一种基于属性值变化程度定权的聚类算法

针对经典K-means聚类算法以欧氏距离作为相似度判断法则进行聚类划分,而未考虑聚类对象的各属性值对聚类划分的影响程度存在差异的问题,该文提出了一种基于属性值变化程度定权的聚类算法。通过采用Iris dataset数据进行实验,该算法相对于其他聚类算法获得了更好的聚类效果,且该算法适用于生物物种分类、遥感影像识别等工作领域,能提高聚类运算的精准度。     

AHP-灰色关联度分析法的耕地质量评价——以湖北省襄阳市为例

针对传统耕地质量评价方法的单一性和局限性,该文提出一种将层次分析法与灰色关联度分析法融合的主客观相结合的耕地质量评定新方法。依据第一次全国地理国情普查数据成果,选取湖北省襄阳市作为研究区,建立试点区耕地质量综合评价指标体系,并对评价结果的可靠性进行验证。结果表明,该方法对耕地质量评价是科学有效的,能为耕地合理规划提出相关建议。     

大范围复杂三维场景并行绘制实时帧同步技术

针对复杂三维模型在实时绘制过程中的帧同步策略,该文提出改进。基于Windows集群开发了一种sort-first数据分布式体系结构的并行图形绘制系统;基于缓存交换技术提出一种多路并行的帧同步算法来提高集群的通信效率。在Windows集群系统上进行了验证实验,结果表明:(1)该算法较大程度地提高了集群的帧同步性能并缩短了同步重建时间;(2)集群并行系统有效地完成了大范围复杂三维GIS场景的流畅绘制显示。     

GIS的矿区土壤重金属污染评价及空间分布

针对土壤中的重金属含量超标会对人体健康造成极大危害的问题,为检测矿区土壤重金属含量超标状况及空间分布特征,以江西省信丰县4个矿区为例,在28个点位的20~60cm处测定Hg、Cd、As、Cu、Pb、Ni的含量,采用地统计学和地理信息系统相结合的方法进行分析。结果表明,单因子污染指数显示Pb的污染程度最大,污染程度为中度污染;插值分析图显示Cu以西南方向的虎山矿区含量较高,Ni以西南方向的虎山矿区和北部的赤岗矿区含量较高,Pb的污染区域贯穿于整个分布区;重金属含量随深度的增加无明显变化。结合在污染修复方面的经验,建议通过植物修复技术、物理与化学方法进行污染治理和修复。     

Performance of GPS and GPS/SINS navigation in the CE-5T1 skip re-entry mission

A CE-5T1 spacecraft completed a high-speed skip re-entry to the earth after a circumlunar flight on October 31, 2014. In addition to the strapdown inertial navigation system (SINS), a lightweight GPS receiver with rapid acquisition was developed as a navigation sensor in the re-entry capsule. The GPS receiver effectively solved the poor accuracy problem of long-term navigation using only the SINS. In contrast to ground users and low-earth-orbit spacecraft, numerous factors, including high altitude and kinetic characteristics in high-speed skip re-entry, are important for GPS positioning feasibility and were presented in accordance with the flight data. GPS solutions started at nearly 4900 km orbital altitude during the phases of re-entry process. These solutions were combined by an inertial measurement unit in a loosely coupled integrated navigation method and SINS navigation initialization. A simplified GPS/SINS navigation filter for limited resources was effectively developed and implemented on board for spacecraft application. Flight data estimation analyses, including trajectory, attitude, position distribution of GPS satellite, and navigation accuracy, were presented. The estimated accuracy of position was better than 42 m, and the accuracy of velocity was better than 0.1 m/s.     

Position-domain integrity risk-based ambiguity validation for the integer bootstrap estimator

Integrity monitoring for ambiguity resolution is of significance for utilizing the high-precision carrier phase differential positioning for safety–critical navigational applications. The integer bootstrap estimator can provide an analytical probability density function, which enables the precise evaluation of the integrity risk for ambiguity validation. In order to monitor the effect of unknown ambiguity bias on the integer bootstrap estimator, the position-domain integrity risk of the integer bootstrapped baseline is evaluated under the complete failure modes by using the worst-case protection principle. Furthermore, a partial ambiguity resolution method is developed in order to satisfy the predefined integrity risk requirement. Static and kinematic experiments are carried out to test the proposed method by comparing with the traditional ratio test method and the protection level-based method. The static experimental result has shown that the proposed method can achieve a significant global availability improvement by 51% at most. The kinematic result reveals that the proposed method obtains the best balance between the positioning accuracy and the continuity performance.     

