Scale mismatches and their ecological and economic effects on landscapes: A spatially explicit model

Mismatches between the spatial scales of human decision-making and natural processes contribute to environmental problems such as global warming and biodiversity losses. People damage the environment through local activities like clearing land or burning fossil fuels, but the damages only become manifest at larger regional or global scales where no one pays for them. Payments for ecological services like carbon sequestration can correct for these damages caused by scale mismatches. This paper presents a spatially explicit land-use model to investigate the consequences of scale mismatches for pollination and carbon storage services and examine the effect of payment for only carbon storage services. The model integrates processes in multiple spatial scales ranging from the parcel level used by landowners’ decision about deforestation, to the larger scale used by animals to pollinate plants, and finally to the global scale where carbon storage services are supplied. We show that payment for carbon storage services can become an effective mechanism to protect forests at the same time that it creates inequities among landowners in income level.These findings suggest that market-based approaches that focus on conservation of a single ecosystem service may reproduce unequal power relations among landowners.     

单双频智能手机GNSS定位精度分析

为分析单、双频手机在单点定位和动态导航中的差异,本文对单、双频手机观测卫星数、信噪比、静态/动态定位中原始观测值/卡尔曼滤波值进行了对比和分析。试验结果表明,在静态无遮挡的试验条件下,小米MI8双频手机原始观测值较OPPO Reno单频手机定位误差均值减小了1.70 m且能观测到更多的卫星数,进行卡尔曼滤波处理后,单频手机较双频手机而言精度提升更多,两者最终精度相当。而在动态有遮挡的试验条件下,双频较单频定位误差均值减小了5.24 m,进行卡尔曼滤波处理后,两者精度均有明显改善,双频相对单频误差均值减小了0.87 m。     

基于分类回归树分析的遥感影像土地利用／覆被分类研究

以专家知识和经验为基础,综合影像光谱信息和其他辅助信息进行分类的基于知识的遥感影像解译方法,是提高遥感影像分类精度,实现自动解译的有效途径之一。然而,知识的获取一直是其得以广泛应用的“瓶颈”问题。以江苏省江宁试验区土地利用/覆被分类为例,利用分类回归树分析(CART)从训练样本数据集中发现分类规则,集成遥感影像的光谱特征、纹理特征和空间分布特征进行分类实验,并与传统的监督分类和逻辑通道分类方法进行比较。结果表明,基于CART的分类方法的精度基本在80%以上,与另两种方法相比,有了较大的提高,而且该算法复杂性低,效率高。由此说明,利用CART算法构建决策树获取的分类规则是合理的。它可以快速、有效地获取大量分类规则,是促进基于知识的遥感影像分类方法在土地利用/覆被分类中广泛应用的一项有效手段。     

X射线衍射-扫描电镜等技术研究秘鲁铜硫矿石选矿工艺矿物学特征

秘鲁铜硫矿石的主要回收对象是铜和硫矿物,由于铜矿物嵌布复杂、粒度过细以及与各种脉石矿物或金属矿物交生关系紧密,利用传统工艺矿物学研究方法如化学分析、光学显微镜检测等较难准确定量其工艺矿物学参数。本文采用化学分析、X射线衍射、扫描电镜、偏光显微镜及矿物参数自动分析系统(MLA)等技术手段,研究秘鲁铜硫矿石的化学成分、矿物组成和主要矿物的嵌布特征、粒度分布及单体解离特性等,并对影响选矿指标的主要矿物学因素进行分析。结果表明:矿石中主要元素为Cu(0.65%)和S(9.53%)。矿石中黄铁矿(16.57%)含量较高,形态较为规则,与其他矿物之间的交生关系相对简单,粒度普遍偏粗,其中粒径大于0.30mm的黄铁矿占95.06%。铜矿物主要以不规则粒状、皮壳状、网脉状、纤维状、尘粒状、斑点状分布于脉石中或与黄铁矿、闪锌矿、磁铁矿等金属矿物交生紧密,粒度极不均匀,使得铜矿物解离难度加大,且矿石中云母(12.51%)、绿泥石(3.74%)、滑石(3.34%)、高岭石、蒙脱石(3.59%)等黏土质矿物含量较高,在磨矿过程中易发生泥化从而恶化分选环境。根据该类型矿石的工艺矿物学特性,本文建议采用"粗磨-部分优先浮铜-铜硫混浮-混合精矿再磨再选分离"的工艺流程,可得到质量高的铜、硫精矿。     

耦合PCA-SVM算法的金矿矿床规模预测分析研究

判断矿床(点)的类型是矿床勘探中的重要内容,传统预测金矿成矿规模的方法不仅耗时耗力,而且所需的经济成本较大。为提高矿床规模的勘探效率和准确度,揭示元素与金矿成矿规模的潜在联系,文中提出了耦合主成分分析(principal component analysis,PCA)和支持向量机(support vector machine,SVM)算法的预测分析PCA-SVM(principal component analysis-support vector machine)方法。该方法先通过主成分分析提取数据中的主要特征,再将主要特征带入支持向量机算法,从而训练出最优分类器以预测金矿成矿规模。文中共使用了3 812个金矿样本数据用于学习训练和预测分析,训练准确率为92.3%,测试准确率为88.7%,分别比直接使用支持向量机算法高出14.3%和17.1%。基于PCA-SVM的预测模型,不仅消除了人为主观因素的影响,而且有效提高了勘探过程中矿床预测的准确率和矿床勘探的效率,为地质勘查工作提供依据。     

