Reactive glass and vegetation patterns

The formation of vegetation patterns in the arid and the semiarid climatic zones is studied. Threshold for the biomass of the perennial flora is shown to be a relevant factor, leading to a frozen disordered pattern in the arid zone. In this "glassy" state, vegetation appears as singular plant spots separated by irregular distances, and an indirect repulsive interaction among shrubs is induced by the competition for water. At higher precipitation rates, the diminishing of hydrological losses in the presence of flora becomes important and yields spatial attraction and clustering of biomass. Turing patterns with characteristic length scale emerge from the disordered structure due to this positive-feedback instability.     

Landsat8光谱衍生数据分类体系下的牧草生物量反演

牧草生物量的估算对于草地资源合理利用和载畜平衡监测具有重要的意义,是评价草地生态系统与草地资源可持续发展的关键指标。基于Landsat遥感技术快速、无损的大面积植被生物量估算研究已广泛应用,当前大多基于单一变量或几个常用植被指数构建反演模型,这些指数往往不能从多方面反映植被理化特征。归纳了不同Landsat8光谱衍生数据所反映的植被理化特征及它们间的关联方式,构建了Landsat8光谱衍生数据的分类体系;在此基础上提出了一种基于随机梯度Boosting(SGB)算法的多变量、非线性生物量估算模型,探讨不同类型光谱衍生数据组合对于牧草生物量反演结果的影响。以青海省海晏县为研究区进行方案可行性探讨。结果表明常用的Landsat8光谱衍生数据主要从植被的绿度、黄度、盖度、水分含量、纹理特征以及通过消除大气干扰和土壤背景干扰等7个方面反映植被的理化特征(7个小类),可归纳为直接因子(绿度、黄度、盖度、水分含量)、间接因子(消除大气干扰和消除土壤背景干扰)和空间因子(纹理特征)3大类型。在牧草生物量反演中,这些光谱衍生数据类型间具有较好的互补性,单一的直接因子模型估算结果最差,引入间接因子和空间因子均能提高模型的估算结果,而由直接因子(GNDVI, TCW, NDTI, NDSVI, TCD)、间接因子(SAVI, VARI)和空间因子(MeanB3, MeanB6, HomⅡ, DisB5)共同构建的SGB模型估算精度最优,R2达到了0.88;RMSE为141.00 g·m-2。与5种常用的生物量估算模型结果对比,该方法具有明显的优势。较单变量模型,R2提高了42%~60%,RMSE降低47%以上,R■提高了31%~53%, RMSEcv降低29%;较多变量模型,R2提高了29%~42%, RMSE降低35%以上,R■提高了2%~18%, RMSEcv降低2%以上。此外,所提出方法在消除反演模型过饱和方面也具一定成效。综上,利用Landsat8数据从反映植被不同理化特征角度构建反演模型实现了牧草生物量的精准估算,对于后期牧草生长状况实时监测以及草地资源可持续利用与管理具有重要的指导意义。研究结果还可以为今后进行大面积区域草地动态监测以及其他农业领域的研究提供参考和借鉴。     

The impact of competition and litter accumulation on germination success in a model of annual plants

A new model of one type of annual plant dynamics is proposed and discussed. The model is based on individual agents Monte Carlo simulations. We take into account, the plant requirements for external resources (sunshine, moisture etc.), competition among plants and the influence of accumulated dead biomass on the plant germination and seed production. We show that the density of plants could have oscillatory character, with periods depending on the rate of biomass reduction. Investigations on the temporal changes in the spatial distribution of plants show some clustering and moreover persistence of patterns during the oscillations. The average number of seeds produced by a plant in a year versus density of plants has a power-law type character. The obtained results are compared with field data and findings in other theoretical models. Agreement with experimental data is found, at least on a qualitative level. We have been also able to add new arguments in the long debate about the existence or not of oscillations in plant dynamics.     