Improved decentralized multi-sensor navigation system for airborne applications

The integration of Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) technologies is a very useful navigation option for high-accuracy positioning in many applications. However, its performance is still limited by GNSS satellite availability and satellite geometry. To address such limitations, a non-GNSS-based positioning technology known as “Locata” is used to augment a standard GNSS/INS system. The conventional methods for multi-sensor integration can be classified as being either in the form of centralized Kalman filtering (CKF), or decentralized Kalman filtering. However, these two filtering architectures are not always ideal for real-world applications. To satisfy both accuracy and reliability requirements, these three integration algorithms—CKF, federated Kalman filtering (FKF) and an improved decentralized filtering, known as global optimal filtering (GOF)—are investigated. In principle, the GOF is derived from more information resources than the CKF and FKF algorithms. These three algorithms are implemented in a GPS/Locata/INS integrated navigation system and evaluated using data obtained from a flight test. The experimental results show that the position, velocity and attitude solution derived from the GOF-based system indicate improvements of 30, 18.4 and 20.8% over the CKF- and FKF-based systems, respectively.     

Geographic information science and the analysis of place and health

The representation of place is a key theoretical advancement that geographic information science can offer to improve the understanding of environmental determinants of health, but developing robust computational representations of place requires a substantial departure from conventional notions of geographic representation in GIS. Unlike conventional GIS representations based on either objects or locations, we suggest that place representation should incorporate dynamic subjective, experiential, and relational aspects of place, as the influence of place on health behavior concerns not only the features that can be objectively observed at a particular location but also the environmental perceptions of the individual, as molded by biological, social, and experiential characteristics. In addition, assessments of environmental exposures on health outcomes should focus on individuals' time–activity patterns and microenvironment profiles, which form a potentially unique personalized exposure environment for each individual. Addressing these representational challenges via collaborative research has the potential to advance both geographic information science and health research.     

An enhanced approach for surface flow routing over drainage‐constrained triangulated irregular networks

The accuracy and efficiency of the simulations in distributed hydrological models must depend on the proper estimation of flow directions and paths. Numerous studies have been carried out to delineate the drainage patterns based on gridded digital elevation models (DEMs). The triangulated irregular network (TIN) has been increasingly applied in hydrological applications due to the advantages of high storage efficiency and multi‐scale adaptive performance. Much of the previous literature focuses mainly on filling the depressions on gridded DEMs rather than treating the special cases in TIN structures, which has hampered its applications to hydrological models. This study proposes a triangulation‐based solution for the removal of flat areas and pits to enhance the simulation of flow routing on triangulated facet networks. Based on the drainage‐constrained TIN generated from only a gridded DEM by the compound point extraction (CPE) method, the inconsistent situations including flat triangles, V‐shape flat edges and sink nodes are respectively identified and rectified. The optimization algorithm is an iterative process of TIN reconstruction, in which the flat areas are generalized into their center points and the pits are rectified by embedding break lines. To verify the proposed algorithm and investigate the potential for flow routing, flow paths of steepest descent are derived by the vector‐based tracking algorithm based on the optimized TIN. A case study of TIN optimization and flow path tracking was performed on a real‐world DEM. The outcomes indicate that the proposed approach can effectively solve the problem of inconsistencies without a significant loss in accuracy of the terrain model.     

2016年四川省PM2.5浓度时空分布研究

PM2.5导致大气能见度下降,造成雾霾天气.本文基于2016年四川省89个空气质量监测站的PM2.5数据,对2016年四川省PM2.5浓度时空分布特征进行研究分析.结果表明,2016年四川省PM2.5浓度空间分布呈现出西北部PM2.5浓度较低、空气质量较好,东南部PM2.5浓度较高、空气质量较差的趋势;时间分布呈现夏季PM2.5浓度较低、空气质量较好,冬季PM2.5浓度较高、空气质量较差的趋势,从而得出四川省PM2.5浓度时间和空间分布规律及分布图.