Analysis of Jupiter’s Oval BA: A streamlined approach

We present a novel method of constructing streamlines to derive wind speeds within jovian vortices and demonstrate its application to Oval BA for 2001 pre-reddened Cassini flyby data, 2007 post-reddened New Horizons flyby data, and 1998 Galileo data of precursor Oval DE. Our method, while automated, attempts to combine the advantages of both automated and manual cloud tracking methods. The southern maximum wind speed of Oval BA does not show significant changes between these data sets to within our measurement uncertainty. The northern maximum does appear to have increased in strength during this time interval, which likely correlates with the oval’s return to a symmetric shape. We demonstrate how the use of closed streamlines can provide measurements of vorticity averaged over the encircled area with no a priori assumptions concerning oval shape. We find increased averaged interior vorticity between pre- and post-reddened Oval BA, with the precursor Oval DE occupying a middle value of vorticity between these two.     

Determination of asteroid masses from their close encounters with Mars

An obstacle to the asteroid mass determination lies in the difficulty in isolating the gravitational perturbation exerted by a single asteroid on the planets, being strongly correlated and mixed up with those of many other asteroids. This hindrance may be avoided by the method of analysis presented here: an asteroid mass is estimated in correspondence with its close encounters with Mars where the acceleration it induces on the planet can be sufficiently disentangled from those generated by the remaining asteroid masses to calculate. We test this technique in the analysis of range observations to Mars Global Surveyor and Mars Express performed from 1999 to 2007. For this purpose, we adopt the dynamical model of the planetary ephemeris INPOP06 (Fienga et al., 2008), which includes the gravitational influences of the 300 most perturbing asteroids of the Martian orbit. We obtain the solutions of 10 asteroid masses that have the largest effects on this orbit over the period examined: they are generally in good agreement with determinations recently published.     

基于GIS的地震安全性评价数据管理的研究

目前的地震安全性评价数据管理方法过于陈旧,不利于数据的查询和再利用。通过对这一问题的深入分析,针对安评数据的多元性特点,结合GIS的优势,提出了利用GIS技术对地震安全性评价数据进行管理的方法,并设计出了数据库管理系统的基本框架。该系统的建立,将为地震安全性评价数据管理、查询和再利用提供便利。     

保山西邑铅锌矿采选工程RQD与RBI对比研究

用岩石质量指标和岩体块度指数的理论,对钻孔岩心实测资料进行分析和对比研究,对钻孔周围岩体进行分级。结果表明:岩体块度指数在岩石质量评价中能更准确地反映其优越性,具有更为显著的工程意义。     

多金属成矿区深地震反射剖面数据处理技术实验研究——以庐枞矿集区为例

针对庐枞多金属矿集区地震资料特点及浅、深多重探测目标,对深地震反射数据进行了处理技术实验研究。在区域长剖面上,为了获得矿集区地壳与上地幔结构的精细图像,解释成矿深部过程,开展了循序渐进的常规处理技术实验和精细处理技术实验。在矿区剖面,为了获得了浅层精细结构,针对变观测系统接收等特点,进一步开展了特殊处理实验。经过区域剖面与矿区剖面的多重处理实验,集成了一套矿集区深地震反射剖面数据处理方法与处理技术流程,为我国进一步的深部探测积累了技术与经验。     

基于“数字城市”地理空间框架的国土资源档案管理系统的设计与实现

"数字城市"地理空间框架建设中发布的地理信息数据具有丰富性、多样性及准确性等诸多明显优势,基于该框架开发的国土资源档案管理系统,不仅可以使各类档案实现在线信息化管理,并且对地籍档案、建设用地档案及利用规划类档案实现在线位置查询及浏览具有很大作用,可以极大地提高档案信息化管理和应用水平。     

Conflation and aggregation of spatial data improve predictive models for species with limited habitats: A case of the threatened yellow-billed cuckoo in Arizona,USA

