Clouds’ macrophysical characteristics play an important role in the climate system and dramatically vary because of the diverse climatic and geographic factors in China. We analyze cloud macrophysical characteristics and the differences between subregions in China (18°–54°N, 73°–135°E) from March 2012 to February 2015 based on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations, including cloud fractions, cloud vertical distribution, and cloud geometrical properties with the perspective of daytime and nighttime. We found that annual single layer, multilayer (ML), and total cloud fractions are 40.4±1.1%, 22.4±0.4%, and 62.8±1.5%, respectively, and clouds are generally located between 6 and 12 km. The cloud fractions in daytime are less than that in nighttime over the south while that of Tibet shows the reverse trend. In the vertical direction, except for Tibet, the clouds in nighttime have larger spatial coverage and are higher in altitude than that in daytime. The regional average values of cloud macrophysical characteristics in the south are highest, followed successively by Tibet, north, and northwest. Cloud geometrical depth and spacing show a gradually declining trend with the increase in layers and decrease of altitude in ML cloud system.
KEYWORDS: Digital watermarking, Tolerancing, Zoom lenses, Clouds, Data processing, Associative arrays, Remote sensing, Data hiding, Lithium, Current controlled current source
We describe a method, based on spatial relations, to generate algorithms for watermarking 2D vector map. The method
consists of: defining and computing the metric meatures of topological relations between map objects; extracting cover
data from metric meatures; deviding the cover data into different subsets; adjusting the spatial relations between map
objects within the precision tolerance of the map to make the cover data distribution of one subset shows one of the two
expected patterns to suggest the embedding of bit 1 or 0. The method is blind and experiments show that it is also
robust.
The base land value evaluation plays an important role in urban land value system for a long time. To establish a simple
and feasible method to evaluate the urban land value is always the target for scholars. According to the traditional
method of base land value evaluation, combining the theory of K-means clustering and trend surface analysis, this paper
proposes a new method for base land value evaluation, which fully considers the spatial correlation, inherent similarity
and regional continuity of the land value samples. Additionally, in this method, we propose some measurement indices of
evaluation results, which are wanting in traditional methods. At last, we evaluate the industry land value in Shanghai
with this method for instance.
The spatial data in GIS-T database is huge and complicated, discovery knowledge from this database is very
important, region traffic network evaluation is one of the important contents. In this paper the author referred
to an integrated algorithm combined Ant colony algorithm with FCM to cluster the traffic data of 15 regions
of Hubei Province, then used the method of maximizing deviation to arrange the clustering result. From the
result we can evaluate the traffic conditions of the 15 regions.
KEYWORDS: Web services, Databases, Human-machine interfaces, Data modeling, Data centers, Taxonomy, Data processing, Information fusion, Standards development, Data integration
Antarctica plays a key role in many scientific questions, of which those related to global climate change are probably the
most prominent examples. There are many researches on Antarctic are carried out at present, and some special institutes
sponsored by public and private communities are responsible for antarctica data management and maintenance.
Antarctic Spatial Data Infrastructure (AntSDI) [1]sponsored by SCAR's Standing Committee on Antarctic Geographic
Information (SC-AGI) is the one responsible for Antarctica spatial data maintenance and sharing by means of OGC
standard and specification. Antarctica Spatial Data Infrastructure (AntSDI) has already collected huge volumes of
geospatial data and offer an opening geospatial information service. In order to management and use Geospatial data
efficiently, and enable most of the users can access to Geospatical data and service at will, we firstly must registry data
and service into one or more registry center, then we should construct a building system which can supply users a
uniform interface to access data and service in registry center and user also can add their own data and service to system
and become part of system's capability. in this paper we present GeoAnt, a prototype interoperable AntSDI building
system. GeoAnt is a three-tier standard-based open geospatial web service system which fully automates data discovery,
access, and integration steps of the geospatial information discovery process under the interoperable service framework.
The paper discusses the system architecture, the individual components of the system and the use of the system in the
international project- Grove Mountains GIService Portal (GMGP).
KEYWORDS: Fuzzy logic, Data mining, Telecommunications, Geographic information systems, Analytical research, Roads, Databases, Neural networks, Binary data, Decision support systems
In GIS for Transportation (GIS-T), how to discover knowledge from complex traffic data is very vital. This paper focuses
on the regional traffic to evaluate the traffic condition in a certain region, which can provide decision-making support for
leadership. Nowadays, there are multitudinous regional traffic network evaluation models, most of which are based on a
single item of index. It is difficult to give a satisfying evaluation result to the whole regional traffic condition. In this paper,
we establish a regional traffic evaluation system for traffic network based on the theory of fuzzy clustering and maximizing
deviation, and evaluate the traffic networks of 15 regions in Hubei province in 2004.
The modeling and simulation method of Galileo E1-C intermediate frequency signal is proposed in this article. The
simulation results can be used for the further research of the Galileo receiver development and calibration of the core
skill of signal acquisition and tracking. And we program the software based on the model and give out the simulation
results. The results match very well with the theoretical ones.
KEYWORDS: Data modeling, Geographic information systems, Roads, Data storage, Composites, Associative arrays, Databases, Systems modeling, Bridges, Statistical analysis
The application, development and key matters of applying spatio-temporal GIS to traffic information management system are discussed in this paper by introducing the development of spatio-temporal database, current models of spatio-temporal data, traits of traffic information management system.
This paper proposes a method of organizing spatio-temporal data taking road object changes into consideration, and describes its data structure in 3 aspects, including structure of spatio-temporal object, organizing method spatio-temporal data and storage means of spatio-temporal data. Trying to manage types of spatio-temporal data involved in traffic system, such as road information, river information, railway information, social and economical data, and etc, uniformly, efficiently and with low redundancy.
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