黄土高原沟谷地貌发育演化研究进展与展望

黄土沟谷是黄土地貌中最有活力、最具变化、最富特色的对象单元,黄土高原千沟万壑的地貌形态以及触目惊心的侵蚀状态也让区域内沟谷地貌的形成、发育及演化问题成为研究中焦点及前沿性科学问题。近年来,诸多学者采用地学测年法、特征表达法、监测模拟法力图实现对黄土沟谷发育演化进程中“过去-现代-未来”的科学认知。这些研究在相当程度上丰富了黄土沟谷发育过程的认知。本文梳理了黄土高原沟谷地貌演化相关研究的现状,并从黄土高原地貌演化、黄土沟谷发育、基于DEM的沟谷信息提取与表达等研究进行了系统的回顾、梳理与分析。此外,本文提出“黄土沟道剖面群组”概念与方法,试图从新的视角审视黄土沟谷地貌发育演化过程。沟道剖面在黄土沟谷发育演化进程中传递物质能量和累积地形动力,并通过径流节点的串联实现剖面群的连接与组合,形成独特的剖面“群组”模式;该沟道剖面群组是集黄土沟谷地貌特征与过程于一体的综合信息集成体,其三维空间结构是对黄土沟谷地貌发育演化的高度抽象与映射,并可望进一步丰富黄土高原数字地形分析理论与方法体系,为黄土高原黄土地貌成因机理与空间分异格局带来创新的认识。     

Long‐term variations and temporal scaling of hydroclimatic time series with focus on the German part of the Elbe River Basin

Long‐term variations and temporal scaling of mean monthly time series of river flow, precipitation, temperature, relative humidity, air pressure, duration of bright sunshine, degree of cloud cover, short wave radiation, wind speed and potential evaporation within or in vicinity of the German part of the Elbe River Basin are analyzed. Statistically significant correlations between the 2–15 year scale‐averaged wavelet spectra of the hydroclimatic variables and the North Atlantic Oscillation‐ and Arctic Oscillation index are found which suggests that such long‐term patterns in hydroclimatic time series are externally forced. The Hurst parameter estimates (H) based on the Detrended Fluctuation Analysis (DFA) indicate persistence for discharge, precipitation, wind speed, air pressure and the degree of cloud cover, all having an annual cycle and a broad low‐frequency distribution. Also, DFA H parameter estimates are higher for discharge than for precipitation. The major long‐term quasi‐periodic variability modes of precipitation detected using Singular Spectrum Analysis coincide with those detected in the discharge time series. Upon subtraction of these low‐frequency quasi‐periodic modes, the DFA H parameter estimates suggest absence of the persistence for both precipitation and discharge. Copyright © 2013 John Wiley & Sons, Ltd.     

多维“流”视角下区域旅游网络结构特征及其作用机制分析——以云南省为例

基于多维流视角,运用GIS及社会网络分析方法,对比分析云南省旅游经济流、客流、信息流、资金流的网络结构差异特征及相互影响作用机制。研究表明：云南省供需两侧旅游流反向发展态势明显,旅游流网络异质演变特征明显,流量水平趋高,而流质水平偏低。旅游经济流发展未能随着旅游客流和信息流的发展而增强,网络密度偏低且长期存在旅游经济发展孤点,旅游经济合作交流不足。各州市在旅游经济流网络中“零和竞争”的偏利非共生发展态势,使得旅游市场领域存在一定的“公地悲剧”现象。云南省旅游流节点水平及其空间特征差异显著,”核心-边缘”结构明显。云南省旅游经济流受到旅游客流的中介力、旅游信息流的推动力、旅游资金流的拉动力三者的共同作用影响,各作用力影响程度表现出强弱历时性差异演化,旅游客流中介力持续增强,旅游信息流推动力稳步强化,旅游资金流拉动力显著下降。云南省旅游经济增长及旅游经济流网络发展驱动模式,正逐步由“供给侧拉动型”向“需求侧推动型”转变。     

Changes and continuity of wood-pastures in the lowland landscape in Czechia

The term wood-pastures is usually applied to areas with trees or other woody vegetation, scattered through a mainly grazed grassland area, and reflects one of the oldest land use types in Europe, which plays important ecological, agricultural and socio-cultural roles. However, a rapid decline in their area due to changes in land use and a lack of tree regeneration has recently been observed all over Europe, which has led to the necessity of a deeper understanding of their behaviour in relation to different factors via a detailed analysis of the history of the changes in their distribution over space and time. Despite the recent increase in the number of related studies, information on historic patterns of wood-pastures in many European locations, such as Czechia, remains incomplete. The goal of this study is to assess the habitat continuity of current wood-pastures and to analyse the land-use/land-cover changes of historical and current wood-pastures in lowlands and warm landscapes of hills and basins of Czechia. To achieve this, nine sites covering a total area of 98.6 km² were studied in Czechia. The situation on three time horizons (1820–1840s, the early 1950s and today) was analysed. The results have shown that almost all wood-pastures from the 1st half of the 19th century have now been lost and most of the currently existing ones were formed from the 1950s till today. Most wood-pastures, which were lost by the 1950s, were turned into open habitats, such as arable lands, and the ones lost from 1950 were turned into forest. New wood-pastures are mostly formed from open habitats, often in former military areas.