基于天宫一号高光谱数据的荒漠化地区稀疏植被参量估测

为了精准地估测荒漠化地区的稀疏植被信息,选取内蒙古苏尼特右旗为研究区,以天宫一号高光谱数据为数据源,结合野外实地调查数据,通过归一化植被指数(normalized difference vegetation index, NDVI)和土壤调节植被指数(soil adjusted vegetation index, SAVI)对研究区内的植被覆盖度和生物量进行反演,并对比两种植被指数的优劣。首先,分析了每种波段组合下的植被指数与覆盖度、生物量的相关性,确定了最大相关的波段组合。覆盖度和生物量与NDVI的最大相关系数可达0.7左右,而与SAVI的最大相关系数可达0.8左右。NDVI的最佳波段组合的红光波段中心波长为630 nm,近红外波段的中心波长为910 nm,而SAVI的组合为620和920 nm。其次,分别构建了两种植被指数与覆盖度、生物量之间的线性回归模型,所建模型的R2均能达到0.5以上。SAVI所建模型R2要比NDVI略高,其中植被覆盖度的反演模型R2高达0.59。经留一交叉验证,SAVI所建模型的均方根误差RMSE也比基于NDVI的模型小。结果表明：天宫一号高光谱数据丰富的光谱信息能有效地反映地表植被的真实情况,并且SAVI比NDVI更能较为精准地估测荒漠化地区的稀疏植被信息。     

Ecosystem engineers: from pattern formation to habitat creation

Habitat and species richness in drylands are affected by the dynamics of a few key species, termed "ecosystem engineers." These species modulate the landscape and redistribute the water resources so as to allow the introduction of other species. A mathematical model is developed for a pair of ecosystem engineers commonly found in drylands: plants forming vegetation patterns and cyanobacteria forming soil crusts. The model highlights conditions for habitat creation and for high habitat richness, and suggests a novel mechanism for species loss events as a result of environmental changes.     

Formation of Vegetation Patterns and Hysteresis Phenomena in Arid and Semiarid Zones

Considering the spatial effect of the complicated interactions between plant and resource （soil water） and the stochastic character of the complicated ecological processes in an ecosystem, we introduce a lattice gas model to investigate the vegetation pattern formation in the arid and the semiarid ecosystems with Monte Carlo sim- ulations. With consistency of some previous mean-field models, the model reproduces a wide range of patterns observed in the arid and the semiarid regions. The sequences of vegetation states are also investigated with scanning three parameters, i.e., the precipitation and the plant growth rate, and then the parameter ranges are identified where a hysteresis loop appears and two different stable states coexist. The simulation results denote that the complex structures occur only when the precipitation parameter decreases. Moreover, based on the model, it is found that an increase of the competition of the plant for the resource along the slope direction results in the regular stripes parallel to the hill＇s contours. The model provides an interesting mechanism to understand the formation of the other regular vegetation stripe in a limited resource condition.     

Biomass estimation of desert steppe based on spectral indices along a precipitation gradient

Abstract

Accurate estimation of grassland biomass in desert steppe is crucial for various studies such as grassland dynamic monitoring, scientific management, and environmental degradation. Observational tests were conducted in the Ordos desert steppe in July and August from 2014 to 2016 to measure the grassland biomass and grassland canopy spectral data along a precipitation gradient, to analyze the spectral reflectance characteristics and the correlation between different spectral indices and grassland biomass in the range of 350–1830?nm, and to establish and verify a model for estimating grassland biomass of desert steppe. The results showed that the spectral reflectance of the Ordos desert steppe is similar to the spectral characteristics of typical green vegetation. The spectral reflectance values of control and of lightly, medium-, and heavily degraded plots successively increased in the visible light band at 350–696?nm and decreased in the near-infrared band at 792–1349?nm. The sensitive band of the normalized difference spectrum indices after optimization was 705 and 710. The coefficient of determination of normalized difference spectral indices (705 and 710) and grassland biomass was R²?=?0.735. These values were significantly correlated at the p?R² values of the fitted power function model and the verification power function model were 0.764 and 0.746, respectively. The root mean square error was 41.59?g/m². The relative error was 28.37%, and the constructed power function model was the best model. Therefore, the optimized spectral indices can be used to effectively estimate the grassland biomass of desert steppe.     

