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Bachground: The existence of cloud pixels reduces the practicability of optical satellite remote sensing data. Existing problems: Existing cloud reconstruction methods generally cannot solve the following problems:(1)Large-scale thick cloud cannot be well reconstructed. (2)There are high requirements for reconstructed data. (3)Most data used to reconstructed are single temporal images. Ways: In order to overcome these problems, a new multi temporal weighted aggregation method is proposed. Specifically, we adopt a multi-temporal iterative aggregation method for cloud pixels to reconstruct and a multi-temporal weighted aggregation method for cloud shadow pixels to reconstruct. Result: Finally, the experiment proves that our method can quickly and accurately complete the cloud reconstruction, and under the effective uniform color strategy, a cloud- free image with accurate geometric position and uniform gray scale can be obtained. Conclusion: Experiments prove that the pixel reconstruction method proposed in this paper has achieved good cloud and cloud shadow pixel reconstruction effects in different types of ground objects.

The high-precision geometric positioning of optical remote sensing satellites is the prerequisite to determine the application capability of satellite image products. Its positioning accuracy is related to the observation accuracy of each link in the imaging process, including satellite attitude, orbit measurement accuracy, time synchronization accuracy, camera measurement accuracy, and so on. Untimely and inaccurate on-orbit calibration will lead to great geometric positioning errors. To optimize the positioning accuracy of satellite images with the rational function model (RFM) under low positioning accuracy, our paper proposes an improved geometric quality model based on the reorientation of internal and external orientation elements in the RFM model of remote sensing images. By establishing the rational function positioning model, the external orientation model, and the internal orientation model, the original image can be reorientated. Then, we use the improved model to generate uniformly distributed virtual ground control points. By analyzing and verifying the relationship between each rational polynomial coefficient (RPC) and its influence on geometric positioning accuracy, we propose an RPC coefficients optimization method based on image offset correction and positioning dominant coefficients. Finally, we use the small satellite “MN200Sar-1” with low geometric accuracy for experimental verification. The results show that the model can effectively eliminate the errors of internal and external elements in the on-orbit calibration, and the positioning accuracy is improved from one hundred pixels to one pixel. At the same time, the rational polynomial dominant coefficient optimization method can improve geometric positioning accuracy without introducing additional compensation parameters.

The emerging satellite videos provide the opportunity to detect moving objects and track their trajectories, which were not possible for remotely sensed imagery with limited temporal resolution. So far, most studies using satellite video data have been concentrated on traffic monitoring through detecting and tracking moving cars, whereas the studies on other moving objects such as airplanes are limited. In this paper, an integrated method for monitoring moving airplanes from a satellite video is proposed. First, we design a normalized frame difference labeling (NFDL) algorithm to detect moving airplanes, which adopts a non-recursive strategy to deliver stable detection throughout the whole video. Second, the template matching (TM) technique is utilized for tracking the detected moving airplanes in the frame sequence by improved similarity measures (ISMs) with better rotation invariance and model drift suppression ability. Template matching with improved similarity measures (TM-ISMs) is further implemented to handle the leave-the-scene problem. The developed method is tested on a satellite video to detect and track eleven moving airplanes. Our NFDL algorithm successfully detects all the moving airplanes with the highest F1 score of 0.88 among existing algorithms. The performance of TM-ISMs is compared with both its traditional counterparts and other state-of-the-art tracking algorithms. The experimental results show that TM-ISMs can handle both rotation and leave-the-scene problems. Moreover, TM-ISMs achieve a very high tracking accuracy of 0.921 and the highest tracking speed of 470.62 frames per second.

In recent years, satellites capable of capturing videos have been developed and launched to provide high definition satellite videos that enable applications far beyond the capabilities of remotely sensed imagery. Moving object detection and moving object tracking are among the most essential and challenging tasks, but existing studies have mainly focused on vehicles. To accurately detect and then track more complex moving objects, specifically airplanes, we need to address the challenges posed by the new data. First, slow-moving airplanes may cause foreground aperture problem during detection. Second, various disturbances, especially parallax motion, may cause false detection. Third, airplanes may perform complex motions, which requires a rotation-invariant and scale-invariant tracking algorithm. To tackle these difficulties, we first develop an Improved Gaussian-based Background Subtractor (IPGBBS) algorithm for moving airplane detection. This algorithm adopts a novel strategy for background and foreground adaptation, which can effectively deal with the foreground aperture problem. Then, the detected moving airplanes are tracked by a Primary Scale Invariant Feature Transform (P-SIFT) keypoint matching algorithm. The P-SIFT keypoint of an airplane exhibits high distinctiveness and repeatability. More importantly, it provides a highly rotation-invariant and scale-invariant feature vector that can be used in the matching process to determine the new locations of the airplane in the frame sequence. The method was tested on a satellite video with eight moving airplanes. Compared with state-of-the-art algorithms, our IPGBBS algorithm achieved the best detection accuracy with the highest F1 score of 0.94 and also demonstrated its superiority on parallax motion suppression. The P-SIFT keypoint matching algorithm could successfully track seven out of the eight airplanes. Based on the tracking results, movement trajectories of the airplanes and their dynamic properties were also estimated.

