Estimation of litchi (Litchi chinensis Sonn.) leaf nitrogen content at different growth stages using canopy reflectance spectra

The estimation of crop nitrogen status in fresh vegetation leaf using field spectroscopy is challenging due to the weak responses on leaf/canopy reflectance and the overlapping with the absorption features of other compounds. Although the spectral indices were proposed in the literature to predict leaf nitrogen content (LNC), the performance of selected spectral indices to estimate the LNC is often inconsistent. Moreover, the models for nitrogen content estimation changed with the growth stage. The goal of this study was to evaluate the performance of published indices, ratio of data difference index (RDDI) and ratio of data index (RDI) developed by band iterative-optimization algorithm in LNC estimation. The correlation analysis, linear regression and cross validation were used to analyze the relationship between spectral data and LNC and construct the best performed estimation model. The study was conducted by the data of five growing seasons of litchi from the orchards in Guangdong Province of China. Results showed that the relationship between chlorophyll (Chl) related spectral indices and LNC varied with the growth stage. Even in flower bud morphological differentiation stage and autumn shoot maturation stage, there were not significant correlations between the proposed spectral indices and LNC. Besides it is difficult to estimate the LNC by the general model across the growth stages due to the integrated effects of cultivar, biochemical, canopy structure, etc. The band iterative-optimization algorithm can improve the sensitivity of spectral data to LNC to some extent. The optimal RDDI performed better than other indices for the synthetic dataset and the dataset in each growth stage. And the sensitive bands selected in the optimal indices at each growth stage are not consistent, which are not only related to the Chl absorption but also other biochemical components, such as starch, lignin, cellulose, protein, etc. In general, the LNC can be estimated by the optimized CR-based RDDI indices in autumn shoot maturation stage, flower spike stage, fruit maturation stage, and flowering stage with the R² > 0.50 and RMSE < 0.14. Although there were the significant relationship between RDIs and RDDIs in flower bud morphological differentiation stage, the highest R²s of the model developed by RDDIs and RDIs were less than 0.50 in cross validation. This study indicated that the applicability of canopy reflectance to estimate litchi LNC was closely related to the growth stage of litchi. Growth stage-specific models will be preferred for estimating litchi LNC estimation.     

基于光谱吸收特征的土壤含水量预测模型研究

为了定量分析土壤含水量与反射光谱特征之间关系,并为土壤含水量速测提供理论依据。以黑土作为研究对象,测定实验室光谱反射率,利用去包络线方法提取反射光谱特征指标,建立土壤水分含量高光谱预测模型。结果表明:黑土含水量与1 420 nm、1 920 nm附近吸收谷的主要光谱特征(吸收谷深度、宽度、面积)呈显著正相关;1 920 nm附近吸收谷可作为黑土土壤水分的特征吸收谷,由其光谱特征参数预测黑土含水量;以1 920 nm附近吸收谷面积为自变量建立的一元线性回归模型预测精度高,输入量少,可以作为土壤含水量速测仪器研制的理论依据。     

浅谈村落精神在农民回迁安置区中的延续

文章以2007年首届奥斯本杯国际景观设计大赛优胜奖作品为例,探讨我国城市化进程中农民回迁安置区的景观规划设计思想和手法。通过分析村落的布局特点、空间形态和农田肌理,提炼"田"字格模型概念,阐述作者如何延续村落精神,营造出符合农民回迁安置区特点的景观空间。     

基于节点变量法的连续体结构拓扑优化设计

为避免结构拓扑优化设计中的数值不稳定性及考虑制造因素,提出了一种节点变量的连续体结构拓扑优化设计方法。在指定的子区域内,采用不依赖网格的映射函数表示节点设计变量与节点密度变量的关系,实现最小尺寸约束,以满足加工工艺要求。以应变能力最小化为目标函数满足结构刚度要求,以结构体积作为约束,建立最小尺寸约束下的连续体结构拓扑优化模型,将移动近似算法用于拓扑优化问题求解。数值算例结果表明,提出的方法应用于连续体拓扑优化设计中是有效的,能够消除数值不稳定性现象获得清晰的拓扑结果,结构便于制造加工。     

社会转型期农村养老模式的变迁趋势探究

论述"连续统"中各种模式在我国过去、当前和未来的发展变化及作用,提出从传统社会到现代社会的社会转型过程是不可逆的,"连续统"中从以家庭养老为主到以社会养老保障为主也必将是农村养老模式变迁的总体趋势。     

干旱区典型盐碱土反射光谱特征分析

地物光谱特征是遥感机理的重要内容,也是遥感应用研究的重要依据.盐碱土的反射光谱特性反映了盐碱土的理化特征.以干旱区3种典型的盐碱土为研究对象,测量了不同含盐量和含水率的土壤反射率光谱,并分析了其光谱特征.结果表明,3种盐碱土的光谱反射率在干燥状态下有明显的高低规律.经过去包络线处理后,3种盐碱土在干燥状态下具有明显不同的光谱特征,且在干湿两种状态下,两个水分吸收谷处的吸收深度的深浅均具有明显的深浅差异.根据这些特征可以将3种类型的盐碱土区分出来.研究结果可为今后进一步研究盐碱化土壤参数反演和分类,以及盐碱土监测等遥感应用服务.     