基于多源数据的新疆棉田螨害大范围监测研究

针对新疆棉田传统螨害监测方法耗时低效的问题,提出了一种基于冠层高光谱、近地多光谱、环境数据与地面调查相结合的多源数据棉田螨害大范围监测方法。首先,分别采集地面尺度的棉花冠层350~2 500 nm高光谱遥感数据和不同时期低空尺度的棉田无人机多光谱遥感影像数据,通过分析高光谱的原始光谱和一阶微分光谱特征,提取出了4个螨害敏感波段,分别为：绿光波段553 nm附近、红光波段680 nm附近、红边波段680~750 nm、近红外波段760~1 350 nm,这几个波段同时包含在无人机搭载的多光谱传感器波段范围内,验证了低空尺度下无人机遥感螨害监测的可行性。其次,初选23种植被指数和13种田间环境数据,结合地面调查的螨害发生情况做相关性分析。其中,SAVI、OSAVI、TVI、NDGI、平均湿度、温湿系数和10 cm土壤平均温度均与螨害发生达到极显著相关水平（sig≤0.01）;RDVI、RVI、MSR、最高温度、平均温度、积温、10 cm土壤最高温度和10 cm土壤平均湿度均与螨害发生达到显著相关水平（sig≤0.05）。选取sig值在0.05以下的15种特征值,分别建立基于单一环境数据、单一植被指数、环境数据与植被指数相结合的3种支持向量机（SVM）棉田螨害发生监测模型。最后,根据评价效果最优的监测模型,绘制不同时期的螨害遥感监测空间分布图,通过统计分布图中螨害和健康像元数计算出螨害面积占比,将螨害占比与同时期田间环境数据进行相关性分析,筛选出显著特征值,再通过多元逐步回归分析法确定出与螨害面积值关系最密切的环境因子,建立棉田螨害面积预测模型。结果表明：基于单一环境数据的棉田螨害发生监测模型准确率为62.22%,基于单一植被指数的棉田螨害发生监测模型准确率为75.56%,基于环境数据与植被指数相结合的棉田螨害发生监测模型效果最优,准确率为80%。螨害面积预测模型的决定系数R2=0.848,模型拟合度较好。本研究基于多源数据建立的棉田螨害发生监测模型和螨害面积预测模型,可以为新疆地区棉田螨害的大范围监测和趋势预警提供参考。     

作物覆盖条件下土壤中水热分布的稳态数值比较

本文应用非饱和多孔介质中传热传质的数学模型,考虑到作物根系和冠层的影响,对稳态情况下圆柱形士壤床中的水热分布进行了数值计算模拟。在不同环境条件下对土壤中的水热分布也进行了模拟计算。同时,在相同环境条件下对有作物覆盖的土壤床和无作物覆盖的土壤床中的水热分布也进行了模拟比较。文中数值模拟的结果较好地反映了实际情况。     

遥感光谱信息提取不同覆盖下植被水分信号的研究进展

综述了基于遥感光谱信息的植被水分信号提取的研究进展,包括直接利用光谱反射率反演植被水分信息到建立植被水分指数(WI),再发展至利用辐射传输模型来获取植被冠层水分信息。着重评述了针对低植被覆盖条件下的提取其冠层水分信息的方法,包括利用冠层生理参数估算植被水分信号;基于去除土壤背景影响的光谱植被水分指数或辐射传输模型估算植被水分信息,以及基于多角度的星-地观测提取稀疏条件下的植被水分信息。最后讨论了针对提取低覆盖植被冠层水分信息方法的可能发展趋势。     

Cogeneration: One way to use biomass efficiently

Cogeneration in district heating systems is the most energy-efficient way to convert biomass into heat and electricity with current or nearly commercial technologies. Methanol produced from biomass and used in vehicles instead of petrol or diesel could reduce carbon dioxide emissions nearly as much per unit of biomass as if the biomass were used to replace natural gas for cogeneration, but at some higher cost per unit of carbon dioxide reduction. The most energy-efficient way to use biomass for cogeneration appears to be combined cycle technology, and the world's first demonstration plant is now being built. Potentially, this technology can be used for electricity production in Swedish district heating systems to provide nearly 20% of current Swedish electricity production, while simultaneously reducing carbon dioxide emissions from the district heating systems by some 55%. The heat costs from cogeneration with biomass are higher than the heat costs from fossil fuel plants at current fuel prices. Biomass can only compete with fossil fuels if other advantages, for example a lower environmental impact, are considered.     

