基于OFA-PP模型的区域最严格水资源管理类型识别与评价

为科学识别云南省16个州市最严格水资源管理区域类型,提出最优觅食算法(OFA)-投影寻踪(PP)识别模型。从最严格水资源管理用水总量控制红线、用水效率控制红线、纳污控制红线3个方面分别构建指标体系和分级标准,利用2015年云南省各州市指标数据及分级标准阈值分别构建基于"三条红线"的投影指标函数,采用OFA分别搜索最优投影向量,并计算各州市综合投影值和各分级标准阈值投影值,利用分级标准阈值投影值对各区域最严格水资源管理类型进行识别。结果表明,OFA-PP识别模型具有较好的识别效果,识别结果可为云南省实行最严格水资源管理制度提供参考。     

敦煌西湖自然保护区湿地演化及驱动力分析

西湖国家级自然保护区位于河西走廊西端,是敦煌盆地人工绿洲的天然屏障。近几十年来,由于气候变化和人类水土资源过度开发,保护区生态环境持续恶化,湿地退化和沙漠化趋势日趋严重。本文运用多时相资源卫星遥感影像,解译分析了保护区湿地演化规律。结果表明：1980-2013年间有23个年份湿地处于快速退化状态,保护区湿地面积由1.72×10⁴ hm²减少到0.99×10⁴ hm²,减少了42.4%;保护区湿地的斑块数从32个增加到51个,平均斑块面积由537 hm²减少为213 hm²,湿地演化呈破碎化趋势。湿地分布质心向西南方向移动了11.59 km,湿地呈整体向西南缓慢移动的趋势。运用因子分析法对湿地演化的驱动因子进行了分类,并利用投影寻踪模型分析各驱动因子对湿地演化的贡献率,结果表明：下游湿地退化的根本原因是大规模引地表水和开采地下水灌溉,其次是气候变化引起的冰川退缩、径流量衰减。20世纪90年代,西湖保护区湿地处于相对稳定状态,建议敦煌地区耕地维持在20世纪90年代初的2.7×10⁴ hm²水平,或通过节水、调整作物结构和跨流域调水等措施,压缩引地表水和开采地下水水量,灌溉用水需控制在20世纪90年代初的用水水平。该研究成果可为自然保护区湿地保护和流域综合开发提供依据。     

Methods for detecting apparent differences between spatial tessellations at different time points

This paper proposes methods for detecting apparent differences between spatial tessellations at two different points in time, with the objective of conflation of spatial tessellations at multiple time points. The methods comprise three steps. First, we eliminate systematic differences between tessellations using the affine transformation. Second, we match subregions between tessellations at two points in time and match boundaries based on matching relationships between the subregions. Third, we propose a distance metric for measuring differences between the matched boundaries and a method for determining whether the measured differences are apparent or not. We apply the proposed methods to a part of the US Census data for 1990 and 2000 and empirically demonstrate the effectiveness of these methods.     

Localized versus wide-ranging effects of the post-Soviet wars in the Caucasus on agricultural abandonment

Wars are frequent and can affect land use substantially, but the effects of wars can vary greatly depending on their characteristics, such as intensity or duration. Furthermore, the spatial scale of the effects can differ. The effects of wars may be localized and thus close to conflict locations if direct mechanisms matter most (e.g., abandonment because active fighting precludes farming), or wide-ranging, e.g., farther away from conflict locations, if indirect mechanisms predominate (e.g., no access to agricultural inputs). Our goal was to quantify how the very different wars in the Caucasus region during post-Soviet times most likely affected agricultural abandonment at different scales. We analyzed data on conflict locations plus Landsat-derived land-cover data from 1987 to 2015, and applied matching statistics, difference-in-differences estimators, and logistic panel regressions. We examined the localized versus wide-ranging effects of the different wars on permanent agricultural abandonment and inferred to direct and indirect mechanisms that may have resulted in agricultural abandonment. While permanent agricultural abandonment was overall surprisingly limited across the Caucasus, up to one third of abandonment was most likely related to the wars. Among the wars, the war in Chechnya was by far the most intense and longest, but its effect on abandonment was similar to the less intense and relatively short war in Abkhazia. 47 % and 45 % of agricultural abandonment was related to each war, respectively. The reason was that the effect of the war in Chechnya was more localized, and abandonment occurred near conflict locations, in contrast to Abkhazia, where the effect was wide-ranging and abandonment occurred farther away from conflict locations. In contrast, the war in South Ossetia showed no significant effect on abandonment, and the war in Nagorno-Karabakh had the surprising pattern that abandonment was higher where no war had occurred. For each of the wars, abandonment was predominately related to the nearest conflict locations, but in Abkhazia additional conflict locations within 10 km further increased the probability of abandonment. We infer that the direct mechanisms of the war such as bombing, and active fighting most likely resulted in a localized effect close to conflict locations in Chechnya and in Nagorno-Karabakh. However, in Nagorno-Karabakh subsidies for new settlers after the war, (i.e., a positive wide-ranging effect), potentially reduced the amount of abandonment there. In contrast, negative wide-ranging effects such as refugee movements and post-war restrictions on their return is related to broad-scale abandonment in Abkhazia. In summary, permanent agricultural abandonment was not necessarily higher in a war with a high overall intensity. Instead, the effect of a given war varied in scale, and was related to the relative importance of direct and localized versus indirect and wide-ranging mechanisms, including postwar events and policies, which is likely the case for other wars, too.     

