• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Spatially explicit modelling of forest structure and function using airborne lidar and hyperspectral remote sensing data combined with micrometeorological measurements.
【24h】

Spatially explicit modelling of forest structure and function using airborne lidar and hyperspectral remote sensing data combined with micrometeorological measurements.

机译：使用机载激光雷达和高光谱遥感数据结合微气象测量对森林结构和功能进行空间显式建模。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This research models canopy-scale photosynthesis at the Groundhog River Flux Site through the integration of high-resolution airborne remote sensing data and micrometeorological measurements collected from a flux tower. Light detection and ranging (lidar) data are analysed to derive models of tree structure, including: canopy height, basal area, crown closure, and average aboveground biomass. Lidar and hyperspectral remote sensing data are used to model canopy chlorophyll (Chl) and carotenoid concentrations (known to be good indicators of photosynthesis). The integration of lidar and hyperspectral data is applied to derive spatially explicit models of the fraction of photosynthetically active radiation (fPAR) absorbed by the canopy as well as a species classification for the site. These products are integrated with flux tower meteorological measurements (i.e., air temperature and global solar radiation) collected on a continuous basis over 2004 to apply the C-Fix model of carbon exchange to the site.; Results demonstrate that high resolution lidar and lidar-hyperspectral integration techniques perform well in the boreal mixedwood environment. Lidar models are well correlated with forest structure, despite the complexities introduced in the mixedwood case (e.g., r2=0.84, 0.89, 0.60, and 0.91, for mean dominant height, basal area, crown closure, and average aboveground biomass). Strong relationships are also shown for canopy scale chlorophyll/carotenoid concentration analysis using integrated lidar-hyperspectral techniques (e.g., r2=0.84, 0.84, and 0.82 for Chl(a), Chl(a+b), and Chl(b)). Examination of the spatially explicit models of fPAR reveal distinct spatial patterns which become increasingly apparent throughout the season due to the variation in species groupings (and canopy chlorophyll concentration) within the 1 km radius surrounding the flux tower. Comparison of results from the modified local-scale version of the C-Fix model to tower gross ecosystem productivity (GEP) demonstrate a good correlation to flux tower measured GEP (r2=0.70 for 10 day averages), with the largest deviations occurring in June-July.; This research has direct benefits for forest inventory mapping and management practices; mapping of canopy physiology and biochemical constituents related to forest health; and scaling and direct comparison to large resolution satellite models to help bridge the gap between the local-scale measurements at flux towers and predictions derived from continental-scale carbon models.
机译：这项研究通过集成高分辨率机载遥感数据和从通量塔收集的微气象测量结果，模拟了土拨鼠河通量站点的冠层尺度的光合作用。分析光检测和测距（激光）数据以得出树木结构的模型，包括：冠层高度，基础面积，树冠闭合和平均地上生物量。激光雷达和高光谱遥感数据用于对冠层叶绿素（Chl）和类胡萝卜素浓度（已知是光合作用的良好指标）进行建模。激光雷达和高光谱数据的集成可用于得出冠层吸收的光合有效辐射（fPAR）比例的空间显式模型，以及该地点的物种分类。这些产品与通量塔气象测量结果（即气温和全球太阳辐射）集成在一起，该测量结果是在2004年连续收集的，以将C-Fix碳交换模型应用于该地点。结果表明，高分辨率激光雷达和激光雷达-高光谱集成技术在北方混合木环境中表现良好。尽管在混合木情况下引入了复杂性（例如，对于平均优势高度，基础面积，树冠闭合和平均地上生物量，r2 = 0.84、0.89、0.60和0.91），激光雷达模型与森林结构具有很好的相关性。使用集成的激光雷达-高光谱技术进行冠层规模的叶绿素/类胡萝卜素浓度分析也显示出很强的关系（例如，Chl（a），Chl（a + b）和Chl（b）的r2 = 0.84、0.84和0.82）。对fPAR的空间显式模型的研究表明，由于通量塔周围1 km半径内物种分组（和冠层叶绿素浓度）的变化，整个季节的明显空间格局变得越来越明显。将修正的局部修正版本的C-Fix模型的结果与塔式生态系统总生产率（GEP）进行比较，结果表明，与流量塔测得的GEP有很好的相关性（10天平均值为r2 = 0.70），最大偏差发生在6月。 -七月。;这项研究对森林资源清单制图和管理实践具有直接的好处；测绘与森林健康有关的树冠生理和生化成分；并与大型卫星模型进行比例缩放和直接比较，以帮助弥补通量塔的局部尺度测量值与大陆尺度碳模型得出的预测之间的差距。

著录项

  • 作者

    Thomas, Valerie Anne.;

  • 作者单位

    Queen's University (Canada).;

  • 授予单位 Queen's University (Canada).;
  • 学科 Environmental Sciences.; Remote Sensing.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 228 p.
  • 总页数 228
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 环境科学基础理论;遥感技术;
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号