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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Stand delineation and composition estimation using semi-automated individual tree crown analysis
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Stand delineation and composition estimation using semi-automated individual tree crown analysis

机译:利用半自动个体树冠分析进行林分轮廓和成分估计

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Stand delineation and species composition estimation are cornerstones of forest inventory mapping and key elements to forest management decision making. Improved mapping techniques are constantly being sought in terms of speed, consistency, accuracy, level of detail, and overall effectiveness. Semi-automated analysis of high-resolution imagery at the individual tree crown level may offer such benefits. Methods, however, need to be developed and tested under a variety of forest conditions. High-resolution (60 cm) multispectral airborne imagery was acquired over a predominantly young conifer forest and plantation test area on the west coast of Canada. Automated tree isolation algorithms were applied to the data in order to delineate tree crowns or clusters of crowns. An object-oriented single tree classification was conducted using a maximum likelihood classifier. Stands of similar species composition, closure, and stem density were defined through a sequence that first generated images of these parameters from the automated delineation and classification, used these as input to an unsupervised classification, and then filtered and smoothed the resulting classification clusters. Because of the dense nature of the stands and small crowns on the site, the isolation process often delineated clusters of several trees. Species classification accuracy was determined by comparing the average stand composition from the automated technique to that derived from ground transects or plots. Species classification was good, with average composition error (difference between field measured and automated composition) over all 16 test stands being 7.25%. Most errors for individual species in stands were below 20%, but a few were up to 30%. The automatically generated stand boundaries mimicked well those of known plantation and interpreted inventory boundaries. The automated technique created a few larger stands and some additional small stands in areas of complex forest structure. Overall, for the young fairly uniform stands of the site, both stand delineation and species composition estimation were of a quality suitable for operational use in inventory and forest management. Further development and testing is needed to extend results to situations covering large areas, multiple flight lines, varied topography, and different forest conditions. (C) 2003 Elsevier Science Inc. All rights reserved. [References: 36]
机译:林分的划定和物种组成的估算是森林清单测绘的基石,也是森林管理决策的关键要素。在速度,一致性,准确性,详细程度和整体有效性方面不断寻求改进的映射技术。在单个树冠级别对高分辨率图像进行半自动分析可能会提供此类好处。但是,需要在各种森林条件下开发和测试方法。在加拿大西海岸一个年轻的针叶林和人工林测试区上采集了高分辨率(60厘米)多光谱机载航空影像。将自动树隔离算法应用于数据,以描绘树冠或树冠簇。使用最大似然分类器进行了面向对象的单树分类。通过以下顺序定义具有相似物种组成,封闭和茎密度的林分:首先从自动定界和分类中生成这些参数的图像,然后将这些图像用作无监督分类的输入,然后对所得分类簇进行过滤和平滑处理。由于林分茂密的性质和场地上的小树冠,隔离过程经常描绘出几棵树的集群。通过比较自动化技术的平均林分组成与地面样地或样地得出的林分组成,可以确定物种的分类准确性。物种分类良好,所有16个试验台的平均组成误差(实地测量值与自动组成之间的差异)为7.25%。林分中单个物种的大多数误差均低于20%,但少数误差高达30%。自动生成的林分边界很好地模仿了已知种植园的林分边界并解释了库存边界。自动化技术在森林结构复杂的地区创建了一些较大的林分和一些其他的小型林分。总体而言,对于该地点年轻,统一的林分,林分的划定和物种组成的估算均适合用于清单和森林管理的业务使用。需要进一步的开发和测试,以将结果扩展到涉及大面积,多条飞行路线,变化的地形和不同森林状况的情况。 (C)2003 Elsevier Science Inc.保留所有权利。 [参考:36]

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