Community remote sensing (CRS),a new approach to the application of remote sensing,is a human-based remote sensing technique. With activities of volunteers, this technique can compensate effectively for the disadvantage of traditional monitoring equipment of remote sensing. Based on abundant literatures of related topics,the authors described the status of the development of CRS that emerged in recent years,and discussed its potential for geoscience applications in such aspects as primary research contents,adopted techniques,application field and future prospect. The research indicates that, although the application of CRS has just started and is met with many problems,the carried-out-projects and applying practices have fully proved its great potential. In recent years,CRS has achieved important progress especially in such fields as ecosystem monitoring and disaster response. Its geoscience application, however, is relatively limited,showing a great space of developing in the future. CRS,as an emerging field of geoscience applications,might affect the future decadal development of new approaches to geosciences applications and hence deserves much attention.

The massive bloom of the green macroalgae Ulvaprolifera is called "green tide". The "green tide" event frequently happens in the world and is known as an oceanic disaster due to its bad effects on the marine ecological environment, coastal scene, seashore tourism and water sports. Remote sensing has the advantages over the conventional methods in oceanic monitoring because of its great capabilities of large-area, multi-resolution, multi-spectrum, quick and dynamic observations. Remote sensing has become a necessary method in the study of the origin, spatial pattern, evolution, size and movement of "green tide". At present, 3 main approaches detecting Ulvaprolifera have been developed, which are single band threshold image segmentation method, multi-band ratio method and radiation transmission model method. The multi-band ratio method is most widely used, which includes two-band ratio algorithm, normalized differential vegetation index, floating algae index and normalized difference algae index. The method of radiation transmission model is mainly used to monitor Ulvaprolifera suspended in water, and its study is just in the initial stage. Further researches on distinguishing the difference between the spectrum of Ulvaprolifera and other type of floating algae, monitoring Ulvaprolifera suspended in water, solving the contradiction between the deficiency of monitoring capability and the needs of users are the directions of Ulvaprolifera monitoring in the future.

In order to utilize the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products to detect the properties of Atmospheric Infrared Sounder (AIRS) cloud, this paper first adopted space collocation algorithm to match the MODIS and AIRS, and then combined the MODIS cloud classification mask, cloud phase mask products and the operational algorithm of MODIS cloud retrieval to realize the utilization of MODIS data to detect AIRS single field of the cloud (pixel cloud). The results show that MODIS 1km resolution products can realize AIRS cloud classification (lower, midlevel or high clouds) and cloud phase (water, ice or mixed-phase clouds) detection.

As the linear mixture model cannot well characterize the resultant mixed spectra due to the complicated relations between different ground objects and the effect of atmospheric scattering, a nonlinear spectral mixture model-secondary scattering model is proposed in this paper. Computer simulated images and AVIRIS hyperspectral images of Cuprite district in America were tested, and the experimental results show that the decompostion result of the proposed model are much more precise than that of the traditional linear spectral mixture model.

In this paper, the linear spectral mixture model (LSMM) was used for the spectral unmixing analysis of the Moderate Resolution Imaging Spectrometer (MODIS) data of the study area in Gurbantunggut desert. Using the spectral response function (SRF) of MODIS1-7 bands,the authors transformed the end-member spectrum quasi-synchronously collected by the full-band spectrometer (ASD) to the pixel spectra, thus generating the discrete spectrum of MODIS1-7 bands. Compared with the MODIS end-member spectra obtained by minimum noise fraction (MNF) transform and pixel purity index(PPI),the end-member spectral values of the first band of MODIS were much larger than the transformed spectrum values,but the spectral values of the MODIS2-7 bands were close to the transformed values. Therefore,selecting the image end-member spectral values of the MODIS2-7 bands,the authors used LSMM to estimate the abundance of snow in the sparse vegetation area appropriately. Fitting the estimated snow component value to the normalized difference snow index(NDSI),the authors found that a significant correlation exists between them after excluding MODIS1 band. The correlation coefficients show that the snow component can be a typical index of the snow cover.