To realize the application of super-resolution technology from theory to practice, and to improve microsatellite spatial resolution, we propose a special super-resolution algorithm based on the multi-modality super-CMOS sensor which can adapt to the limited operation capacity of microsatellite computers. First, we designed an oblique sampling mode with the sensor rotated at an angle of 26.56 ∘ ( arctan 1 2 ) to obtain high overlap ratio images with sub-pixel displacement. Secondly, the proposed super-resolution algorithm was applied to reconstruct the final high-resolution image. Because the satellite equipped with this sensor is scheduled to be launched this year, we also designed the simulation mode of conventional sampling and the oblique sampling of the sensor to obtain the comparison and experimental data. Lastly, we evaluated the super-resolution quality of images, the effectiveness, the practicality, and the efficiency of the algorithm. The results of the experiments showed that the satellite-using super-resolution algorithm combined with multi-modality super-CMOS sensor oblique-mode sampling can increase the spatial resolution of an image by about 2 times. The algorithm is simple and highly efficient, and can realize the super-resolution reconstruction of two remote-sensing images within 0.713 s, which has good performance on the microsatellite.

This is the first study to inverse leaf area index (LAI) with photon counting LiDAR (i.e., Ice, Cloud, and Land Elevation Satellite-2/Advanced Topographic Laser Altimeter System, ICESat-2/ATLAS). A new framework composed of three major steps was applied: noise removal algorithm, photon classification algorithm, and the LAI estimation model. To evaluate the feasibility and accuracy of ICESat-2 derived LAI, the MODIS (Moderate Resolution Imaging Spectroradiometer) LAI product at the spatial resolution of 500-m over two sites (Amazon rainforest and Daxing’an mountains forests) were selected for comparison purpose. The results show satisfactory agreements (Amazon: R=0.693, RMSE=2.545; Daxing’an: R=0.626, RMSE=1.893; Two sites together: R=0.667, RMSE=2.433) between MODIS LAI and ICESat-2 derived LAI. Moreover, we also selected the LAI derived from Sentinel-2 to further validate the ICESat-2 derived LAI, and got better results than MODIS LAI (Amazon: R=0.752, RMSE=2.329; Daxing’an: R=0.704, RMSE=1.724). Our study found that: (1) The new applied framework can effectively inverse LAI with ICESat-2. (2) The ICESat-2 derived LAI are reliable. (3) ICESat-2 exists many advantages over MODIS in terms of LAI estimation, for example, it not only can alleviate the issue of saturation of MODIS when LAI is high, but also can mitigate the problem of poor inversion effect of MODIS where the vegetation types are diversity.

The paper builds a model of marine fishing vessel early-warning based on principle of Negative selection algorithm of artificial immune system and Fishing Boat Accident Case Library. Firstly, the index weight of model was calculated by using BP neural network algorithm. Then, the model of fishing vessel early-warning based on artificial immune system was built and tested, through steps of data encoding, affinity calculation, threshold determination, and creating warning detector. 80% warning success rate proved this model has good warning effect.

