基于MATLAB的关联规则空间数据挖掘探讨——以济南市平阴县安城乡为例

本文根据关联规则挖掘方法,在Matlab中编写程序,时土地利用现状数据库进行数据挖掘。计算了不同用地类型与坡度之间的支持度和置信度,得出关联规则。通过平阴县安城乡的实证,取得了较好的结果。     

《巴黎协定》特设工作组适应信息通报谈判的最新进展和展望

适应信息通报作为《巴黎协定》下联结国家个体适应行动、全球适应目标以及全球集体适应努力的纽带,是目前《巴黎协定》特设工作组（APA）下唯一的适应议题,会对未来全球适应气候变化的政策和行动产生较大影响。本文总结了APA适应信息通报的谈判进程和最新进展,梳理了不同缔约方和谈判集团对适应信息通报目的、内容、报告渠道、指南和灵活性的立场和观点,展望了适应信息通报未来的谈判走势。中国与大多数发展中国家相比,开展适应行动及提供信息报告的能力较强,在适应信息通报谈判中立场相对灵活,但未来在有关适应的资金支持谈判等方面仍面临着压力,建议推动和深化适应气候变化领域南南合作以团结更多发展中国家,促进全球适应行动,回应发展中国家的关切。     

Scenario archetypes reveal risks and opportunities for global mountain futures

Mountain social-ecological systems (MtSES) are transforming rapidly due to changes in multiple environmental and socioeconomic drivers. However, the complexity and diversity of MtSES present challenges for local communities, researchers and decision makers seeking to anticipate change and promote action towards sustainable MtSES. Participatory scenario planning can reveal potential futures and their interacting dynamics, while archetype analysis aggregates insights from site-based scenarios. We combined a systematic review of the global MtSES participatory scenarios literature and archetype analysis to identify emergent MtSES archetypal configurations. An initial sample of 1983 rendered 42 articles that contained 142 scenarios within which were 852 ‘futures states’. From these future states within the scenarios, we identified 59 desirable and undesirable futures that were common across studies. These ‘common futures’ were grouped into four clusters that correlated significantly with three social-ecological factors (GDP per capita, income inequality, and mean annual temperature). Using these clusters and their associated significant factors, we derived four MtSES scenario archetypal configurations characterized by similar key adaptation strategies, assumptions, risks, and uncertainties. We called these archetypes: (1) “revitalization through effective institutions and tourism”; (2) “local innovations in smallholder farming and forestry”; (3) “upland depopulation and increased risk of hazards”; and (4) “regulated economic and ecological prosperity”. Results indicate risks to be mitigated, including biodiversity loss, ecosystem degradation, cultural heritage change, loss of connection to the land, weak leadership, market collapse, upland depopulation, increased landslides, avalanches, mudflows and rock falls, as well as climate variability and change. Transformative opportunities lie in adaptive biodiversity conservation, income diversification, adaptation to market fluxes, improving transport and irrigation infrastructure, high quality tourism and preserving traditional knowledge. Despite the uncertainties arising from global environmental changes, these archetypes support better targeting of evidence-informed actions across scales and sectors in MtSES.     

基于北斗反射信号的支持向量回归机海面风速反演研究

随着全球导航卫星系统的发展,一种基于导航卫星反射信号(GNSS-R)的海洋遥感技术成为近年来研究的热点。为研究GNSS-R测风方法,分析了海面风速与反射信号时延功率之间的关系,同时结合机器学习方法中的支持向量回归机方法,将反射信号时延功率作为训练标签,最终完成海面风速的反演。将"北斗反射信号海风海浪探测系统——山东示范站"项目期间海风海浪系统的探测结果与同期风速仪探测结果进行对比分析,结果表明,两者具有很好的一致性,海面风速的反演精度为2.4 m/s,证明了基于北斗反射信号的支持向量回归机海面测风方法是可行的。     

An intelligent spatial land use planning support system using socially rational agents

This research presents an intelligent planning support system based on multi-agent systems for spatial urban land use planning. The proposed system consists of two main phases: a pre-negotiation phase and an automated negotiation phase. The pre-negotiation phase involves interaction between human actors and intelligent software agents in order to elicit the actors’ social preferences. The agents employ social value orientation theory, which is rooted in social psychology, in order to model actors’ social preferences. The automated negotiation phase involves negotiation among autonomous software agents, the aim being to achieve consensus about the spatial problem on behalf of the relevant actors and using the information obtained.

