Abstract The objective of this study was to estimate forest variables using TanDEM-X interferometric synthetic aperture radar (InSAR) data acquired over the Shastkalate forest of Gorgan in northern Iran. Inventory variables, including diameter at breast height, tree height (Lorey’s mean tree height), basal area and volume, were collected from 112 circular sample plots with a size of 0.1 ha. Interferometric phase height and coherence were computed from TanDEM-X data. Stepwise multiple linear regression was used to develop models describing the relationship between field-derived forest variables and the InSAR based statistical metrics. The validation was carried out using the leave-one-out cross-validation method. The estimation accuracy results in terms of relative RMSE for Lorey’s mean tree height, basal area and volume were 11.0, 34.1, and 37.8%, respectively, whereas the corresponding figures for R2adj were 32.0, 10.0, and 16.0%, respectively. The results were good enough for estimating forest variables and it was concluded that TanDEM-X could be used in Hyrcanian hardwood forests.

中文翻译：

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使用海尔卡尼亚森林中的 TanDEM-X 数据估计森林变量

摘要 本研究的目的是使用在伊朗北部戈尔甘的 Shastkalate 森林上获得的 TanDEM-X 干涉合成孔径雷达 (InSAR) 数据估计森林变量。从 0.1 公顷大小的 112 个圆形样地收集清单变量，包括胸高直径、树高（Lorey 平均树高）、基面积和体积。从 TanDEM-X 数据计算干涉相位高度和相干性。逐步多元线性回归用于开发描述现场导出的森林变量与基于 InSAR 的统计指标之间关系的模型。验证采用留一法交叉验证法。Lorey 的平均树高、基面积和体积的相对 RMSE 估计精度结果分别为 11.0、34.1 和 37.8%，R2adj 的相应数字分别为 32.0、10.0 和 16.0%。结果足以估计森林变量，并得出结论，TanDEM-X 可用于希尔卡尼亚阔叶林。