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Healthy Forest, Healthy People II: Remote Sensing and Community Networks Extend the Benefits of Community Forestry in Thailand

机译:健康的森林,健康的人们II:遥感和社区网络扩展了泰国社区林业的优势

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Thailand has historically been an area of very high rates of forest destruction. Responses have included designating forests as protected areas and restricting access and usage by forest-dwelling communities. Smallholder farmers in these communities have often found themselves faced with critical issues of environmental degradation and deforestation and without the appropriate channels to resolve them. Over several decades, community forest management (CFM) has gained global momentum as a potential solution with both economic and environmental benefits, but results have been mixed. In 2012 we presented a case study at the IEEE Global Humanitarian Technology Conference (GHTC) documenting the progress of the CFM program in the northern Thailand village of Huai Lu Luang. This village partnered with several non-government organizations, including Upland Holistic Development Project and Plant With Purpose, to implement CFM using Global Positioning Systems (GPS) and Normalized Difference Vegetation Index (NDVI) remote sensing technologies for mapping and monitoring. At the 2012 GHTC we presented results showing significant improvements in both forest health and the community standard of living as a result of this combined approach. Now, six years later, not only has Huai Lu Luang village continued its efforts at CFM, but their success in community-based forest protection has expanded to the watershed level. Fifteen communities in the Huai Lu River watershed have created an effective CFM network to advocate for community forestry, and have expanded the use of remote sensing and mapping technologies to develop accurate village maps and relevant land management plans. This initiative has gained the active support of local and national government agencies. We provide evidence that the participating communities are experiencing greater economic stability and more sustainable farm systems. Using NDVI data, we observe a consistent increase in vegetative cover in the watershed relative to similar neighboring watersheds over a period of 7 years, indicating continuing improvements in forest health. These successes have made this watershed a model for others in northern Thailand and Burma who would use CFM and remote sensing technology to achieve environmental restoration and improve the standard of living for forest-dwelling communities.
机译:历史上泰国一直是森林破坏率很高的地区。应对措施包括将森林指定为保护区,并限制森林居住社区的使用和使用。这些社区的小农户常常发现自己面临着环境退化和森林砍伐的关键问题,而没有解决这些问题的适当渠道。几十年来,社区森林管理(CFM)作为一种具有经济和环境效益的潜在解决方案而获得了全球动力,但结果喜忧参半。 2012年,我们在IEEE全球人道主义技术会议(GHTC)上进行了案例研究,记录了泰国北部村庄Huai Lu Luang的CFM计划的进展。这个村庄与包括高地整体开发项目和有目的植物在内的数个非政府组织合作,使用全球定位系统(GPS)和归一化植被指数(NDVI)遥感技术进行制图和监测,以实施CFM。在2012年GHTC上,我们展示了结果,表明采用这种综合方法可以显着改善森林健康和社区生活水平。六年后的今天,不仅是槐Lu琅村继续开展森林经营活动,而且他们在基于社区的森林保护方面的成功已扩大到分水岭。淮河流域的15个社区建立了有效的CFM网络,以倡导社区林业,并扩大了遥感和制图技术的使用范围,以开发准确的乡村地图和相关土地管理计划。该倡议得到了地方和国家政府机构的积极支持。我们提供的证据表明,参与社区正在经历更大的经济稳定和更加可持续的农场体系。使用NDVI数据,我们观察到在7年的时间里,相对于类似的邻近流域,该流域的植被覆盖率持续增加,这表明森林健康状况不断改善。这些成功使该分水岭成为泰国北部和缅甸其他地区的典范,他们将使用CFM和遥感技术实现环境恢复并改善森林居住社区的生活水平。

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