SGER: Seeing the forest and the trees

SGER：既见森林又见树木

• 批准号: 0713866
• 负责人: Gordon Fox
• 金额: --
• 依托单位: University of South Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-03-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0713866&HistoricalAwards=false
• 关键词: SGER; Seeing; forest; trees

Research on many problems in ecology, geography, and forestry depends on being able to accurately identify (to species) and map a large number of individual trees. Doing this on the ground is straightforward, but consumes so much time and expense as to be prohibitive for areas larger than a hundred or so acres -- smaller than the scale on which most forests vary. Consequently, researchers have been hoping to be able to use aerial photography and/or satellite data to do this. However, identification methods have generally not been very accurate. Recently, a new method for identification from satellite or photographic data was developed; it differs from other methods in that each species is compared successively with all other species, rather than simultaneously attempting to match individuals to the descriptions of species. A preliminary study in the UK suggested that this method has much promise. However, it remains to be seen how useful this method is in more challenging settings where there are many species, including many that closely resemble one another. This project will constitute a much more severe trial of this new method, in that it will attempt to correctly identify and map individuals of 18 species (out of 200+) in a first-growth Mexican tropical forest. For each species there is at least one closely-related (and thus similar) species present. This study will thus provide critical data allowing other researchers to determine when this method is useful. Should this particular test be successful, it will also provide a remarkable dataset on the spatial distribution of trees in an intact tropical forest.

对生态学、地理学和林业中许多问题的研究依赖于能够准确地识别（到物种）和绘制大量个体树木的地图。在地面上做这件事很简单，但要花费太多的时间和费用，以至于超过100英亩的面积是令人望而却步的--比大多数森林的规模都要小。因此，研究人员一直希望能够使用航空摄影和/或卫星数据来做到这一点。然而，识别方法通常不是很准确。最近，发展了一种新的从卫星或照片数据进行识别的方法;它与其他方法的不同之处在于，每个物种都连续地与所有其他物种进行比较，而不是同时试图将个体与物种的描述相匹配。英国的一项初步研究表明，这种方法很有前途。然而，这种方法在更具挑战性的环境中有多大用处还有待观察，因为那里有许多物种，包括许多彼此非常相似的物种。该项目将对这种新方法进行更严格的试验，因为它将试图正确识别和绘制墨西哥热带森林中18个物种（超过200个）的个体。每个物种至少有一个密切相关（因此相似）的物种存在。因此，这项研究将提供关键数据，使其他研究人员能够确定这种方法何时有用。如果这项特殊的测试成功，它还将提供一个关于完整热带森林中树木空间分布的显着数据集。