Simulation of leaf area index and biomass at landscape scale

The method for simulating the temporal and spatial distribution patterns of leaf area index (LAI) and biomass at landscape scale using remote sensing images and surface data was discussed in this paper. The procedure was: (1) annual maximum normalized difference vegetation index (NDVI) over the landscape was calculated from TM images; (2) the relationship model between NDVI and LAI was built and annual maximum LAI over the landscape was simulated; (3) the relationship models between LAI and biomass were built and annual branch, stem, root and maximum leaf biomass over the landscape were simulated; (4) spatial distribution patterns of leaf biomass and LAI in different periods all the year round were obtained. The simulation was based on spatial analysis module GRID in ArcInfo software. The method is also a kind of scaling method from patch scale to landscape scale. A case study of Changbai Mountain Nature Reserve was dissertated. Analysis and primary validation were carried out to the simulated LAI and biomass for the major vegetation types in the Changbai Mountain in 1995.     

Use of principal components of UAV-acquired narrow-band multispectral imagery to map the diverse low stature vegetation fAPAR

The fraction of absorbed photosynthetically active radiation (fAPAR) is an important plant physiological index that is used to assess the ability of vegetation to absorb PAR, which is utilized to sequester carbon in the atmosphere. This index is also important for monitoring plant health and productivity, which has been widely used to monitor low stature crops and is a crucial metric for food security assessment. The fAPAR has been commonly correlated with a greenness index derived from spaceborne optical imagery, but the relatively coarse spatial or temporal resolution may prohibit its application on complex land surfaces. In addition, the relationships between fAPAR and remotely sensed greenness data may be influenced by the heterogeneity of canopies. Multispectral and hyperspectral unmanned aerial vehicle (UAV) imaging systems, conversely, can provide several spectral bands at sub-meter resolutions, permitting precise estimation of fAPAR using chemometrics. However, the data pre-processing procedures are cumbersome, which makes large-scale mapping challenging. In this study, we applied a set of well-verified image processing protocols and a chemometric model to a lightweight, frame-based and narrow-band (10 nm) UAV imaging system to estimate the fAPAR over a relatively large cultivated land area with a variety of low stature vegetation of tropical crops along with native and non-native grasses. A principal component regression was applied to 12 bands of spectral reflectance data to minimize the collinearity issue and compress the data variation. Stepwise regression was employed to reduce the data dimensionality, and the first, third and fifth components were selected to estimate the fAPAR. Our results indicate that 77% of the fAPAR variation was explained by the model. All bands that are sensitive to foliar pigment concentrations, canopy structure and/or leaf water content may contribute to the estimation, especially those located close to (720 nm) or within (750 nm and 780 nm) the near-infrared spectral region. This study demonstrates that this narrow-band frame-based UAV system would be useful for vegetation monitoring. With proper pre-flight planning and hardware improvement, the mapping of a narrow-band multispectral UAV system could be comparable to that of a manned aircraft system.     

船舶减纵摇方法研究

针对现有减小船舶纵摇的方法和装置进行总结和分析,并在此基础之上详细介绍一种新型十字型的被动式抗纵摇舵.通过对比分析,抗纵摇舵对于船舶具有明显地减小纵摇的减摇效果.     

小偃54小麦的抗逆性表现

小偃54是一个具有杂种优势、品质优良的小麦品种。通过在豫南试种、示范及对其生理机制探讨发现：它有发达的根系，可在逆境中充分吸收营养、水分等，以满足自身营养需要和加大蒸发量，以调解渍水及旱灾条件下的生理功能和提高抵御病、旱、涝、倒伏等自然灾害的抗逆能力；具有旗叶中等、旗叶上挺的特征，因此通风透光较好，冠层温度较低，具有较高的抗干热风能力。此外，它是蛋白质含量很高的优质小麦，又是氮高效基因型，既能在逆境胁迫下充分吸收营养，又能用自身能量维护渍水条件下的生存需要，同时它又是属于高效低营养基因型。尤其适合在低磷协迫下利用其自身遗传生理特性去活化吸收营养，调解抗逆能力，获得较高产量。     

基于遥感和地面数据的景观尺度叶面积指数和生物量的模拟

The method for simulating the temporal and spatial distribution patterns of leaf area index (LAI) and biomass at landscape scale using remote sensing images and surface data was discussed in this paper,The procedure was:(1) annual maximum normalized difference vegetation index (NDVI) over the landscape was calculated from TM images;(2) the relationship model between NDVI and LAI was built and annual maximum LAI over the landscape was simulated;(3) the relationship models between LAI and biomass were built and annual branch ,stem ,root and maximum leaf biomass over the landscape were simulated;(4) spatial distribution patterns of leaf biomass and LAI in different periods all the year round were obtained.The simulation was based on spatial analysis module GRID in ArcoInfo software ,The method is laso a kind of scaling method from patch scale to landscape scale ,A case study of Changbai Mountain Nature Reserve was dissertated ,Aalysis and primary validation were carried out to the simulated LAI and biomass for the major vegetation types in the Changbai Mountain in 1995.     