In this paper, the effect of Aerosol Optical Thickness (AOT) on cyanbacteria bloom in the Taihu Lake was investigated, which could lay a foundation for dynamically monitoring cyanbacteria bloom. Moreover, a study of the elimination of the effects of AOT on the extraction results was carried out. MODIS products (MOD 02, MOD 04 and MOD 09) were chosen. Single band (NIR) and ratio vegetation index (NIR/G) were used to extract the spatial distribution of cyanbacteria bloom in the Taihu Lake in 2006. The effect of AOT was explored. A quantitative analysis of the degree of the effect of AOT on both the net changes of the area of cyanbacteria bloom and threshold selection was conducted. The results show that the correlation in the case of fixed threshold is higher than that of the demand threshold when the correlation of the area differences of cyanbacteria bloom and AOT is studied with single band and ratio vegetation index. In these two methods, the correlation without atmospheric correction is higher than that with atmospheric correction in the case of the corresponding value. This shows that the atmosphere will have some impact on the extraction of cyanbacteria bloom. Therefore, if cyanbacteria bloom information needs to be extracted accurately and reliably, AOT cannot be ignored. Also, if it cannot be completely eliminated, appropriate methods could be used to minimize its effect.

The fluctuations of atmospheric water vapor content in space and time, which will lead to an uncertainty propagation delay of the radar signal, is one of the main factors affecting the accuracy of InSAR. As a new sounding instrument, the foundation GPS can provide in real time continuous, all-weather, high precision precipitation water vapor values, which can be used for atmospheric correction of InSAR, nevertheless, it needs interpolation in space for using GPS water vapor observations to correct atmospheric delay in InSAR. Inappropriate interpolation methods will lead to distortion of the spatial distribution of water vapor. In conventional interpolation methods, such as inverse distance weighted (IDW) interpolation and Kriging, due to the failure to take account of the influence of topography on atmospheric delay, the interpolation results are not ideal. Therefore, this paper proposes an improved Kriging (IKriging) method, which can take into account the impact of elevation and distance on the atmospheric interpolation. The experimental results in Hong Kong show that IKriging has obvious advantages over the Kriging method. This method can be further promoted to establish the multi-factors fitting interpolation model.

Soil water content is an important indicator for monitoring agricultural drought. The thermal inertia method is one of the primary means for agricultural drought assessment in low vegetation cover. This study proposes an improved calculation of the thermal inertia model. With Agricultural Ecosystem Experimental Station of Chinese Academy of Sciences in Luancheng as a base, the authors measured the thermal inertia values with different vegetation covers and different soil water content concentrations in the experimental zone by measuring model parameters and on the apparent thermal inertia model. The purpose is to find whether the thermal inertia method is applicable to the inversion of the soil water content (NDVI threshold value). The validation results show that the monitoring of soil water content of the model is feasible with high precision when the vegetation cover is low (NDVI≤0.35). In high vegetation cover area (NDVI>0.35), the thermal inertia model fails, and hence the maximum thermal inertia approach to soil water content retrieval vegetation cover (NDVI) is set at 0.35. This method was applied to MODIS data obtained from Luancheng county, Zhaoxian county and Gaocheng city in the study area, and inversion of the area of soil water content was conducted. The results are consistent with the actual situation. Point artificial ground monitoring of soil water content yielded water content 25.1%, and the Luancheng station model calculations yielded 22.4%, suggesting good consistency. It is shown that the method has been applied well in the remote sensing data.

Phase unwrapping is one of the key technologies for the utilization of Interferometric Synthetic Aperture Radar (InSAR) to conduct DEM extraction and small surface deformation measurement. The conventional Kalman filter phase unwrapping algorithm can obtain reliable results in flat terrain areas, but it will cause error transmission and not make the accurate inversion of surface deformation information in the steep terrain. This paper presents a Kalman filter phase unwrapping algorithm of SAR Interferogram based on DEM. With the DEM topographic information obtained by the U.S. Space Shuttle Radar Topography Mission (SRTM) to guide SAR Interferogram and implement unwrapping, it can improve the speed and accuracy of unwrapping. A comparison with the conventional Kalman filter algorithm shows that the proposed Kalman filter phase unwrapping algorithm can achieve good results, especially in improving unwrapping accuracy in the low coherence region by using the SRTM DEM information to guide unwrapping.

