keywords: Urban forest, biomass, NDVI, inventory. ID: 3621874 -
ArticleSatellite remote sensing-based forest resources assessment methods for effective management and sustainable development of forests by generation of information on forests and trees outside forest cover
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Satellite based remote sensing methods have proved to be an effective and scientifically proven method for managing and conserving forest data and resources at periodic time intervals. The forest resources monitoring methods provide useful data to forest managers for sustainable forest management at different scale and forest management units. Over the years the scientific management of forest have been a subject globally discussed incorporating the role of environmentalist, conservationist and communities associated with the forest. It has been an unhidden fact that forests have suffered tremendous pressure in developing countries on the pretext of development. It is through effective monitoring and communication of forest information and knowledge that the concerned provincial governments are forced to take remedial measures for protecting the forests. Apart from the government owned forests, termed as Recorded Forest Areas(RFA) in India, Trees outside forests(TOF) are well acknowledged as an important component of forest resources. The ToF, which basically exist as block, linear and scattered plantations on earth are captured using LISS-III sensor of Indian Remote Sensing Satellite. For the national level scale mapping, all patches of area 1hectare and above are considered for estimation. For mapping of ToF patches of size between 0.1-1hectare, high resolution data from LISSIV sensor(5.8metres resolution) is analyzed. It has been now a well-established fact that trees outside RFAs, although in small proportion, contribute significantly to forest conservation and meeting the demand of people towards minor forest produce, firewood etc. The exercise on forest change detection using a hybrid method, is effective in identification of significant forest change. The assessment of forests and ToFs using satellite data and advance image processing tools may be helpful in effective management and long term sustainability of forests in developing countries. Keywords: [Recorded Forest Area, Trees Outside Forest, National Forest Inventory, FSI, Neural Network, Machine Learning] ID: 3622277
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