Electromagnetic radiance acquired by sensors is distorted mainly by atmospheric absorbing and scattering. Atmospheric
correction is required for quantitatively analysis of remote sensing information. Radiation transfer model based
atmospheric correction usually needs some atmospheric parameters to be chosen and estimated reasonably in advance
when atmospheric observation data is lacked. In our work, a radiometric calibration was applied on the satellite data
using revised coefficients at first. Then several parameters were determined for the correction process, taking into
account the earth's surface and atmospheric properties of the study area. Moreover, the atmospheric correction was
implemented using 6S code and the surface reflectance was retrieved. Lastly, the influence of atmospheric correction on
spectral response characteristics of different land covers was discussed in respects of the spectral response curve, NDVI
and the classification process, respectively. The results showed that the reflectance of all land covers decreases evidently
in three visible bands, but increases in the near-infrared and shortwave infrared bands after atmospheric correction.
NDVI of land covers also increases obviously after atmospheric influence was removed, and NDVI derived from the
surface reflectance is the highest comparing to that from the original digital number and the top of atmosphere
reflectance. The accuracy of the supervised classification is improved greatly, which is up to 87.23%, after the
atmospheric effect is corrected. Methods of the parameter determination can be used for reference in similar studies.
The methods of segment-based image analysis are becoming more and more important for remote sensing as a result of
the progresses in spatial resolution of satellite image. An approach to segmentation of IKONOS panchromatic image
based on frequency domain filtering and marker-controlled watershed transform is presented in the paper. Primarily the
texture and edge features are extracted from the response of log Gabor filtering. The texture features are obtained from
the amplitude response, and phase congruency is introduced as a new method to detect invariant edge features. Then an
approach to combining texture with edge features is presented and used to implement the marker-controlled watershed
segmentation. Combination of different frequency texture features is used to mark different complicated images. Finally
empirical discrepancy is calculated to evaluate the segmentation results. It shows that the precision of right segmentation
is up to 80~85%. The approach presented in the paper basically satisfies the demand of feature recognition and extraction
of high-resolution remotely sensed imagery.
During the last decades, researchers have mainly focused on improving of the pixel-based classification methods and their applications. As the image resolution improved, it can't get good classification result. In order to overcome this problem, the object-oriented approaches are introduced. In this paper, two methods were compared on urban area. A part of Nanjing city in china was selected as study area; TM and IKONOS imagery were employed. Three pixel-based classification methods, the maximum likelihood, ISODATA (Iterative Self-Organizing Data Analysis Technique), minimum distance method, and an object-oriented technique, the nearest neighbor method, were used to classify image, and evaluate the result. For TM imagery, the accuracy assessment of the results showed that the object-oriented classification approach couldn't get better classification result comparing to the pixel-based classification method, the salt-pepper phenomena of the pixel-based classification result images were not obvious. For IKONOS imagery, classification results provided by the object-oriented classification method were better than the pixel-based classification approaches. So, for urban classification using TM imagery, the traditional classification method could be used to get classification information and an acceptable result could be acquired. But when the IKONOS imagery was used to investigate the urban class, the object-oriented method could find the expected result.
KEYWORDS: Data modeling, Databases, Java, Geographic information systems, Data integration, Data storage, Standards development, Cognition, Spatial analysis, Integration
Time and space are ubiquitous aspects of reality. The spatio-temporal data is our cognition to external matter and the spatio-temporal data model is the theoretical foundation to manage the spatio-temporal data. But now the research of the spatio-temporal data model still is on the stage of theoretical research and can not implement the real application. Those how to uniformly manage the Spatio-Temporal multi-data source and different structure data and how to implement the Spatio-Temporal data model practically need to be crucially solved. We use the principle and the construction idea of the data engine for reference, build the spatio-temporal data engine by applying the notion and function of the data engine into the theory of the Spatio-Temporal data model and then use the Spatio-Temporal data engine to implement the application of the spatio-temporal data. The article mainly introduces the construction idea, the design, the implement of the spatio-temporal data engine and provides the example of using the spatio engine--ArcSDE to implement the application of the spatio-temporal data which explains our thinking of implementing the spatio-temporal data engine. The article is an attempt to resolve how to effectively and uniformly manage the Spatio-Temporal multi-data source and how to make the Spatio-Temporal data used in practice.
KEYWORDS: Data modeling, Databases, Composites, Inspection, Geographic information systems, Process modeling, Roads, Systems modeling, Computer programming, Geoinformatics
A framework to express the changes and the causalities within the object's evolution is proposed based on a general inspection of the interactions among the Spatiotemporal Objects (STOs). Why the STOs can evolve is that they can exchange the material, the energy and the information mutually. The result of their evolution is the changes of their features and mechanism. Feature changes can be categorized into 2 levels: the changes of the feature statuses and the changes of the feature structures. The former result in just the increment of the data quantity of the database, the later can furthermore result in the increment of data structures defined in the database. Any a change of a STO is caused directly by a behavior of either itself or another STO. Feature changes can be directly expressed by spatiotemporal data or data structure, but the mechanism changes of a STO can only be indirectly reflected by its feature and behavior description. The proposed framework consists of five key elements: the essence, the features, and the behaviors of the STO, the information flow and the material flow within the spatiotemporal interactive process.
KEYWORDS: 3D modeling, Visualization, 3D displays, Internet, Java, Tin, Systems modeling, 3D visualizations, Analytical research, Visual process modeling
With the singular development of Internet technique and 3DGIS as well as VR and the imminence demand of 3D
visualization from Groundwater information management field, how to display, roam, anatomize and analyze of 3D
structure of Groundwater system on Internet have become a research hotspot in hydrogeology field. We simulated the 3D
Groundwater resource structure of Taiyuan basin and implemented displaying, roaming, anatomizing and analyzing
functions on Internet by Java 3D.
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