This study employs a computationally effective Bayesian learning technique, along with social value orientation theory, to design socially rational intelligent agents who work on behalf of real actors. The proposed system is applied to a real world urban land use planning case study. Human actors participate in a pre-negotiation phase, and their social preferences are elicited by intelligent software agents through a number of interactions. Then, software agents come together to engage in an automated negotiation phase and eventually reach an agreement on the spatial configuration of urban land uses on behalf of the actors. The results of the study show that the proposed system is effective at performing an automated negotiation, plus that the final plan – which is the output of the automated negotiation – produces higher social utility and better spatial land use configurations for the agents.     

端元可变非线性混合像元分解模型

遥感影像中混合像元普遍存在。端元固定的情况下对混合像元进行分解,很难高精度地识别影像地物。本文基于支持向量机,提出了端元可变的非线性混合像元分解模型。首先,通过构建多个支持向量机获取每个像元的优化端元集,在优化端元集的基础上运用支持向量机与两两配对方法相结合的算法获取像元组分。试验结果表明,本文提出的方法效果优于传统的多端元光谱分解法。     

基于非正定 OCSVM 的高光谱影像地物异常检测

针对基于高斯径向基核函数的OCSVM等异常检测算法,对地物光谱变异极为敏感,导致算法异常检测性能不稳定的问题,根据光谱角度余弦测度对光谱形状相似性的描述不受地物光谱辐射强度变异影响的特性,将具有非正定核特性的光谱角度余弦核测度引入非正定SVM算法中,提出一种基于非正定OCSVM的高光谱影像地物异常检测算法。利用四组模拟数据进行目标异常检测实验,结果表明,该算法能够有效检测出高光谱影像数据中的目标地物,检测精度提升明显。     

基于AEPSO改进支持向量机的堤基沉降预测

在支持向量机的预测模型中,关键参数的选取是最重要的一步。在此基础上提出基于AEPSO改进的支持向量机预测模型。利用AEPSO的局部和全局搜索能力,提高支持向量机关键参数寻优的精度。文中详细介绍模型建立的过程,以莆田市木兰溪防洪工程为例,应用改进的模型进行堤基沉降预测,并与标准PSO支持向量机预测模型相对比。结果表明,基于AEPSO改进的支持向量机预测模型提高了预测的精度。     

递进式预测模型在滑坡变形预测中的应用

为达到提高滑坡变形预测精度的目的,利用量子算法和粒子群算法对支持向量机进行优化,并利用马尔科夫链对滑坡变形预测误差进行修正,综合构建滑坡变形的递进式预测模型。结果表明:通过量子算法及粒子群算法对支持向量机优化,克服支持向量机参数选取困难,实现预测过程的全局优化,并经过MC误差修正模型对滑坡变形预测值误差修正,提高预测精度及预测值稳定性,验证预测模型可行性和有效性,为滑坡变形预测提供一种新的预测方法。     

Multiple spectral similarity metrics for surface materials identification using hyperspectral data

Modern hyperspectral imaging and non-imaging spectroradiometer has the capability to acquire high-resolution spectral reflectance data required for surface materials identification and mapping. Spectral similarity metrics, due to their mathematical simplicity and insensitiveness to the number of reference labelled spectra, have been increasingly used for material mapping by labelling reflectance spectra in hyperspectral data labelling. For a particular hyperspectral data set, the accuracy of spectral labelling depends considerably upon the degree of unambiguous spectral matching achieved by the spectral similarity metric used. In this work, we propose a new methodology for quantifying spectral similarity for hyperspectral data labelling for surface materials identification. Developed adopting the multiple classifier system architecture, the proposed methodology unifies into a single framework the differential performances of eight different spectral similarity metrics for the quantification of spectral matching for surface materials. The proposed methodology has been implemented on two types of hyperspectral data viz. image (airborne hyperspectral images) and non-image (library spectra) for numerous surface materials identification. Further, the performance of the proposed methodology has been compared with the support vector machines (SVM) approach, and with all the base spectral similarity metrics. The results indicate that, for the hyperspectral images, the performance of the proposed methodology is comparable with that of the SVM. For the library spectra, the proposed methodology shows a consistently higher (increase of about 30% when compared to SVM) classification accuracy. The proposed methodology has the potential to serve as a general library search method for materials identification using hyperspectral data.