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。     

大米草室内叶片光谱特征参数与叶绿素浓度关系研究

本文通过分析大米草叶片反射光谱特征,并提取红边位置、红边斜率和红边面积三个红边参数以及叶面叶绿素指数(LCI)、水分指数(WI)、三角植被指数(TVI)、结构相关色素指数(SIPI)四个高光谱植被指数,利用线性、对数、倒数、二次函数和三次函数曲线模拟算法得到大米草叶片叶绿素a浓度的高光谱估算模型。研究结果表明:叶绿素a浓度与红边斜率和红边面积在0.01水平上显著负相关,与LCI、WI和TVI在0.01水平上显著正相关。基于红边斜率、红边面积、TVI三个参数,选用倒数法构建叶绿素a浓度的估算模型精度明显高于其他算法。基于LCI和WI参数,应用三次函数法构建的叶绿素a浓度的高光谱检测模型精度明显高于其他算法。比较R2和模型估算误差,利用WI水分指数应用三次函数构建叶绿素a浓度的高光谱检测模型精度在所有模型中最高。因此,利用叶片光谱技术可以较高精度地估算叶绿素a浓度。     

银杏叶有效成分提取工艺研究

用正交实验探讨了银杏叶有效成分的最佳提取工艺。研究结果表明,在乙醇体积浓度为60%,回流温度为80℃,提取时间为3h的条件下,银杏叶提取效果最好;并分别用Al3 和红外光谱法对提取物有效成分进行了定性检测。该实验操作简单,重复性好,可行性强,为后续精制工艺提供前提条件。     

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。     

黑河中游沙枣树干液流的动态变化及其与林木个体生长的关系

利用热脉冲树干液流仪, 在生长季节对黑河中游防风固沙树种沙枣树干液流速率进行了连续观测, 结果表明: 沙枣树干液流速率没有明显的昼夜变化规律, 树干液流日平均值在(1.41±0.52)~(2.00±0.66)g·cm^-2·h^-1之间; 树干液流速率8月份最高, 7月份次之, 6月与9月份基本一致。不同的单株在相同月份平均树干液流速率存在差异。树干液流与树木的胸径、胸径的平方与树高之积呈复合指数函数关系, 与边材面积呈线性关系, 与叶面积指数呈现三次幂函数关系。     

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.     

黑河中游二白杨叶面积指数动态变化及其与耗水量的关系

在黑河中游,利用直接法和热脉冲树干液流仪分别监测了二白杨生长季节的叶面积指数和耗水量动态变化,研究了二白杨叶面积指数动态变化规律及其与耗水量的关系.结果表明:在生长季节,二白杨叶面积指数的增长符合Logistic模型;在树冠结构垂直分布上,1 000~1 400 cm之间二白杨叶面积指数占全树叶面积指数的75.5%;二白杨个体间的叶面积指数与胸径平方和树高乘积呈指数函数关系.当单株叶面积指数从0.44增大到4.94时,二白杨耗水量从42.95 L·d^-1增加到140.30 L·d^-1.单株二白杨耗水量与叶面积指数之间呈现线性关系.     

极端干旱区胡杨水势及影响因子研究

依据2002年4月至2003年9月在极端干旱区额济纳旗的观测资料,对胡杨叶水势的日、季变化规律及影响因子进行了分析研究。试验结果表明:胡杨叶水势日变化均值为(-2.86±0.75)MPa,季变化均值为(-2.72±0.14)MPa。叶水势日、季节变化曲线呈单峰型,这种变化规律是胡杨适应该地区生境的生理特性之一。对胡杨不同部位和不同叶型的叶水势测定结果表明,上部的叶水势比下部低,披针叶的叶水势比阔卵叶的叶水势高,这与水分移动的规律相符合。胡杨叶水势的日、季变化与气温、大气相对湿度、辐射照度间有十分显著的相关关系。与土壤水分间也有十分显著的相关关系,土壤含水量下降,蒸腾加快,叶水势降低,土壤含水量增加,蒸腾减弱,叶水势回升。     

Strength of ensemble learning in multiclass classification of rockburst intensity

Rockbust is a violent expulsion of rock due to the extreme release of strain energy stored in surrounding rock mass, leading to considerable damages to underground strucures and equipment, and threatening workers' safety. As the operational depth of engineering projects increases, a larger number of factors influence the mechanism of rockburst. Therefore, accurate classification of rockburst intensity cannot be achieved based on conventional criteria. It is urgent to develop new models with high accuracy and ease to implement in practice. This study proposed an ensemble machine learning method by aggregating seven individual classifiers including back propagation neural network, support vector machine, decision tree, k-nearest neighbours, logistic regression, multiple linear regression and Naïve Bayes. In addition, we proposed nine data imputation methods to replace the missing values in the compiled database including 188 rockburst instances. Five-fold cross validation and the beetle antennae search algorithm are used to tune hyperparameters and voting weights of the individual classifiers. The results show that the rockburst classification accuracy obtained by the classifier ensemble has increased by 15.4% compared with the best individual classifier on the test set. The predictor importance obtained by the classifier ensemble shows that the elastic energy index is the most sensitive input variable for rockburst intensity classification. This robust ensemble method can be extended to solve other classification problems in underground engineering projects.     

植被叶面积指数估算的红边指数建模分析

针对在路域环境监测中,如何精确估算叶面积指数问题,该文提出以长韶娄高速路域为研究区,筛选出4种常用植被指数和4种红边指数两类指数,分别构建了经验模型和机器学习的反演模型,利用Sentinel-2影像数据和同步的LAI-2000地面实测数据完成路域植被叶面积指数反演。结果表明,红边波段参与运算的植被指数与植被叶面积指数敏感性是显著相关,红边指数在反演精度上更优。由此可知,相较于常见植被指数,红边指数增强了其与叶面积指数的敏感性,提高了叶面积指数估算模型精度。