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1.
新一代星载激光雷达卫星ICESat-2首次采用了微脉冲光子计数激光雷达技术,由于单光子探测的灵敏性导致数据在大气和地表下层产生了大量噪声,因此对光子计数激光雷达点云数据实现信号和噪声的分离是开展进一步应用研究的前提和基础。本文选择美国俄勒冈州和弗吉尼亚州2个研究区,采用MATLAS数据,根据光子点云数据的特点构造了12个光子点云特征,对所构造的特征利用随机森林进行变量筛选,用机器学习方法对光子点云进行分类,并将建立好的模型推广到整个研究区。研究结果表明,本文构建的分类器分类总精度达到了96.79%,Kappa系数为0.94,平均生产者精度和用户精度分别为97.1%和96.8%。在相对弱噪声、平坦地形区域和强噪声、复杂地形区域都取得较好的分类结果。本文结果显示了基于少量样本通过机器学习的方法构建模型,可以推广到较大范围区域的光子点云分类应用中。  相似文献   
2.
为了研究大气静力平衡适应过程的本质,利用波动理论和能量转换角度,分别对完全可压缩的等温大气模型、滞弹近似下的等温大气模型和层结中性大气模型进行研究比较.结果表明:大气静力平衡适应过程的本质是声波和混合声重力波对扰动能量的频散过程,滞弹近似模型和层结中性模型均不能完全描述此适应过程;在波动假设下,此三类大气模型中扰动物理量之间的偏振关系同波动的性质有关,气团的运动方程均为椭圆方程,声波和混合声重力波对气团运动的作用差异较显著.
大气静力平衡适应过程中扰动能量以有效势能、有效弹性势能、动能或波动能量的形式存在并相互转换;扰动有效势能与其他形式能量之间的转换与混合声重力波或者重力内波有关,扰动有效弹性势能与其他形式能量之间的转换与声波有关.在完全可压缩的等温大气模型中,扰动有效势能增加1个单位,其中69.9%来自扰动垂直动能,其余30.1%来自扰动有效弹性势能.  相似文献   
3.
不同厚度饱和砂土中群桩结构动力响应试验研究   总被引:2,自引:2,他引:0       下载免费PDF全文
液化土中桩基础动力响应规律一直是工程抗震领域关注的热点问题。本文基于非液化砂土和不同厚度饱和砂土中的2×2群桩结构模型振动台试验,通过输入一定峰值加速度和频率的正弦波,对群桩在非液化土层和两种不同厚度饱和砂土层中的横向动力响应特性进行振动台试验研究。研究结果表明:在正弦波输入情况下,非液化砂土中群桩承台加速度和位移时程与台面输入时程相比,波形变化规律与峰值大小均相差不大;而对两种不同厚度饱和砂土中承台加速度和位移峰值放大较多,在相对较薄的饱和砂土中群桩承台加速度峰值较台面输入放大了1.83倍,较台面输出位移峰值放大了1.58倍;在相对较厚的饱和砂土中承台加速度和位移峰值则分别放大了2.18倍和1.91倍,说明在相同输入条件下,较厚的饱和砂土在发生液化后群桩承台的动力响应更加显著。  相似文献   
4.
豫西南泥湖钼矿集区是以花岗斑岩体为中心的钼多金属矿床系列,区内出露大面积加里东期变辉长岩和燕山期辉长岩。通过分析区内辉长岩的岩石学、年代学、地球化学和成矿元素等方面特征,研究其在成岩成矿过程中的作用。区内加里东期变辉长岩和燕山期辉长岩成矿元素总稀土含量低,稀土元素球粒陨石标准化曲线右倾平缓,具有明显的Eu,Tm元素的异常;同比世界基性岩,自晚元古代上地幔主要成矿元素(除钨元素以外)基本没有明显的富集,主成矿元素钼含量呈明显的亏损,预示燕山期成矿花岗质岩浆没有从上地幔获得主要成矿物质。初步认为大规模的钼多金属成矿带的形成与基性岩浆的底垫作用相关,基性岩浆的底垫作用为下地壳部分熔融形成岩浆房提供了热源。  相似文献   
5.