Riparian vegetation provides important wildlife habitat in the southwestern United States, but limited distributions and spatial complexity often leads to inaccurate representation in maps used to guide conservation. We test the use of data conflation and aggregation on multiple vegetation/land-cover maps to improve the accuracy of habitat models for the threatened western yellow-billed cuckoo (Coccyzus americanus occidentalis). We used species observations (n = 479) from a state-wide survey to develop habitat models from 1) three vegetation/land-cover maps produced at different geographic scales ranging from state to national, and 2) new aggregate maps defined by the spatial agreement of cover types, which were defined as high (agreement = all data sets), moderate (agreement ≥ 2), and low (no agreement required). Model accuracies, predicted habitat locations, and total area of predicted habitat varied considerably, illustrating the effects of input data quality on habitat predictions and resulting potential impacts on conservation planning. Habitat models based on aggregated and conflated data were more accurate and had higher model sensitivity than original vegetation/land-cover, but this accuracy came at the cost of reduced geographic extent of predicted habitat. Using the highest performing models, we assessed cuckoo habitat preference and distribution in Arizona and found that major watersheds containing high-probably habitat are fragmented by a wide swath of low-probability habitat. Focus on riparian restoration in these areas could provide more breeding habitat for the threatened cuckoo, offset potential future habitat losses in adjacent watershed, and increase regional connectivity for other threatened vertebrates that also use riparian corridors.     

中国科技资源配置效率测度及其时空格局演变特征(英文)

According to the connotation and structure of science and technology resources and some relevant data of more than 286 cities at prefecture level and above during 2001–2010, using modified method—Data Envelopment Analysis(DEA), science and technology(ST) resource allocation efficiency of different cities in different periods has been figured out, which, uncovers the distributional difference and change law of ST resource allocation efficiency from the time-space dimension. Based on that, this paper has analyzed and discussed the spatial distribution pattern and evolution trend of ST resource allocation efficiency in different cities by virtue of the Exploratory Spatial Data Analysis(ESDA). It turned out that:(1) the average of ST resource allocation efficiency in cities at prefecture level and above has always stayed at low levels, moreover, with repeated fluctuations between high and low, which shows a decreasing trend year by year. Besides, the gap between the East and the West is widening.(2) The asymmetrical distribution of ST resource allocation efficiency presents a spatial pattern of successively decreasing from Eastern China, Central China to Western China. The cities whose ST resource allocation efficiency are at higher level and high level take on a cluster distribution, which fits well with the 23 forming urban agglomerations in China.(3) The coupling degree between ST resource allocation efficiency and economic environment assumes a certain positive correlation, but not completely the same. The differentiation of ST resource allocation efficiency is common in regional development, whose existence and evolution are directly or indirectly influenced by and regarded as the reflection of many elements, such as geographical location, the natural endowment and environment of ST resources and so on.(4) In the perspective of the evolution of spatial structure, ST resource allocation efficiency of the cities at prefecture level and above shows a notable spatial autocorrelation, which in every period presents a positive correlation. The spatial distribution of ST resource allocation efficiency in neighboring cities seems to be similar in group, which tends to escalate stepwise. Meanwhile, the whole differentiation of geographical space has a diminishing tendency.(5) Viewed from LISA agglomeration map ofST resource allocation efficiency in different periods, four agglomeration types have changed differently in spatial location and the range of spatial agglomeration. And the continuity of ST resource allocation efficiency in geographical space is gradually increasing.     

Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing

As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral Imaging (HSI). Consequently, a novel Folded-PCA is proposed, where the spectral vector is folded into a matrix to allow the covariance matrix to be determined more efficiently. With this matrix-based representation, both global and local structures are extracted to provide additional information for data classification. Moreover, both the computational cost and the memory requirement have been significantly reduced. Using Support Vector Machine (SVM) for classification on two well-known HSI datasets and one Synthetic Aperture Radar (SAR) dataset in remote sensing, quantitative results are generated for objective evaluations. Comprehensive results have indicated that the proposed Folded-PCA approach not only outperforms the conventional PCA but also the baseline approach where the whole feature sets are used.