The Clue of this paper is the data of marine environmental early warning service platform, and our research basis includes data classification, database index table, structure design and data consistence. The normalized data which is realized by ETL is ported in automatic drawing template, and use the pre configured symbol library, color library and pixel library to the marine environment early warning signs product data to automate the project, in order to realize the no manual intervention of the marine environmental warning signs product automatic template mapping. And then we release the marine environmental early warning products to achieve our goal which is the process of data batch input and output by ArcGIS Online based marine environment early warning product release database. Introduction In China, the coastal area is able to become the country's most economically developed regions, there is a factor cannot be ignored---the ocean, which not only provides a very rich natural resources for the coastal areas, but also creates a favorable climate environment as well as a convenient and efficient international access. In the last 20 years, China's marine industry is thriving. As the most important growth point of China's economic development in the present and in the future, the marine economy is much higher than that of the coastal zone. However, any coin has two sides. The rapid development of coastal zone and marine economy has intensified the economic loss rate of marine disasters. Therefore, as a kind of effective technology to deal with the marine disasters, marine disaster early warning platform should be studied urgently. The standardization and database design of marine environmental data Marine environmental data as the core of marine warning, there are significant differences between its type and format. It has multi service, multi time, multi domain, mass and other characteristics. Based on the relevant standards and norms, this paper studies the database classification system of marine environmental warning system. The information classification method is applied to the database. A unified database naming standard is formulated for the platform of marine environmental warning system, and the multi ocean data are normalized. On the basis of this, the design of the platform of the marine environmental warning system is carried out. The analysis of data format In the framework of the spatial database of marine early warning, it can be divided into three main parts, the basic database, the intermediate database and the published database. The product database of marine environmental warning involving a total of 8 kinds of special forecasting data, which consist of the wind field module group, sediment module group, rescue module group , temperature and salt flow module group and oil spill module, storm surge module group, coastal 5th International Conference on Computer Sciences and Automation Engineering (ICCSAE 2015) © 2016. The authors Published by Atlantis Press 467 wave modu in details: The data o The detail The pr into three database. T Line, Raste relationship The ETL o ETL is different d achieve th built-in lib complex co theme of th source, and be represen

General marine environmental early warning data have not formed a unified standard, due to the different angles and dimensions in expression of marine environment. General formats of these data are text type, binary type, and mixed type. These data types cannot be read and processed by the GIS platform, so it is necessary to normalize these data to standard format supported by GIS platform. This paper studied the visualization system for marine early warning products which based on MFC framework and Arc Engine development kit and used GDAL and NetCDF function libraries, solved the problem of heterogeneous data sources and realized data production, results presentations, automatic drawing, 3D profile analysis and other functions. It will provide convenience for the comprehensive operation of different types data and improve the visual expression effect for marine early warning products and marine management at the same time. Introduction General marine environmental early warning products include the wind field, three-dimensional thermohaline circulation, storm surge, salt water intrusion, sediment and other numerical early warning products. Due to the non-uniform of the product formats and the different calculation modes, the data analysis and process will encounter various difficulties. Both the establishment of unified operational framework and research of a variety of visualization methods are imperative. Rufu Qin [1] proposed solution that building mixed GIS system for the multi-dimension marine geographic data. Xinfang Li [2] constructed the marine environment visual simulation system by using open source OpenSceneGraph and ArcGIS data process tools. Lingda Wu [4] researched parallel visualization of large scale 3D scalar field. Zhe Bi [5] developed a marine GIS system based on ArcObject, and described the use of AO Library. Jie Huang [6] described the method of spatio-temporal model and visualization for marine environment integrated data. Wenwen Jiang [7] described the method of data formats and data process for marine environment. Jun Gao [9] discussed the modeling of visualization for geospatial data and the role of GIS in the visualization. Chao Tu [10] researched 3D visualization for the ocean temperature field. In the above researches, there is no research on the normalization of the marine currents field data and then building the visualization system for marine early warning products based on GIS. The paper studied the visualization system for marine early warning products. This study solved the problem of heterogeneous data sources. It will provide convenience for the comprehensive operation of different kinds of data and improve the visual expression effect of marine early warning data and marine management at the same time. Analysis and process for marine early warning data Marine environment is a complex giant system, which is multi-coupling, multi-factor, and time-varying. Description, expression and reproduction for the marine environment requires a variety of monitoring platforms and a variety of data acquisition and process which means to cooperate with each other. At present, the basic marine information provided by China includes the 5th International Conference on Computer Sciences and Automation Engineering (ICCSAE 2015) © 2016. The authors Published by Atlantis Press 461 following types: hydrological data, marine biological data, meteorological data, marine stations data, marine chemical data, geophysical data, ARGO data, Modis and other satellites data. Marine environmental early warning data is particularly important in a great deal of marine data due to its dynamic and predictive characteristics. General marine environmental early warning data include wind field, three-dimensional thermohaline circulation, storm surge, salt water intrusion and sediment data. These data have not formed a unified standard, due to its different angles and dimensions in expression of marine environment. General formats of these data are text type, binary type, and mixed type. These data types cannot be read and processed by the GIS platform, so it is necessary to normalize these data to standard format supported by GIS platform. This study selects the ESRI shapefile format as the standard format. The conversion of NetCDF storage format of three-dimensional thermohaline circulation vector data will be described to illustrate the process of data normalization. Data format analysis of NetCDF The full name of NetCDF is Network Common Data Form. NetCDF is a kind of self-explanatory, cross platform data storage and exchange format, which is suitable for scientific data sharing. The data of three-dimensional thermohaline circulation is usually three dimensional data with early warning cycle for one day, which contains three kinds of factors: temperature, salinity and marine current. General data storage format of three-dimensional thermohaline circulation is NetCDF format, opening the NetCDF data through the MeteoInfo software to read the metadata information. The main metadata types include nele node number, node node number, data layers, dimension, time, data length, etc. Process of normalizing data formats It is difficult to use hierarchical color to render vector field directly. The wind field and the wave field are the general vector fields of marine, which are usually stored in NetCDF format that need to be processed and normalized. Data normalization process is as follows

