KMS XINJIANG INSTITUTE OF ECOLOGY AND GEOGRAPHY，CAS
| 典型荒漠植物叶片和冠层蒸腾高光谱遥感研究 | |
| 靳佳 | |
| Subtype | 博士 |
| Thesis Advisor | 王权 ; 李兰海 |
| 2017-05-01 | |
| Degree Grantor | 中国科学院大学 |
| Place of Conferral | 新疆乌鲁木齐 |
| Degree Discipline | 理学博士 |
| Keyword | 干旱区 蒸腾 Scope 光谱指数 Plsr 辐射传导模型 Arid Land Transpiration Scope Spectral Indices Plsr Radiative Transfer Model |
| Abstract | 植物蒸腾反映植物耗水情况与生理状态，是区域能量平衡和水量平衡的重要组成部分。在干旱区，准确掌握荒漠植物蒸腾动态是理解干旱区水循环和监测荒漠生态系统稳定性的重要途径。本研究针对传统的植物蒸腾速率的获取方法耗时耗力，无法实现快速动态监测等缺点，以典型荒漠植物梭梭（Haloxylon ammodendron）为研究对象，开展植物蒸腾、高光谱反射信息、植物生化物理等参数及环境因子的野外同步观测实验。基于野外同步实测数据，结合统计方法（指数法、PLSR 法）与 SCOPE 机理模型，研究探讨了不同尺度（叶片和冠层）植物蒸腾的高光谱遥感反演方法，得到的研究成果如下：（1）研究提出了结合 EFAST 全局敏感性分析方法和多目标优化的 SCOPE 模型校正方法。对 SCOPE 模型的敏感性分析结果表明，在 460 nm，675 nm 和 1900 nm附近的冠层反射率受植物生理参数的一定影响，可能与植物蒸腾等生理过程存在联系。研究改进和校正的 SCOPE 模型能够较准确模拟荒漠植物冠层反射信息（R2 >0.9）、冠层蒸腾（R2 > 0.6），及净辐射（R2 > 0.9）。（2）对同步实测数据的植物蒸腾高光谱遥感分析结果表明：一阶导数光谱相比原始反射率在荒漠植物蒸腾估算中的精度更高，尤其是在包含强土壤背景噪声的冠层尺度。研究基于一阶导数光谱，分别构建了叶片和冠层尺度蒸腾最优光谱指数和 PLSR模型。在叶片尺度，基于一阶导数光谱的最优指数 dND(1020, 1900) 估算的叶片蒸腾与实测值之间的决定系数为 0.33，而基于 9 个波段（2210，2215，1980，2205，2000，2140，435，2375 和 2345 nm）一阶导数光谱建立的 PLSR 模型估算的叶片蒸腾与实测值之间的决定系数为 0.71。在冠层尺度，基于一阶导数光谱的最优指数 dSR(660,1040)估算的冠层蒸腾与实测值间的决定系数为 0.53，而基于 7 个波段（670，1195，2190，915，2425，2365 和 2205 nm）导数光谱建立的 PLSR 模型估算的冠层蒸腾与实测值间的决定系数分为 0.78。（3）为解决基于实测数据的植被参数估算统计模型因数据量有限，存在普适性差的问题，研究提出了结合 SCOPE 模拟数据库与野外实测数据集的冠层蒸腾高光谱指数开发方法。结合模拟数据库和实测数据集得到的高光谱指数在实测数据集和模拟数据库中蒸腾估算具有较好的一致性，基于一阶导数光谱的 dSR(660, 1040)指数对实测数据集和模拟数据库中蒸腾估算 R2 分别为 0.54 和 0.50。同时，该指数也是在 10 nm光谱间隔下的最优光谱指数。因此，dSR(660, 1040)指数可为利用 Hyperion 及 AVIRIS等高光谱影像产品进行大范围植物蒸腾遥感监测提供参考。本研究建立了高光谱技术估算荒漠植物蒸腾的新途径，研究成果可为高光谱遥感技术在干旱荒漠生态安全与稳定的监测应用提供技术支持和科学理论依据。 |
| Other Abstract | Transpiration, an important indicator of vegetation water consumption situation and physiological status, is one of the most critical components of regional water and energy fluxes. A clear understanding of plant transpiration is an essential way to improve our knowledge of water cycle in arid areas and arid ecosystems monitoring as well. However,traditional measurements of transpiration are generally time consuming, expensive, and often unfeasible at regional scale. In this study, we focused on a native dominant plant in the arid land of Central Asia——Haloxylon ammodendron, and conducted synchronous measurements of transpiration, biochemical, biophysical, environmental and soil parameters, as well as in situ hyperspectral reflectance at different scales. This research explored a new way to estimate transpiration from hyperspectral remote sensing by combining statistical methods with SCOPE model. In detail:(1) This research proposed a calibration method for SCOPE model by combining the EFAST global sensitivity analysis (GSA) with multi-objective optimization. The GSA results revealed that plant physiological parameters had impacts on canopy spectra around 460 nm, 675 nm and 1900 nm, indicating that the canopy reflectance around these bands would have the potential to trace the physiological process like transpiration in turn. The calibrated SCOPE model was capable of simulating canopy reflectance (R2 > 0.9),transpiration (R2 > 0.6) and net radiation (R2 > 0.9) of Haloxylon ammodendron accurately.(2) Hyperspectral remote sensing of transpiration based on synchronous field measured dataset revealed that the first-derivative spectra based indices and PLSR models were more effective for tracing transpiration compared with those models based on the original reflectance. At leaf scale, the coefficent of determination (R2) of the identified best index dND(1020, 1900) using first-derivative spectra for estimating leaf transpiration was 0.33, while R2 of the PLSR model with 9 bands (2210, 2215, 1980, 2205, 2000, 2140, 435,2375 and 2345 nm) of the first-derivative spectra reached 0.71. At canopy scale, the R2 of the identified best index dSR(660,1040) based on the first-derivative spectra for estimating canopy transpiration was 0.54, and R2 of PLSR model with 7 bands (670, 1195, 2190, 915,2425, 2365 and 2205 nm) of the first-derivative spectra was 0.78.(3) This research combined a simulated database generated by SCOPE model with the field measured dataset to develop a potentially general and robust index for transpiration estimation. Results proved that the index dSR(660,1040) based on the first-derivative spectra performed well for both field measured dataset and simulated database generated by SCOPE model. The coefficients of determination (R2) of dSR(660,1040) with the canopy transpiration in the two datasets were 0.54 and 0.50, respectively. Moreover,dSR(660,1040) was also the best index to trace canopy transpiration with the spectral resolution of 10 nm, suggesting dSR(660,1040) might be a generic one and could be widely applicable for regional transpiration monitoring with images from Hyperion and AVIRIS.This research highlighted a promising way to retrieve plant transpiration from the hyperspectral remote sensing data. The results obtained in this study also would have provided a basis for monitoring ecological safety and stability in arid land using remote sensing data. |
| Subject Area | 地图学与地理信息系统 |
| Language | 中文 |
| Document Type | 学位论文 |
| Identifier | http://ir.xjlas.org/handle/365004/14782 |
| Collection | 研究系统_荒漠环境研究室 |
| Affiliation | 中国科学院新疆生态与地理研究所 |
| Recommended Citation GB/T 7714 | 靳佳. 典型荒漠植物叶片和冠层蒸腾高光谱遥感研究[D]. 新疆乌鲁木齐. 中国科学院大学,2017. |
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