Modeling Local Vapor Pressure Deficit Using Drone-based Photogrammetry Data

This dataset supports the research article, "Local atmospheric vapor pressure deficit as a microclimate index to assess tropical rainforest riparian restoration success." It contains Photogrammetry-derived point cloud data (.las files) representing 3D forest structure from 30 plots across five riparian restoration stages. The dataset also includes R code used for processing this point-cloud data to extract key forest structural metrics (provided in code metrics.extraction.las), R code for modeling and mapping vapor pressure deficit (VPD) using these metrics, and field-collected microclimatic data (provided as plot.data.xlsx), and the resulting VPD model (code, model). In addition, all data collected in the field to allow comparing microclimate between sites are available in (data.xlsx). These data allow for comprehensive analysis and replication of the study's findings. Research Hypothesis: Riparian forest restoration success in tropical rainforests can be quantified using vapor pressure deficit (VPD) as a microclimate indicator. Higher VPD values indicate lower restoration success due to increased stress on vegetation. Forest structure, measurable through photogrammetry, significantly influences VPD. The data demonstrates a strong negative correlation between forest structure (particularly height metrics like the 50th and 75th percentiles of height distribution) and VPD. Old-growth forests exhibit significantly lower VPD values than younger, restored forests, highlighting the role of mature forest canopies in buffering VPD. Early-stage restoration sites show consistently higher VPD, exceeding a threshold (1.0 kPa) associated with negative impacts on ecosystem functioning. Notable Findings: VPD as a Restoration Indicator: VPD effectively differentiates restoration stages and is a reliable indicator of restoration success. Forest Structure's Role: The study quantifies the strong influence of forest structure on VPD, showing that taller, denser canopies effectively buffer VPD, leading to more stable microclimatic conditions. Spatial Mapping: Spatial VPD mapping, enabled by photogrammetry, offers valuable insights for targeted interventions in forest management. Canopy Buffering: Mature forests exhibit a significantly higher capacity to buffer VPD fluctuations compared to younger forests, which can be used to inform restoration strategies and site selection. The findings support the hypothesis that VPD, in combination with photogrammetrically derived forest structural metrics, can effectively assess forest restoration success. Spatial mapping enables more precise targeting of restoration activities and enhances site selection and adaptive management strategies based on the microclimatic conditions of specific areas.本数据集配套支撑研究论文《以局地大气水汽压亏缺作为微气候指标评估热带雨林河岸带修复成效》。本数据集包含5个河岸带修复阶段共30个样地的三维森林结构点云数据（.las格式文件），该数据由摄影测量（Photogrammetry）技术生成。此外，数据集还涵盖：用于处理该点云数据以提取关键森林结构指标的R代码（代码文件为metrics.extraction.las）、基于上述指标建模并绘制水汽压亏缺（Vapor Pressure Deficit, VPD）空间分布图的R代码、野外采集的微气候数据（存放于plot.data.xlsx），以及最终得到的VPD模型（含代码与模型文件）。此外，所有用于对比不同样地微气候的野外采集数据均收录于data.xlsx文件中。 上述数据可支撑本研究结果的全面分析与重复验证。 研究假说： 热带雨林河岸带的森林修复成效，可通过以水汽压亏缺（Vapor Pressure Deficit, VPD）作为微气候指标进行量化评估。由于植被承受的胁迫加剧，较高的VPD值对应着更低的修复成效。而通过摄影测量（Photogrammetry）技术可量化的森林结构，会对VPD产生显著影响。 本数据集的分析结果表明，森林结构（尤其是高度分布的50百分位数、75百分位数等高度指标）与VPD之间存在显著负相关关系。原生林的VPD值显著低于年轻修复林，这凸显了成熟林冠层对VPD的缓冲作用。早期修复样地的VPD值始终偏高，超过了与生态系统功能负面影响相关的阈值（1.0 kPa）。 重要研究发现： 1. 以VPD作为修复成效指标：VPD可有效区分不同修复阶段，是评估森林修复成效的可靠指标。 2. 森林结构的调控作用：本研究量化了森林结构对VPD的显著影响，结果显示更高大、更致密的林冠可有效缓冲VPD，进而形成更稳定的微气候条件。 3. 空间制图应用：依托摄影测量技术实现的VPD空间制图，可为森林管理中的精准干预提供重要参考依据。 4. 林冠缓冲效应：相较于年轻林分，成熟林对VPD波动的缓冲能力显著更强，该结论可为修复策略制定与样地选择提供科学支撑。 本研究结果验证了如下假说：将VPD与摄影测量技术获取的森林结构指标相结合，可有效评估森林修复成效。空间制图技术可实现修复活动的精准靶向实施，并基于特定区域的微气候条件优化样地选择与适应性管理策略。