植物蒸腾作用对红外辐射特征的影响研究

研究植被的红外辐射特征是开展地面军事目标红外伪装与隐身的基础,模拟植被红外特性的形成机理可实现目标与背景的精确融合。叶片蒸腾是植被特有的生理机制,是影响植被红外辐射特征的主要因素之一。通过建立植物叶片的能量平衡物理模型,分析计算出植物蒸腾特性对叶面温度的影响。应用气孔计、红外热像仪实测了樟树、冬青等典型植物叶片的蒸腾作用、叶面温度、红外辐射特征的日周期变化,通过与干枯叶片的对比表明,植物蒸腾作用能够有效调节叶片的能量平衡,控制叶面温度处于合理的范围内,抑制叶片红外辐射特征的深幅变化。     

针对水稻植株三维叶绿素(SPAD)信息获取的最优波段选择问题研究

实时准确地获取作物叶绿素含量的三维空间分布信息,是作物营养、栽培和育种等科学研究和生产领域密切关注的问题。该研究以水稻植株为研究对象,采用改造后的普通单反相机加载近红外滤光片的方法,多角度获取水稻植株的多光谱图像。基于不同波段不同通道的组合图像计算多种植被指数,将其结果与对应的实测SPAD值之间建立水稻植株叶绿素(SPAD)预测模型,并筛选出最优预测模型。研究结果表明,近红外760 nm波段的R通道与可见光G通道构建的GNDVI植被指数,与实测SPAD值建立的二次函数预测模型能够很好地反演水稻植株叶绿素(SPAD)含量,其中,R2=0.758, RMSE=1.532。在此基础上,利用多角度成像三维建模方法建立具备纹理信息的水稻三维模型,将最优预测模型应用于水稻综合纹理图,得到水稻叶绿素含量三维空间分布信息, 从而实现水稻生长情况以及叶绿素养分分布状况的快速无损检测。     

The calculated performance of forest structure and biomass estimates from interferometric radar

Vertical structure and biomass are key characteristics of the forest random medium. This paper calculates the power and interferometric synthetic aperture radar (InSAR) sensitivity to tree height and vegetation density as it manifests in extinction, using a homogeneous, random-volume model of the forest medium, and accounting for speckle and thermal noise. Tree height and extinction are both related to biomass within the context of this simple model. Signal and noise calculations show that InSAR coherence and phase are more sensitive than radar power to structure and biomass to 10% variations in structure parameters over a wide range of medium to high density forests. For example, for extinctions of 0.2 db m^-1 and other parameters as noted in the text, the sensitivity of InSAR coherence to 10% changes in tree height exceeds observation errors for trees shorter than about 37 m, as opposed to 14 m for radar power. InSAR phase sensitivity to 10% structural and associated biomass changes exceeds observation errors for all tree heights. Only for the very lowest densities, for extinctions less than 0.15 db m^-1, does radar power sensitivity to density exceed that of InSAR; even at low densities, InSAR sensitivity to tree height outperforms that of radar power in these calculations.     

