多枝柽柳年轮生长速率测量及TRGR指标优势分析

Abstract

PDF HTML阅读 XML下载 导出引用 引用提醒 多枝柽柳年轮生长速率测量及TRGR指标优势分析 DOI: 10.5846/stxb202202080312 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 欧盟Erasmus+项目（598838-EPP-1-2018-EL-EPPKA2-CBHE-JP） Tree-ring growth rate measurement of Tamarix ramosissima and tree-ring growth rate index superiority analysis Author: Affiliation: Fund Project: This work was supported by the GIS and RS for Sustainable Forestry and Ecology（598838-EPP-1-2018-EL-EPPKA2-CBHE-JP） 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:灌木对生境和气候变化具有高度敏感性，其年轮资料在认识区域环境演变过程、全球气候变化和环境保护中具有重要作用。灌木植株在生长过程中受遗传和极端环境的影响，年轮常出现偏心和不规则生长，这使得专业年轮分析软件测量的年轮宽度数据难以准确反映其整体径向生长信息。为探讨适合于寒旱区灌木年轮学研究的年轮测量指标和测量方法，研究以该区域荒漠常见植物多枝柽柳（Tamarix ramosissima Ledeb.）为研究对象，通过U-net深度学习方法，获得年轮提取训练模型，自动获取扫描轮盘各年早材区域。轮盘扫描及语义分割后的图像经GIS配准赋坐标、ENVI图像处理后，借助GIS编辑和测量工具，完成多枝柽柳各年年轮生长速率（Tree-ring growth rate，TRGR）、年轮宽度（Tree-ring width，TRW）和树木基部断面积生长增量（Basal area increment，BAI）的测量；研究基于Timesat Savitzky-Golay （S-G）滤波时间序列拟合，获取点样尺度归一化植被指数（Normalized difference vegetation index，NDVI）季节曲线峰值、季节开始时的增长速率、大季节积分和季节结束时的值等7个关键参数。将多枝柽柳TRGR、TRW和BAI测量结果与NDVI季节曲线关键参数进行相关性分析，检验TRGR指标的合理性，分析指标优势。结果表明：测量的多枝柽柳TRGR指标与点样尺度NDVI关键参数间存在高度正相关，最高相关系数达0.98。TRGR指标不仅能够反映多枝柽柳年轮整体径向生长情况，而且可以有效去除年轮指标中的胸径趋势，突显指标环境趋势，有利于解决树木年轮学中指标去趋势难的问题。TRGR与TRW和BAI指标相比优势明显，可以作为灌木年轮学研究的新代用指标。研究结果为多枝柽柳年轮信息重构NDVI或反之提供了有利证据。研究构建的年轮测量方法相比于专业年轮分析系统具有更为多样的测量手段。研究结果可推动寒旱区灌木年轮学发展。 Abstract:Shrubs are highly sensitive to habitat and climate change, and its tree-ring data plays an important role in understanding regional environmental evolution, global climate change and environmental protection. Due to the influence of heredity and extreme environment during shrub growth, the growth rings often have serious eccentricity and irregular growth, which makes it difficult for the tree-ring width measurement by professional tree-ring analysis software to accurately reflect the overall radial growth information. In order to explore the measuring indexes and methods of tree-ring, which are suitable for study on shrub dendrochronology in cold and arid regions, this study takes Tamarix ramosissima Ledeb., a common desert plant in this region, as the study object. Based on U-net deep learning method, we created the training model of Tamarix ramosissima tree-ring extraction, which would automatically obtain each year tree-ring springwood area of scanning disc. After tree-ring scanning image and semantic segmentation image were processed by GIS assigning measurement coordinates and ENVI image processing, tree-ring growth rate (TRGR), tree-ring width (TRW), and basal area increment (BAI) of tamarix ramosissima were measured by using GIS editing and measurement tools. Based on Timesat Savitzky-Golay (S-G) filtering time series fitting, seven key parameters of seasonal curve of normalized difference vegetation index (NDVI) were obtained at point-scale, including peak value, rate of increase at the beginning of the season, large seasonal integral and value for the end of the season etc. The correlation between TRGR, TRW, BAI and the key parameters of NDVI seasonal curve were analyzed to test the rationality and to analyze the advantages of TRGR index. The results show that there are high positive correlations between TRGR index of Tamarix ramosissima and the key parameters of point-scale NDVI seasonal curve. The highest correlation coefficient is 0.98.TRGR index can not only reflect the overall radial growth of tree-ring, but also effectively remove trend of diameter at breast height (DBH) in tree-ring index and highlight the index's environmental trend, which is helpful to solve the problem of index detrending in dendrochronology. Compared with TRW and BAI, TRGR index has obvious advantages and it can be used as a new index for shrub dendrochronology. The results provide evidence for NDVI reconstruction from tree-ring information of tamarix ramosissima or vice versa. Research methods have more diverse means than the professional tree-ring analysis system measurement. The results can promote the development of shrub dendrochronology in cold and arid regions. 参考文献 相似文献 引证文献