A Cosserat Theory-based Numerical Simulation of an Underground Cavern in Layered Rock Mass

Conventional equivalent continuum theory poorly interprets the bending deformations and damage phenomena encountered in rock engineering because the theory ignores the influence of gradient stress.The influence of the bending effect on deformation characteristics of the media has been considered in Cosserat continuum theory which introduces the concepts of coupled stress and bending curvature.The basic principle of Cosserat medium theory and its expanded constitutive model were introduced firstly.Next,a numerical simulation of an underground cavern was carried out using FLAC software.After this,the results of the Cosserat model and explicit joint model were compared.The simulation results not only displayed the bending deformation of layered rock mass well,but also demonstrated the validity and superiority of the Cosserat expanded model.     

基于去包络线法的番茄叶霉病发病程度估测方法

阐明番茄叶霉病(Fulvia fulva)光谱特征并对其发病程度进行估测,可为番茄叶霉病大面积遥感监测提供依据。本研究通过分析番茄叶霉病不同发病程度下叶片光谱变化特征,筛选对发病程度识别的敏感波段。并利用去包络线法对光谱反射率进行处理,构建基于光谱特征吸收参量的发病程度估测模型。研究结果表明:随着叶霉病病害等级的加深,番茄叶片的原始光谱反射率、光谱敏感度、相对反射率均呈逐渐降低趋势;可见光波段(550~730 nm)和短波红外波段(1 860~2 260 nm)是识别番茄叶霉病发病程度的最佳波段;且随着病害等级的增加,吸收波段位置(λ)向短波方向移动,最大吸收深度(D_c)和吸收面积(A)均呈递增规律。利用光谱参数构建的番茄叶霉病病害等级预测的逐步回归模型R~2达0.81,且模型验证结果较好。研究结果对利用高光谱遥感技术定量估测番茄叶霉病发病程度以及监测、防治农作物病虫害均具有较高的实用价值。     

基于连续统去除法的南疆水稻土有机质含量预测

监测土壤有机质含量状况,可为土壤肥力诊断及土壤资源的合理开发利用提供科学依据。本研究通过对南疆191个水稻土样品的反射率数据进行连续统去除处理后,构建了有机质连续统去除光谱指数并提取了850~1 380、1 380~1 550、1 730~2 150、2 150~2 380 nm 4个波段的吸收特征参数,据此建立了多种定量反演模型。结果表明:经连续统去除后,有机质的吸收特征得到了有效放大,不同有机质含量的连续统去除曲线在850~1 380 nm,其有机质含量与连续统去除值呈正相关,与吸收面积呈负相关,而在1 730~2 150 nm波段则呈现相反的规律。反射率连续统去除值与有机质含量的相关性要优于反射率与之的相关性,而反射率一阶微分与连续统去除一阶微分与有机质的相关性差异不明显。不同有机质光谱指数模型之间的建模参数与预测能力差异不大,但均只具备初略估测有机质的能力。吸收特征参数模型中,仅有850~1 380 nm波段的面积归一化最大吸收深度(NMAD850~1380nm)所建模型具有较好的定量预测能力。以反射率、反射率连续统去除、反射率一阶微分、反射率连续统去除一阶微分所建的PLSR模型均具有较好的预测能力,相对分析误差均大于2.00。所有模型中,连续统去除一阶微分(CR′)模型的决定系数与相对分析误差最高,分别为0.91、2.58,均方根误差最低,其值为5.62,具有最好的预测能力。     

基于连续统去除法的土壤盐分含量反演研究

通过对新疆维吾尔自治区温宿县、和田县、拜城县191个土样的原始反射率进行连续统去除及连续统去除的一阶微分处理,分析了盐分的高光谱吸收特征及敏感波段,并建立了盐分含量的多种高光谱定量反演模型。结果表明,在400~2 400 nm波段,土壤反射率与盐分含量之间无明显规律。640~700 nm波段的连续统去除数据与含盐量呈极显著负相关,而710~780 nm波段呈极显著正相关。原始反射率经连续统去除处理后,可明显提高反演模型的预测性能。基于盐分光谱指数和吸收特征参数构建的反演模型的稳定性及预测能力不如连续统去除、连续统去除一阶微分的400~2 400 nm或敏感波段的偏最小二乘回归(PLSR)模型。所有模型中,仅有以400~2 400 nm和640~700 nm连续统去除数据所建模型的相对分析误差(RPD)达2.5以上,分别为2.62和2.52,且二者其余各项评价指标差异不大。以640~700 nm波段连续统去除数据构建的PLSR模型对南疆水稻土盐分含量具有很好的反演效果。