华北地台早古生代竹叶状灰岩岩石特征及成因研究进展

砾屑灰岩在华北地台寒武系-奥陶系广泛发育,竹叶状灰岩只是其中一种,且所指范围界限模糊,常与其他类型的砾屑灰岩伴生在一起。古代陆表海提供了砾屑灰岩广泛发育的环境基础。潮坪和潮下开阔海是陆表海广泛发育的基本地貌单元,也是砾屑灰岩形成的重要场所。古板块运动表明,寒武纪华北地台处于低纬度地区,符合古风暴频发的要求。风暴及潮汐流是砾屑灰岩形成的主要动力。另外,成岩过程中的压实和固结脱水也是板条状砾屑的重要成因。条带状薄层灰泥石灰岩与泥岩及泥质灰岩的频繁互层是发生破碎并形成砾屑的物质基础。华北地台砾屑灰岩具有多种成因,可以按照砾屑的颜色特征、形态及磨圆程度、砾屑灰岩的支撑结构、充填物的类型等进行区分并进行成因分析。     

植物叶蜡单体氢同位素重建非洲和东亚大陆古降水:亮点与难点

植物利用周围环境中的水分进行光合作用合成有机质, 其叶蜡氢同位素记录了源水中的氢同位素组成, 被认为是重建古水循环的替代性指标。然而从源水(降水)到合成叶蜡脂类化合物, 降水中的氢同位素会发生多步分馏作用。本文综述了对氢同位素分馏造成影响的因素及其校正方法, 通过有效的数据处理, 叶蜡氢同位素可以比较直接地反映降水的氢同位素组成。由于在热带地区降水氢同位素受"雨量效应"影响较大, 所以可以较好地反映降水量变化, 在非洲大陆常被用于重建水循环和气候变化; 在东亚大陆,"雨量效应"不再那么显著, 水汽的来源可能在影响降水氢同位素组成的过程中也起到了重要作用。     

甘肃窑街中侏罗世化石角质层有机质及其碳同位素组成与古环境的关系

通过对甘肃窑街中侏罗统窑街组化石银杏以及现代银杏角质层有机质组分和碳同位素组成分析,表明银杏角质层有较强的抗风化能力,化石和现代银杏角质层有机质烷烃和甾萜类化合物组成十分相似。可以通过角质层的碳同位素组成等参数进行古环境重建,结果表明中侏罗世早期古环境较为温湿,到了中期后古气候逐渐变得干旱少雨,后期降雨量又逐渐增加,温度升高,植被发育。     

用LAI监测植被信息分析飞蝗生境

东亚飞蝗自20世纪80年代以来在我国再度猖獗危害。本文选择国家一类蝗区河北省黄骅市为实验区,用植被冠层孔隙度反演了该地区不同植被的LAI。从光学模型建立机理及数量分析的角度,分析和对比了四种由植被冠层孔隙度反演LAI的算法。结果表明,在四种估算方法中LAI-2000算法最适用于研究区植被LAI的估算。为了验证分析结果,用实测的植被盖度与四种算法反演的LAI进行了拟合。发现LAI与植被盖度之间呈明显的正相关关系,且LAI-2000算法最能反映研究区的植被特征。在此基础上,建立了LAI与飞蝗发生面积的关系模型,发现两者之间呈负线性相关,即随着LAI的减小,飞蝗的发生面积呈线性增大。研究结果为实时、快速、大面积监测蝗虫种群动态奠定了基础,并为合理、经济地防治蝗灾提供了科学依据。     

作物LAI的遥感尺度效应与误差分析

以黑河中游盈科绿洲为研究区, 利用Hyperion高光谱数据, 采用双层冠层反射率模型(ACRM)迭代运算反演LAI; 通过LAI的均值化(LAImean)以及Hyperion数据反射率线性累加反演LAI(LAIp), 定量分析LAI反演的尺度效应; 从模型的非线性和地表景观结构的空间异质性2个方面分析引起反演误差的原因, 并在LAI-NDVI回归方程的基础上利用泰勒展开的方法对低分辨率数据反演结果进行了误差纠正。结果表明, 地表景观结构的空间异质性是造成多尺度LAI反演误差的关键因素, 通过泰勒展开式能很好地实现大尺度数据LAI反演结果的误差纠正。