Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China

The significance of crop yield estimation is well known in agricultural management and policy development at regional and national levels. The primary objective of this study was to test the suitability of the method, depending on predicted crop production, to estimate crop yield with a MODIS-NDVI-based model on a regional scale. In this paper, MODIS-NDVI data, with a 250 m resolution, was used to estimate the winter wheat (Triticum aestivum L.) yield in one of the main winter-wheat-growing regions. Our study region is located in Jining, Shandong Province. In order to improve the quality of remote sensing data and the accuracy of yield prediction, especially to eliminate the cloud-contaminated data and abnormal data in the MODIS-NDVI series, the Savitzky–Golay filter was applied to smooth the 10-day NDVI data. The spatial accumulation of NDVI at the county level was used to test its relationship with winter wheat production in the study area. A linear regressive relationship between the spatial accumulation of NDVI and the production of winter wheat was established using a stepwise regression method. The average yield was derived from predicted production divided by the growing acreage of winter wheat on a county level. Finally, the results were validated by the ground survey data, and the errors were compared with the errors of agro-climate models. The results showed that the relative errors of the predicted yield using MODIS-NDVI are between −4.62% and 5.40% and that whole RMSE was 214.16 kg ha⁻¹ lower than the RMSE (233.35 kg ha⁻¹) of agro-climate models in this study region. A good predicted yield data of winter wheat could be got about 40 days ahead of harvest time, i.e. at the booting-heading stage of winter wheat. The method suggested in this paper was good for predicting regional winter wheat production and yield estimation.     

基于退火BP神经网络的GPS高程转换

阐述模拟退火算法的基本思想和原理,提出并介绍模拟退火算法优化的BP神经网络模型在GPS高程转换中的具体应用,同时编写相应的MATLAB处理程序,结合大量数据进行仿真实验,结果表明文中提出的退火BP神经网络模型具有收敛速度快、精度高、避免陷入局部最小的优良特性。     

模拟退火算法在控制网平差中的应用

线性最小二乘估计在对非线性函数进行线性近似的过程中会产生模型误差,而一些非线性参数估计方法可能因为函数复杂而难以求导,法方程系数矩阵秩亏或呈病态矩阵时难以求解,非线性迭代解法有时对初始值的选择存在依赖性,不恰当的初始值会导致迭代无法收敛。针对这些问题,引入了模拟退火算法,介绍了该算法的基本原理、计算步骤和收敛性,并以3个控制网平差应用为例,说明该算法具有无需求导求逆,简洁实用,易于编程等优势,并能实现全局优化,获得高精度的平差结果。     

江西省永平铜矿西部排土场极限堆载高度确定

国内外对排土场极限堆载高度的理论计算缺乏研究,目前尚无成熟的统一理论计算方法。文章结合永平铜矿西部排土场的工程实例,在进行边坡工程地质条件勘察与排土场岩土物理力学性质试验研究的基础上,采用数值计算方法对排土场进行了分层堆载数值模拟计算。通过对计算结果的分析,得到位移、塑性区与安全系数随堆载高度的变化规律,并确定了该排土场的极限堆载高度。     

Income distribution dynamics and cross-region convergence in Europe

This paper presents a continuous version of the model of distribution dynamics to analyse the transition dynamics and implied long-run behaviour of the EU-27 NUTS-2 regions over the period 1995–2003. It departs from previous research in two respects: first, by introducing kernel estimation and three-dimensional stacked conditional density plots as well as highest density regions plots for the visualisation of the transition function, based on Hyndman et al. (J Comput Graph Stat 5(4):315–336, 1996), and second, by combining Getis’ spatial filtering view with kernel estimation to explicitly account for the spatial dimension of the growth process. The results of the analysis indicate a very slow catching-up of the poorest regions with the richer ones, a process of shifting away of a small group of very rich regions, and highlight the importance of geography in understanding regional income distribution dynamics.

长江流域沿江镉异常源追踪与定量评估的方法技术研究:以长江流域安徽段为例

长江全流域性的Cd异常是被中国正在进行的多目标地球化学调查发现的重大生态环境问题。以长江流域安徽段为研究对象,对沿江镉异常源追踪与定量评估的方法技术进行了系统研究。通过对安徽段长江干流及其主要支流悬浮物中元素含量的测量查明:悬浮物是流域内重金属元素大跨度迁移的主要载体;Cd在悬浮物中的富集程度远远大于其他重金属元素,这或许正是Cd可以形成沿江流域性异常的主要原因;长江干流悬浮物中重金属元素含量的变化明显受到沿江支流的影响。安徽段长江干流及其主要支流重金属元素输出通量定量计算结果表明:秋蒲河是安徽段重金属元素输出通量最大的支流,每年在安徽段长江两岸土壤中沉积下约4.45t的Cd。利用悬浮物加密测量、1∶5万土壤测量和岩石测量对顺安河流域Cd异常源追踪结果显示:内生金属矿床特别是铅锌矿是悬浮物中Cd的最大的供应源。采用河漫滩沉积物分层采样技术和同位素测年技术,初步恢复了研究区Cd等重金属元素沉积和污染的地球化学历史,对研究区Cd等重金属元素异常的未来演变趋势进行了预警预测。     

附加约束条件的序贯平差

从观测量分组的参数平差出发,详细推导了附加约束条件的序贯平差及其精度估计,讨论了附加约束条件的抗差序贯平差的计算过程.算例表明,推导的公式正确有效,简单实用,附加约束条件的序贯平差抗差估计能有效地抵制粗差的影响.     

抗差最小二乘配置在数字化地图几何纠正中的应用讨论

抗差估计具有较好的抗拒异常观测值及粗差的能力,而最小二乘配置又能较好地处理系统误差,本文结合两者的优点,利用抗差最小二乘配置对数字化地图进行几何纠正,其中对协方差函数采用抗差拟合,得到了较好的结果。实验证明在GIS数据处理的扫描数字化地图几何纠正中,抗差最小二乘配置在抗拒异常值和处理系统误差方面优于单纯的最小二乘估计和单纯的最小二乘配置方法。     

基于岭估计的有理多项式参数求解方法

在使用最小二乘法解算卫星遥感影像的RPC参数时,如果控制点非均匀分布或模型过度参数化,其法方程系数矩阵很容易产生病态,获得的解将偏离真值,甚至得到错误的解.使用岭估计可改善法方程的状态,保证解稳定.采用岭估计方法,通过所获取的不同岭参数对SPOT和QuickBird影像进行实验,证实L曲线法是一种稳定的、有效的岭参数确定方法,可显著提高RPC参数的解算精度.     

应用探地雷达探测活动断层

在浅覆盖区采用探地雷达探测地震活动断层。通过实验确定出最佳的采集参数和数据处理流程,在雷达剖面上,能够清晰地显示出断层上部的形态特征、上断点埋深和岩土分层。结合钻孔资料,利用雷达剖面上对第四系覆盖的分层结果和上断点所在的层位可以分析和评价断层的活动性。