The brightness temperature variation along the Ganzi-Yushu fault before and after 2010 Ms 7.1 Yushu earthquake was analyzed using MODIS data so as to obtain the infrared radiation variation information of the active fault related to the earthquake. It is shown that the value of the brightness temperature in one month before the earthquake was higher than that of other periods. The maximum variation was located at the northern end of the fault, where surface ruptures were found by field investigation. The obvious increase of brightness temperature was found during the 7-16 days after this event through an analysis of the data obtained from the seismic month at 10 day interval, and this might have had some relationship with the degassing of vapor and CO along the faults during the earthquake. For comparison, the data obtained in the same period of 2011 were analyzed. The results indicate that the brightness temperature of Ganzi-Yushu fault showed a homogeneous belt during the non-seismic time. The increase in brightness temperature of this fault was also found in May which might have had relationship with the Ms 5.3 Nangqian earthquake that occurred on June 26, 2011. It can be concluded that the variation of brightness temperature related to the fault zone can serve as an indicator of the fault activities. The study of the infrared radiation variation of main faults using satellite data is therefore significant for the monitoring of the seismic tectonic activity.

The conventional way to emend errors of rational polynomial coefficients (RPC) is carried out by a polynomial transform between metrical image point coordinates and projective point coordinates from ground points,but in such a performance,the number of parameters will increase,and the number of parameters changes along with the form of the polynomial,which increases the utilization difficulties. In this paper,the authors consider that the nature of RPC is analogous to that of the attached polynomial parameters,and therefore propose that the errors of RPC parameters can be eliminated by emending partial RPC. The experimental results show that the ideal point precision can be attained without using additional parameters,and the precision is better than that of the traditional means.

Based on analyzing the theory of the Optimum Band Combination, Principal Component Analysis (PCA) and NDISI, this paper presents an improved method, i.e., "experimental layer stack", to extract impervious surface of Taiyuan city, Shanxi Province, from Landsat TM image. Both unsupervised and supervised classification methods were used to classify the original multi-band image, PCA image, NDISI and experimental band combination images. The accuracies of the classification were assessed using 256 sampling points randomly selected from Google Earth high resolution image of Taiyuan. By comparison and analysis, the authors found that the experimental B combination method obtained the highest overall accuracy of 87.72% with the Kappa coefficient of 0.85.

In order to improve the remote sensing data classification accuracy of the environment and disaster monitoring and forecasting small satellite constellation 1A (HJ-1A) Star, the authors first fused hyperspectral imager data and CCD multispectral imagery by the Gram-Schmidt fusion algorithm, and then applied dimensionality reduction to the fused hyperspectral image by using principal component analysis (PCA) and kernel principal component analysis (KPCA). Gaussian, linear and polynomial kernel functions were employed during KPCA dimensionality reduction, and the polynomial kernel function was selected with its highest accumulative contribution rate according to the evaluation results of feature extraction. Finally, the fused hyperspectral image, the PCA image and the KPCA image with the polynomial kernel function were classified using the fuzzy C-means algorithm (FCM), respectively. The experimental results show that, for the fused hyperspectral image, the feature extraction based on KPCA can increase computational efficiency and improve the classification accuracy.

An image classification method based on the spatial relationship of image segment is proposed with the purpose of excavating the spatial relationship between image segments and compensating for deficiencies of the traditional image classification method based on spectral information. Image segmentation is used to get image segments for original image classification employing maximum likelihood (ML) method. Then the spatial relationship of image segments is described by Markov random field (MRF). Quantitative spatial relationship can be obtained by class adjacency matrix (CAM) so as to revise the result of classification. After that the iterated conditional mode (ICM) algorism for classification is presented, which can yield results with higher accuracy. Experimental results show that this method has been functioning well in classification experiments with high resolution remote sensing images.

