Algorithmic development and verification of a remote-sensing driven global forest monitoring system over British Columbian focus areas

不列颠哥伦比亚省重点地区遥感驱动的全球森林监测系统的算法开发和验证

• 批准号: 436436-2012
• 负责人: Coops, Nicholas
• 金额: $ 1.31万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=498296
• 关键词: Algorithmic; development; verification; remote; sensing

Estimating annual changes in forest disturbance is critical for understanding the current and future capacity of forests to sequester carbon. In countries like Canada, we have access to well established forest inventories and monitoring programs to gain this information, however many developing countries have forest areas that are not well monitored or characterised. Without these inventory programs, many of these countries cannot fully participate in internationally driven activities such as the Reducing Emissions from Deforestation and forest Degradation (REDD+) Programme which is aimed at reducing the loss of forest carbon stocks.

估算森林扰动的年度变化对于了解森林目前和未来固碳能力至关重要。在加拿大等国家，我们可以使用完善的森林资源清单和监测计划来获取这些信息，但许多发展中国家的森林面积没有得到很好的监测或描述。如果没有这些清单计划，这些国家中的许多国家就无法充分参与国际驱动的活动，如旨在减少森林碳储量损失的减少毁林和森林退化所致排放量（REDD+）计划。