机载LiDAR在公路勘测方面的用途日益广泛。该文对直升机机载LiDAR在高速公路改扩建中的应用技术路线可行性进行了研究论证,从地面控制测量、点云数据获取、点云数据处理、成果应用等多个方面进行了阐述,通过分析LiDAR点云数据在5种不同地面控制点布设方案校正下的点云数据精度,论证了利用地面控制点对直升机机载LiDAR点云数据进行平面和高程校正的可行性。  相似文献   
6.
Soil moisture has a pronounced effect on earth surface processes. Global soil moisture is strongly driven by climate, whereas at finer scales, the role of non‐climatic drivers becomes more important. We provide insights into the significance of soil and land surface properties in landscape‐scale soil moisture variation by utilizing high‐resolution light detection and ranging (LiDAR) data and extensive field investigations. The data consist of 1200 study plots located in a high‐latitude landscape of mountain tundra in north‐western Finland. We measured the plots three times during growing season 2016 with a hand‐held time‐domain reflectometry sensor. To model soil moisture and its temporal variation, we used four statistical modelling methods: generalized linear models, generalized additive models, boosted regression trees, and random forests. The model fit of the soil moisture models were R2 = 0.60 and root mean square error (RMSE) 8.04 VWC% on average, while the temporal variation models showed a lower fit of R2 = 0.25 and RMSE 13.11 CV%. The predictive performances for the former were R2 = 0.47 and RMSE 9.34 VWC%, and for the latter R2 = 0.01 and RMSE 15.29 CV%. Results were similar across the modelling methods, demonstrating a consistent pattern. Soil moisture and its temporal variation showed strong heterogeneity over short distances; therefore, soil moisture modelling benefits from high‐resolution predictors, such as LiDAR based variables. In the soil moisture models, the strongest predictor was SAGA (System for Automated Geoscientific Analyses) wetness index (SWI), based on a 1 m2 digital terrain model derived from LiDAR data, which outperformed soil predictors. Thus, our study supports the use of LiDAR based SWI in explaining fine‐scale soil moisture variation. In the temporal variation models, the strongest predictor was the field‐quantified organic layer depth variable. Our results show that spatial soil moisture predictions can be based on soil and land surface properties, yet the temporal models require further investigation. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   
7.
Animal husbandry and crop farming are specialized for development in separate areas on the Tibetan Plateau. Such a pattern of isolation has led to current concerns of rangeland and farming system degradation due to intensive land use. The crop-livestock integration, however, has been proven to increase food and feed productivity thorough niche complementarity, and is thereby especially effective for promoting ecosystem resilience. Regional synergy has emerged as an integrated approach to reconcile rangeland livestock with forage crop production. It moves beyond the specialized sectors of animal husbandry and intensive agriculture to coordinate them through regional coupling. Therefore, crop-livestock integration (CLI) has been suggested as one of the effective solutions to forage deficit and livestock production in grazing systems. But it is imperative that CLI moves forward from the farm level to the regional scale, in order to secure regional synergism during agro-pastoral development. The national key R & D program, Technology and Demonstration of Recovery and Restoration of Degraded Alpine Ecosystems on the Tibetan Plateau, aims to solve the problems of alpine grassland degradation by building up a grass-based animal husbandry technology system that includes synergizing forage production and ecological functioning, reconciling the relationship between ecology, forage production and animal husbandry, and achieving the win-win goals of curbing grassland degradation and changing the development mode of animal husbandry. It is imperative to call for regional synergy through integrating ecological functioning with ecosystem services, given the alarming threat of rangeland degradation on the Tibetan Plateau. The series of papers in this issue, together with those published previously, provide a collection of rangeland ecology and management studies in an effort to ensure the sustainable use and management of the alpine ecosystems.  相似文献   
8.