Based on the theory of object-oriented image analysis, this paper carried out a multi-scale segmentation of SPOT5 image to obtain sea use objects at different spatial scales. By integrating objects'spectral, shape and context features to formulate detailed procedures of information extraction, areas of pond aquaculture were identified with classification accuracy better than 94%, indicating that the method of object-oriented image analysis is effective in the extraction of pond aquaculture information in coastal areas. It would promote the operational monitoring and management of sea use.

The image features of landslides with different kinds of geological conditions,types and runout distances show great difference in remote sensing images with different resolutions. For long-runout landslide and complex landslide,the available interpretation keys are few, so that the identification of landslide mainly relies on ground survey. On the basis of the achievements of landslide remote sensing investigation obtained both in China and abroad and the remote sensing investigation projects for geological hazards, the authors analyzed the remote sensing image features of typical landslides,including Daqingkan Landslide,Qianjiangping Landslide,Wulong Landslide and 102 landslide group in Tibetan region. Then,the interpretation keys to landslides,especially to the high-speed and long-runout landslides, were summarized for colleagues'reference.

Based on the Landsat TM/ETM⁺ remote sensing images from 1991 to 2009, the authors obtained the dynamic change of the West Kunlun glaciers as well as the Gozha Co and the Aksayqin Lake, with the climatic data, analyzed the change relationship between the glaciers, the lakes and the local climate in different regions. The conclusions of this paper are as follows: 1 In the period of 1991 to 2009, the West Kunlun glaciers were changing obviously, but the east part and the west part show different characteristics. That is, the glaciers of the east part firstly decreased, then increased, and decreased again. The change was fluctuated. However, the situation of the west part was different: the glaciers were decreasing continuously. Meanwhile the Gozha Co was firstly enlarged, then narrowed, and enlarged again while the Aksayqin Lake was narrowed continuously. 2 In the West Kunlun glaciers, there existed important interaction relationship between the Gozha Co and the Aksayqin Lake, showing an inverse ratio in quantity. 3 From 2000 to 2005, the main factor responsible for the difference in area between the West Kunlun glaciers and the lakes was the temperature. With the growing temperature, the area of the glaciers decreased while that of the lakes increased. The variation showed linear relationship.

The Guide- Gonghe-Tongde basin complex is located along the northeast marginal zone of the Tibetan Plateau. The Yellow River flows through these three basins. For understanding the tectonic and climatic indications of the fluvial erosion of the three basins since Holocene, the authors calculated the erosion quantity by using geological cross sections combined with digital elevation model (DEM). First, the points selected for the interpolation were picked out manually from a series of geological profiles. The minimum Pleistocene surfaces were reconstructed within the basins. This method reduced the error caused by the erosion after the deposition. Second, the erosion quantity and the erosion rates since Holocene were obtained by subtracting the modern elevation from the reconstructed surface. The results show that the erosion rate increased from upstream basin (Tongde basin) to downstream basin (Guide basin). The spatial erosion differences may indicate that the uplift of the margin of the Tibetan Plateau was greater than that of the inner part of the plateau.

The Duobuza deposit in Gaize of Tibet is one of the large-size porphyry copper deposits in Bangong Lake-Nujiang River mineralization zone found in recent years. The study of this typical deposit can provide good understanding for mineral deposit prognosis of this mineralization zone. In this paper, the spectra of samples in the Duobuza deposit were measured by using USA TerraSpec spectrometer, and at the same time, the microscopic identification of the samples was conducted. The results show that the main alterations in this deposit are phyllic alteration and epidotization, and the main mineralizations on the surface include limonite, malachite and azurite. The spectra of two kinds of granodiorite-porphyry are different. The spectrum of granodiorite-porphyry related to mineralization shows distinct phyllic alteration, and the spectrum of granodiorite-porphyry which is not related to mineralization shows little or non alteration, distributed around the first kind of granodiorite-porphyry. The spectra of the samples measured by using TerraSpec are consistent with the spectra of ASTER image. Finally, the phyllic alteration area which has close relationship with the mineralization was delineated based on the spectral analysis, and these areas are considered to be more important prospecting areas in the future.

