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Trees outside Forest in Asian Rice Production Landscapes






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    Book (stand-alone)
    Assessing and promoting trees outside forests (TOF) in Asian rice production landscapes
    The Asia regional rice initiative Biodiversity, landscapes & ecosystem services in Rice Production Systems
    2014
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    Mature planted or spontaneous tree systems scattered throughout or surrounding agricultural landscapes have been proven to be an excellent source of goods and services for increasing the socio-economic and environmental sustainability of agricultural landscapes. In spite of this, their role in supporting the livelihoods and the well-being of rice-based smallholder farmer communities and in environmental sustainability is mostly overlooked. Consequently, their potential contribution is still far from being fully exploited. The “Assessment of Trees outside forests in Asian rice production landscapes” pilot project was developed in 2013 in the framework (Biodiversity, landscape, and ecosystem services) of the FAO Regional Rice Initiative for Asia, with the final objective of providing policy and decision makers with evidence of the contribution that tree systems located in rice production landscapes can provide in terms of socio-economic and environmental sustainability, as well as in ter ms of resilience. This document reports on the outcomes of the project and could be used as a reference to feed higher-level national and regional dialogues, in order to promote an integrated and sustainable approach to the management of rice production landscapes.
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    Satellite 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
    2022
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    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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