Reliable quantification of savanna vegetation structure is critical for accurate carbon accounting and biodiversity assessment under changing climate and land-use conditions. Inventories of fine-scale vegetation structural attributes are typically conducted from field-based plots or transects, while large-area monitoring relies on a combination of airborne and satellite remote sensing. Both of these approaches have their strengths and limitations, but terrestrial laser scanning (TLS) has emerged as the benchmark for vegetation structural parameterization – recording and quantifying 3D structural detail that is not possible from manual field-based or airborne/spaceborne methods. However, traditional TLS approaches suffer from similar spatial constraints as field-based inventories. Given their small areal coverage, standard TLS plots may fail to capture the heterogeneity of landscapes in which they are embedded. Here we test the potential of long-range (>2000 m) terrestrial laser scanning (LR-TLS) to provide rapid and robust assessment of savanna vegetation 3D structure at hillslope scales. We used LR-TLS to sample entire savanna hillslopes from topographic vantage points and collected coincident plot-scale (1 ha) TLS scans at increasing distances from the LR-TLS station. We merged multiple TLS scans at the plot scale to provide the reference structure, and evaluated how 3D metrics derived from LR-TLS deviated from this baseline with increasing distance. Our results show that despite diluted point density and increased beam divergence with distance, LR-TLS can reliably characterize tree height (RMSE = 0.25–1.45 m) and canopy cover (RMSE = 5.67–15.91%) at distances of up to 500 m in open savanna woodlands. When aggregated to the same sampling grain as leading spaceborne vegetation products (10–30 m), our findings show potential for LR-TLS to play a key role in constraining satellite-based structural estimates in savannas over larger areas than traditional TLS sampling can provide.  相似文献   
9.
Inland water bodies are globally threatened by environmental degradation and climate change. On the other hand, new water bodies can be designed during landscape restoration (e.g. after coal mining). Effective management of new water resources requires continuous monitoring; in situ surveys are, however, extremely time-demanding. Remote sensing has been widely used for identifying water bodies. However, the use of optical imagery is constrained by accuracy problems related to the difficulty in distinguishing water features from other surfaces with low albedo, such as tree shadows. This is especially true when mapping water bodies of different sizes. To address these problems, we evaluated the potential of integrating hyperspectral data with LiDAR (hereinafter “integrative approach”). The study area consisted of several spoil heaps containing heterogeneous water bodies with a high variability of shape and size. We utilized object-based classification (Support Vector Machine) based on: (i) hyperspectral data; (ii) LiDAR variables; (iii) integration of both datasets. Besides, we classified hyperspectral data using pixel-based approaches (K-mean, spectral angle mapper). Individual approaches (hyperspectral data, LiDAR data and integrative approach) resulted in 2–22.4 % underestimation of the water surface area (i.e, omission error) and 0.4–1.5 % overestimation (i.e., commission error).The integrative approach yielded an improved discrimination of open water surface compared to other approaches (omission error of 2 % and commission error of 0.4 %). We also evaluated the success of detecting individual ponds; the integrative approach was the only one capable of detecting the water bodies with both omission and commission errors below 10 %. Finally, the assessment of misclassification reasons showed a successful elimination of shadows in the integrative approach. Our findings demonstrate that the integration of hyperspectral and LiDAR data can greatly improve the identification of small water bodies and can be applied in practice to support mapping of restoration process.  相似文献   
10.
The role of hummocky terrain in governing runoff routing and focussing groundwater recharge in the Northern Prairies of North America is widely recognised. However, most hydrological studies in the region have not effectively utilised information on the surficial geology and associated landforms in large-scale hydrological characterization. The present study uses an automated digital elevation model (DEM) analysis of a 6500-km2 area in the Northern Prairies to quantify hydrologically relevant terrain parameters for the common types of terrains in the prairies with different surficial deposits widespread in the prairies, namely, moraines and glaciolacustrine deposits. Runoff retention (and storage) capacity within depressions varies greatly between different surficial deposits and is comparable in magnitude with a typical amount of seasonal snowmelt runoff generation. The terrain constraint on potential runoff retention varies from a few millimetres in areas classified as moraine to tens of millimetres in areas classified as stagnant ice moraine deposits. Fluted moraine and glaciolacustrine deposits have intermediate storage capacity values. The study also identified the probability density function describing a number of immediate upstream neighbours for each depression in a fill-and-spill network. A relationship between depression parameters and surficial deposits, as well as identified depression network structure, allows parametrisation of hydrologic models outside of the high-resolution DEM coverage, which can still account for terrain variation in the Prairies.  相似文献   
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