Evaluating wood volume estimates derived from Quickbird imagery with GEOBIA for Pinus nigra trees in the Pentalofo forest, northern Greece

REMOTE SENSING LETTERS(2017)

引用 3|浏览6
暂无评分
摘要
The objective of this research was to evaluate wood volume estimates of Pinus nigra trees in forest stands, which were derived utilizing Geographic Object-Based Image Analysis. Information on forest parameters such as wood volume and number of trees is useful for forest management facilitating forest sustainability. Most of the existing approaches used to estimate wood volume of forest trees require field measurements, which are laboursome. In this study, the collected field data were utilized only in order to investigate the results. Wood volume was estimated based on an individual tree crown approach and using monoscopic satellite images in combination with allometric data. The study area is the Pentalofo forest, which is located in Kozani prefecture in western Macedonia, Northern Greece. About 1 plot surface of 0.1143 ha was utilized. During the preprocessing, a pansharpened image was produced from two Quickbird satellite images (one multispectral image of 2.4 m spatial resolution and one panchromatic image of 0.6 m spatial resolution). Bands of this image were utilized single or in combination in order to delineate the tree crowns individually. The allometric equation served in order to calculate the tree Diameter at Breast Height (DBH) utilizing the detected tree crowns. The evaluation was conducted on three levels: (i) number of trees, (ii) DBH class distribution and (iii) wood volume. On the third level, the evaluation procedure was conducted twice; once using field height and once without. The difference between the results and the field data for the wood volume reached a maximum of approximately 30%. The total number of trees was exactly the same as counted in the field and the DBH distribution showed a tendency for the trees to move to a higher DBH class, resulting in an overestimation of the wood volume.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要