从高光谱卫星数据中提取植被覆盖区铜污染信息

重金属矿山开采活动对生态环境造成了复杂的影响,而植被的生长状况是矿山周围生态环境变化的重要指示因子。常规的对植被中重金属元素富集程度的估计方法往往依赖于大量的野外调查数据以及实验室化学分析方法,需要耗费大量的物力与时间。而通过光谱分析方法能够非接触地获取植被中的重金属含量信息。然而,从高光谱遥感卫星数据中反演植被重金属含量信息仍然是个比较困难的工作。从众多的卫星数据波段中找到对特定重金属元素敏感的波段是植被重金属含量提取的关键。该工作探索了一种基于统计分析的方法从国产卫星（HJ-1）高光谱数据中实现特征波段发现与重金属含量提取,该方法基于野外实测数据集与环境星高光谱遥感图像,选取叶片铜离子含量作为重金属铜污染程度的指示因子,利用44组德兴铜矿植被覆盖区的叶片铜离子含量数据与逐步多元线性回归与交叉验证方法,实现了环境星高光谱反射光谱与叶片铜离子含量的统计建模。将统计模型应用于德兴铜矿研究区,生成了德兴铜矿植被覆盖区叶片铜离子含量分布图。结果表明,该工作建立的重金属含量估计模型具有明显的统计学意义,叶片铜离子含量对516 nm附近的冠层反射光谱最为敏感。矿区铜含量制图结果表明,德兴铜矿植被覆盖区铜离子含量的分布范围介于0～130 mg·kg-1之间,铜离子含量在德兴市东南角和铜矿周围的植被覆盖区域含量最高,均介于80～100 mg·kg-1之间。制图结果可以为德兴铜矿重金属铜污染的预防与治理提供基础数据支持。     

基于多角度偏振载荷数据的中国典型地物偏振特性研究

相对于传统的光学遥感, 多角度偏振遥感不仅可以获取辐射强度信息, 而且可以获取偏振强度信息. 基于多角度偏振卫星载荷观测的中国典型地物的偏振反射率数据, 获取了地表偏振双向反射模型——Nadal模型的中国区域模型参数值. 在此基础上, 基于修正的Nadal模型研究了中国区域森林、草地、沙漠三种典型地物的多角度偏振特性. 研究表明: 1)各地物的偏振反射率均随着散射角的增大而减小, 随着太阳天顶角和卫星观测天顶角的增大而增大; 2)森林、草地和沙漠三种典型地表偏振反射率存在明显差别, 森林的偏振反射率最低, 草地的偏振反射率次之, 沙漠的偏振反射率大约为森林的两倍; 3)不同地物之间的偏振反射率差值均随着卫星观测天顶角和太阳天顶角的增大而增大. 研究结果可为基于多角度偏振遥感数据探测地表偏振特性和反演气溶胶参数提供先验知识.     

可见光光谱的冬小麦苗期地上生物量估算

地上生物量是表征冬小麦苗期长势的重要参数之一,对于监测冬小麦苗期长势,预测产量具有重要的实际意义。目前,通过计算光谱指数进行生物量估算是冬小麦苗期地上生物量无损测量的主要方法,但该方法需要一定的平台支撑,在便捷性方面存在一定的不足。为此,利用可见光图像数据获取方便、准确率高的特点,基于冬小麦苗期冠层可见光图像数据开展冬小麦苗期地上生物量估算研究。采用数码相机,采集冬小麦苗期冠层可见光图像并利用Canopeo进行冬小麦冠层与背景的分割。在获取冠层分割图像后,提取了CC（canopy cover）、ExG（excessg reen）、ExR（excess red）、ExGR（ExG-ExR）、NGRDI（normalized green-red difference index）、GLI（green leaf index）、RGRI（red-green ratio index）和RGBVI（RGB vegetation index）共8个可见光图像特征。利用相关性分析进行特征优选,选择与冬小麦苗期地上生物量实测数据相关性较高的图像特征构建估算模型。利用优选的图像特征,分别构建偏最小二乘回归（PLSR）、BP神经网络（BPNN）、支持向量机回归（SVR）和随机森林（RF）模型,开展冬小麦苗期地上生物量估算研究,并定量分析特征数量和播种密度对估算模型准确率的影响。结果表明,ExR,GLI和RGBVI与生物量实测数据相关性较低,因此,将这3个特征剔除。CC,ExG,ExGR,NGRDI和RGRI与生物量实测数据的相关性较高,其中CC,ExG和ExGR与生物量实测数据呈正相关,而NGRDI和RGRI与生物量实测数据呈负相关。利用优选的图像特征构建估算模型,研究结果表明,基于优选的5个图像特征,PLSR的估算准确率最高,模型R2为0.801 5,RMSE为0.0788 kg·m-2,表明PLSR能够实现冬小麦苗期地上生物量的准确估算。特征数量是影响估算模型准确率的因素之一,随着特征数量的减少,模型估算的准确率逐步下降。利用不同播种密度数据集对估算模型进行测试,结果表明,PLSR在不同的播种密度数据集上均取得了最高的估算准确率,模型R2分别为0.897,0.827 9和0.788 6,RMSE分别为0.062,0.072和0.079 1 kg·m-2,表明PLSR估算的冬小麦苗期地上生物量数据与实测生物量数据之间具有良好的相关关系。随着播种密度的增加,所有估算模型的准确率均出现下降,而PLSR的准确率下降程度最小。由此可见,基于可见光图像数据,能够实现冬小麦苗期地上生物量的准确估算,为冬小麦苗期田间管理提供参考。     

