基于物元模型的高标准农田建设优先区划定方法

以河北省涿州市为研究区,从耕地的立地条件、基础设施、空间布局、生态保护4方面构建高标准农田建设条件评价指标体系,采用层次分析法对各指标赋值,综合计算评价高标准农田建设条件,并采用物元模型对各评价条件进行综合关联度计算,结合限制因素组合法,对各限制因素进行等级划分和个数组合,通过建设条件和限制因素两方面划分高标准农田建设优先区。研究结果表明:涿州市高标准农田建设条件整体较好,其中优先划入区、适宜调入区、重点整治区、后备调控区面积比例分别为17.58%、48.60%、32.70%、1.12%,且优先划入区主要分布在码头镇、刁窝乡、豆庄乡北部以及松林店镇,适宜调入区主要分布在百尺竿镇东部、东城坊镇、义和庄乡西部、刁窝乡以及涿州市南部大部分地区,重点整治区分布在百尺竿镇、东城坊镇以及义和庄乡东部地区,呈现明显的聚集状态,后备调控区分布较少,零散分布于研究区内。研究结果可为高标准农田建设优先区合理划定提供借鉴参考。

基于SegNet语义模型的高分辨率遥感影像农村建设用地提取

针对传统分类算法、浅层学习算法不适用于高空间分辨率遥感影像中农村建筑物信息提取的问题,该文以河北省霸州市高空间分辨率遥感影像WorldView-2为数据源,利用182 064幅128×128像素大小的影像切片为训练样本,选取基于深度卷积神经网络的SegNet图像语义分割算法对遥感影像中的农村建筑物进行提取,并与传统分类算法中的最大似然法(maximum likelihood,ML)和ISO聚类、浅层学习算法中的支持向量机(support vector machine,SVM)和随机森林(random forest,RF)以及深层语义分割算法中的金字塔场景解析网络(pyramid scene parsing network,PSPNet)的试验结果作对比分析。研究结果表明:SegNet不仅能够高效利用高空间分辨率遥感影像中农村建筑物的光谱信息而且还能够充分利用其丰富的空间特征信息,最终形成较好的分类模型,该算法在验证样本中的分类总体精度为96.61%,Kappa系数为0.90,建筑物的F1值为0.91,其余5种分类算法的总体精度、Kappa系数、建筑物的F1值都分别在94.68%、0.83、0.87以下。该研究可以为高空间分辨率遥感影像农村建设用地提取研究提供参考。

Adsorption of Fe^(3+) Ions from Aqueous Solution by Natural and Synthetic Apatites: Kinetic, Equilibrium and Thermodynamic Study

In this study, the adsorption kinetics, equilibrium and thermodynamics of Fe3+ ions on natural (NAP) and synthetic (HAP) apaties were examined. The adsorption efficiency of Fe3+ onto the NAP and HAP was increased with increasing temperature. The kinetics of adsorption of Fe3+ ions was discussed using three kinetic models, the pseudo-first-order, the pseudo-second-order and the intra-particle diffusion model. The experimental data fitted very well the pseudo-second-order kinetic model. The initial sorption rate and the activation energy were also calculated. The activation energy of the sorption was calculated as 37.15 and 49.84 kJ·mol 1 for NAP and HAP, respectively. Experimental results were also analysed by the Langmuir, Freundlich and Dubinin–Redushkevich (D–R) isotherm equations at different temperatures. RL separation factor for Langmuir and the n value for Freundlich isotherm show that Fe3+ ions are favorably adsorbed by NAP and HAP. Various thermodynamic parameters such as enthalpy (ΔH), Gibbs free energy (ΔG) and entropy (ΔS) changes were computed and the results showed that the adsorption of Fe3+ ions onto NAP and HAP were spontaneous and endothermic in nature.