基于投影寻踪模型的水质综合评价

针对投影寻踪模型中投影指标函数的最优化计算复杂问题,采用加速遗传算法加快寻优速度,解决了投影寻踪过程中最优化问题。实例计算表明,该模型可处理复杂多指标优化问题,是解决复杂水质综合评价的有效途径。     

投影寻踪回归与BP神经网络方法在前汛期降水预测中的比较研究

以1962—2006年粤北地区7个站4—6月前汛期降水量资料为基础,将前汛期降水量与74项环流指数资料进行灰色关联度分析,确定了影响粤北地区前汛期降水量的16个关键环流指数因子,分别应用投影寻踪回归、BP神经网络和逐步回归方法,建立前汛期降水趋势预测模型,对粤北地区前汛期降水趋势进行预测。结果表明:投影寻踪回归和BP神经网络方法的预测能力均优于传统的逐步回归模型。其中,PPR模型比BP神经网络方法的预测效果更好。     

基于多尺度小波特征的高光谱影像亚像素目标识别

提出了一种基于多分辨率小波高频特征系数的高光谱遥感影像亚像素目标识别方法。首先利用多尺度小波变换将光谱信号分解为不同尺度的高频特征信号,然后借助接收操作特性曲线(ROC)和马氏距离投影寻踪求取一维最佳识别特征,最后通过高斯最大似然决策函数求解亚像素目标的存在概率。通过38种小波函数的高光谱数据实验证明,该方法对亚像素目标的识别效果较好。     

投影寻踪门限回归模型在年径流预测中的应用

为预测年径流这类同维复杂动力系统，提出了投影寻踪门限回归（PPTR）模型。构造了新的投影指标函数，用门限回归（TR）模型描述投影值与预测对象间的非线性关系，并用实码加速遗传算法优化投影指标指数函数和TR模型参数。实例的计算结果表明，用PPTR模型预测年径流是可行而有效的。PPRT模型简便、适用性强，克服了目前投影寻踪方法计算量大、编程实现困难的缺点，有利投影寻踪方法的推广应用，为解决高维非线性复杂预测问题提供了新途径。     

基于新型分层邻域阈值搜索法提高水下潜器重力匹配导航的匹配效率

本文开展了水下潜器重力匹配导航的匹配效率改善研究.第一,为克服传统TERCOM算法逐点遍历搜索效率较低的缺点,提出新型分层邻域阈值搜索法.其原理如下:首先,利用4格网间隔数进行粗搜索匹配;其次,为提高初始匹配点的选取标准设置4mGal阈值(基准图上重力值与实测重力值之差),对选取的若干粗搜索行最佳匹配点周围24邻域点进行取舍并匹配比较;最后,获得搜索范围内最佳匹配点.第二,综合考虑了重力场标准差、峰度系数、坡度标准差、粗糙度、信息熵等重力场主要特征参数,将其作为适配区优劣的分析依据.第三,在适配性良好的区域内,在保证水下导航精度的前提下,基于分层邻域阈值搜索法,以本文参数设置为例,水下潜器重力匹配导航的匹配效率提高约14.14倍.     

投影寻踪学习网络的遥感影像分类

采用投影寻踪(projection pursuit,PP)学习网络方法建立了一种新的遥感影像分类模型。该方法结合了统计学中投影寻踪算法节点函数灵活的非参数估计特点和人工神经网络的自学习功能,具有简捷的网络结构和良好的鲁棒性能。利用苏州市TM影像进行了分类实验,将分类结果与BP神经网络和最大似然法的分类结果相比较,投影寻踪学习网络的分类精度较高,具有一定的实用性。