无人机多光谱影像的马铃薯地上生物量估算

地上生物量（AGB）是评估作物生长发育和指导田间农业生产管理的重要指标。因此,高效精准地获取作物AGB信息,可以及时准确地估算产量,对于保障粮食供应和贸易提供有力依据。传统获取AGB的方法是采用破坏性取样法,这使得大面积、长期的测量变为困难。然而,随着精准农业的快速发展,无人机遥感技术被认为是估算大面积作物AGB最有效的技术方式。通过无人机平台搭载多光谱传感器获取马铃薯块茎形成期、块茎增长期和淀粉积累期的多光谱影像,地面实测株高和AGB以及地面控制点（GCP）的空间位置信息。首先,基于SFM（structure from motion,SFM）技术利用无人机影像数据结合GCP的三维坐标生成试验田的DSM（digital surface model,DSM）,通过DSM提取出马铃薯各生育期的株高（Hdsm）;然后,选取原始4个单波段植被指数、9个多波段组合的植被指数、红边波段的高频信息（HFI）和提取的Hdsm分别与AGB作相关性分析;最后基于单波段植被指数（x₁）、多波段组合的植被指数（x₂）、植被指数结合Hdsm（x₃）、植被指数结合HFI（x₄）以及植被指数融合HFI和Hdsm（x₅）为模型输入参数,采用偏最小二乘回归（PLSR）和岭回归（RR）估算各生育期的AGB。结果表明：（1）提取的Hdsm和实测株高拟合的R2为0.87,NRMSE为14.34%;（2）各模型参数都与AGB达到极显著水平,相关性均从块茎形成期到淀粉积累期先升高后降低;（3）各生育期以5种变量使用同种方法估算马铃薯AGB的效果,均从块茎形成期到淀粉积累期先好后变差,其估算精度由高到低依次为x₅>x₄>x₃>x₂>x₁;（4）各生育期使用PLSR以不同变量估算AGB的效果要优于RR方法,其中在块茎增长期基于x₅变量估算马铃薯AGB效果最佳,R2为0.73,NRMSE为15.22%。因此,选取多光谱植被指数结合红边波段的高频信息和Hdsm并使用PLSR方法可以明显提高AGB的估算精度,这为大面积马铃薯作物AGB的监测提供了新的技术支撑。     