Phase unwrapping is a key step in InSAR (Synthetic Aperture Radar Interferometry) processing, and its result may directly affect the accuracy of DEM (Digital Elevation Model) and ground deformation. However, the decoherence phenomenon such as shadows and layover, in the area of severe land subsidence where the terrain is steep and the slope changes greatly, will cause error transmission in the differential wrapped phase information, leading to inaccurate unwrapping phase. In order to eliminate the effect of the noise and reduce the effect of less sampling which caused by topographical factors, a weighted least-squares method based on confidence level in frequency domain is used in this study. This method considered to express the terrain slope in the interferogram as the partial phase frequency in range and azimuth direction, then integrated them into the confidence level. The parameter was used as the constraints of the nonlinear least squares phase unwrapping algorithm, to smooth the un-requirements unwrapped phase gradient and improve the accuracy of phase unwrapping. Finally, comparing with interferometric data of the Beijing subsidence area obtained from TerraSAR verifies that the algorithm has higher accuracy and stability than the normal weighted least-square phase unwrapping algorithms, and could consider to terrain factors.

With the rapid development of rural socio-economic in China, multi-source statistical information is one kind important data to enhance decision-making for government. The rural has become a major problem. In this paper, a set of GIS spatial analysis methods of rural social-economic data were proposed and researched on, spatial data and statistical data were integrated to create a comprehensive spatial database to realize data sharing with existent e-government system. On this basis, a GIS based rural socio-economic statistical system is constructed using COM pattern and put into effect in National Bureau of Statistics of China. It is proved that GIS technology applied in rural statistics department, which provides an information platform that manage and analyze statistical data and spatial data, is feasible and efficient.

With the rapid development of database technique and computer technology nowadays, it is no longer a difficult problem to manage mass statistical data with computer and database system. However, from the statistical mode and time series of rural socio-economic statistical survey, we know that the statistical data have both spatial and temporal attribute, so the traditional systems have no enough ability to manage and analyze the statistical data with spatio-temporal attribute. In this paper, on the basis of the former research and the real demands of rural socio-economic statistic department, four key techniques about the construction of spatial management and analysis system for rural socioeconomic statistic data were designed. Based on the statistical spatio-temporal database, historical statistical data spatio-temporal division, statistical model library, exploratory spatial statistical analysis method techniques, the integrative operational system was realized for spatio-temporal data management, analysis and thematic mapping or expression. It could be utilized in many aspects of operational work of rural socio-economic statistic administration.

This paper aims to introduce a case of Socio-economic statistical Spatio-temporal Database. This database system services in the rural socio-economic statistical work, which is a combination of statistical tables, spatial data, search algorithm and maintenance interface. Administrative codes are the conjunction media of spatial data and attribute data, and also are the key words of database query processing. Through storing the changing information in the database, it could reflect the change of administrative divisions. As the main issues of database design, the studying of the approach to recording and querying these changes as well as the processing of statistical data by the rules of administrative divisions changes, requires a large amount of research work. To address these problems, a series of management analysis tools have been developed to deal with the processing of socio-economic statistical data with changes in the administrative division. A searching algorithm of spatio-temporal database is used to ensure the comparability of the results, which are acquired by the positive sequence and the anti-sequence temporal query under complex spatial changes in the administrative division. According to the spatial changes, searching algorithm of spatio-temporal database mainly translates temporal series statistical data into standard format data which is matched to the benchmark year. The searching algorithm controls the process of inquiry through recursion of the table of the administrative code changes, which are composed of multi-way tree structure and double linked list and record the relationship between upper and lower level administrative units. These search algorithms and meta-data storage structures constitute the spatio-temporal database, so as to serve the spatial analysis of statistical data. The comparability problem mentioned above was well solved by this approach. And a set of functions was provided by this system with spatio-temporal database, such as specialization of statistical data, temporal query, spatial data which can be automatically updated, and maintenance interface.