煤炭矿区植被冠层光谱土地复垦敏感性分析

煤矿区土地复垦及复垦监测工作,对于我国土地利用和生态环境治理具有重要意义。微生物复垦技术能够促进植物吸收利用矿质养分和水分,增强土壤肥力,对矿区生态恢复具有显著作用。监测和评价土地复垦效应对植物生长影响的传统方法,通常采用野外采集植物和土壤样本并进行室内分析,但这些方法不仅破坏植物根系原状土壤,造成植株损伤,而且耗费人力、物力,时效性差。高光谱遥感技术具有数据获取速度快、信息量大、精度高且无须离体破坏植株等优点,对于土地复垦监测有非常大的潜力。目前,土地复垦效应遥感监测相关研究仍以观测盆栽大豆、玉米等作物的叶片光谱分析为主。实际上,卫星遥感数据观测到的是冠层光谱,并非叶片光谱,但目前还没有通过植被冠层光谱对矿区土地复垦进行监测的研究成果出现。植被冠层光谱不仅受到叶片光谱的影响,还受到植株长势、下垫面等其他因素的影响,光谱特征变化更为复杂。矿区植被冠层光谱特征对于土地复垦效应的敏感度分析,是对矿区植被理化参量进行定量反演的基础,也是限制高光谱技术应用于大面积土地复垦监测的主要瓶颈。于煤炭矿区土地复垦实验基地开展野外冠层光谱观测实验,获取了接菌组和对照组野外植株冠层光谱数据,并从光谱波形变化和光谱特征参量变化两方面综合分析了植被冠层光谱对土地复垦的敏感性。冠层光谱波形方面,分别采用标准差和光谱敏感度作为组内和组间光谱波形差异的有效指标;冠层光谱特征参量方面,选取了植被红边、黄边、蓝边、绿峰、红谷等典型光谱特征,计算获取其位置、斜率、面积等特征参量,并通过描述性统计和单因素方差分析研究了这些冠层光谱特征参量对土地复垦效应的敏感性,挑选出矿区土地复垦监测的有效特征参量。研究表明,接菌组和对照组冠层光谱的主要波形变化趋势一致,但接菌组植株的生长状况更稳定,不同植株之间差异较小,且绿峰和红谷两个特征更突出。这说明土地复垦能够减少植株间冠层光谱差异,增强植被典型光谱特征,而绿峰和红谷对土地复垦有较高的光谱敏感度。光谱特征参量方面,绿峰、红谷、红边波长在土地复垦作用下显著向长波方向移动,而此前叶片光谱研究中对土地复垦较敏感的红边、蓝边斜率变化并不显著。这说明,野外植被冠层光谱分析结果与实验室植被叶片光谱分析的结果并不完全一致,这可能和植被类型、生长周期、土壤背景光谱干扰等因素相关。在采用卫星或航拍遥感数据进行矿区植被环境监测时,所获取的都是植被冠层光谱,因此本研究所得到的结论具有更强的参考意义和实际应用价值。     

Simulation of the destruction of a woodland massif by the shock wave generated by the impact of a large cosmic body

The interaction of shock waves with woodland massifs with consideration given to vegetation destruction is examined. The results of numerical simulations of the propagation of a perturbation through a vegetation massif based on solving the Euler equations for two-dimensional and axisymmetric cases are presented. This approach was used by the present author in simulating the propagation of wave fronts through woodland massifs without regard for forest stand destruction. The effect of vegetation is reproduced by introducing bulk forces in the volume occupied by forest. An initial perturbation of explosion-in-flight type was specified in the form of an increased-pressure region located at various heights from the ground surface. Simple threshold models are used to examine the effect of the dynamic pressure on vegetation destruction. A refined model was developed to investigate the change in the configuration of woodland massifs with consideration given to vegetation fall and the effect of this process on the rate of perturbation dissipation. The system of equations was solved by the Godunov method implemented using parallel programming. Numerical experiments were conducted with the use of two types of models of forest stand destruction, with various threshold values of the destruction factor, various initial perturbation intensities, and various heights above the vegetation massif. The effects arising during the interaction of a high-intensity perturbation with a woodland massif were identified. An analysis of the results showed that the destruction of vegetation occurs during its interaction with the fronts of the incident and reflected shock wave and with the jet core of the perturbation. In some cases, the model taking into account the accumulation of fallen vegetation predicts situations where destruction will occur only in the upper part of the forest stand, without touching the canopy. This effect can explain the existence of such regions in the area of the Tunguska event. It was also demonstrated that estimates of the sizes of the destruction zones obtained with the use of the models taking into account the influence of vegetation on the perturbation and destructibility differ substantially from those obtained within the framework of the models without regard for vegetation resistance. The highest range of perturbation dissipation was predicted by the models simulating the formation of obstructions.