Fractal theory could provide quantitative basis for such aspects of the basin as its complex landform and its development process. For further study of river fractal dimension, the authors extracted the river networks of Golmud River basin on the basis of the ASTER-GDEM data and according to different confluence accumulation thresholds. Using the hydrologic analysis model of geographic information system, the authors calculated the corresponding river fractal dimension with the box dimension method so as to describe the topography characteristics of the valley and predict the evolution trend of drainage landform. The results show that, in some non-standard ranges, concentration accumulation thresholds fit fractal dimensions well. The fractal dimension values of Golmud River basin are approximately between 1.6 and 1.8, suggesting that this basin is in the mature stage of geomorphological erosion and tends to develop into the late mature stage. The terrain rises and falls greatly with the fragmentation of the ground. The erosion of rivers is mainly lateral,and the down-cutting is relatively weak. This conclusion is in consistency with the calculation result of the hypsometric integral.

By using TM imagery as the raw data in this paper, the authors first classified the objects of the study area into three classes, i.e., impervious surface (IS), vegetation, and water based on the algorithm of OTSU, and retrieved land surface temperature (LST) of the study area by using the mono-window algorithm. Then, the study area was separated into 45 pieces by setting a multi-level buffer in a discriminating scheme, which was based on the distance between each pixel and the center of Nanjing, and the work of statistics and analysis was carried out for the mean temperature of all pixels, the mean temperature of IS, the mean temperature of vegetation, and the mean temperature of water in each buffer. Finally, the authors set up the relational models between LST and the area ratio of IS, LST and the area ratio of vegetation, LST and the area ratio of water. The results showed that the land surface temperature decreased obviously with the increasing distance from the city's center. Vegetation and water could reduce the temperature in central city proper, and the cooling effect of water is 2.43 times that of vegetation. The integrated relational model between LST and the area ratio of IS, the area ratio of vegetation and the area ratio of water was performed well.

Using RS and GIS technology,the authors analyzed the regularity and causes of water erosion desertification in Yunnan Province and put forward the prevention measures.Studies show that the area of water erosion desertification is 35 949.69 km²,accounting for 9.39% of the total land in Yunnan Province.The overall spatial distribution of erosion desertification is determined by geological environment,topography and other natural factors,and is also triggered and exacerbated by human factors.It is suggest that water erosion desertification prevention work should give priority to such regions as mudstone,claystone,carbonate rocks,Quaternary sediments,the vicinity of the south section of Jinsha River - Honghe River fault zone and other six active faults in the typical eastern and central Yunnan plateau middle mountain type landforms.The existing ecological environment protection projects should be improved,the population pressure should be reduced,and the mining and other industrial activities should be regulated to avoid inducing and exacerbating erosion desertification.

The spatial variation of Chongming Dongtan wetland was monitored using 10 remote sensing images including Landsat MSS, TM and ETM⁺ data. Nine nautical charts were employed to analyze the evolution of underwater terrain from 1951 to 2006. With the above/under water topographic changes as an entirety, the authors made quantitative and qualitative analysis of geomorphic evolution in the past 60 years at Chongming Dongtan wetland using waterline method and depth contour overlaying. Some conclusions have been reached: ① The dynamics of Chongming Dongtan tend to be stable, characterized by erosion in the south part, deposition in the north, rapid propagation in the middle and alternate erosion and deposition in some coasts under the stabilities of the current Yangtze estuary; ② Human activities made important effect on the wetland. Especially, damn in the Baigang tidal channel accelerated deposition in the wetland. Then the 0 m isobath expanded to the east at a stable rate. Although the wetland area was increasing with the human reclamation year by year, the inter-tidal structure of wetland was deviated from the nature state. The proportion of high tidal flat was decreasing and it showed discontinuous spatial distribution at Chongming Dongtan. Because the damn was directly exposed to the outside marine environment, it would reduce the capability of disaster weather prevention.

This paper evaluated 3 Chinese-made satellite images for extraction of land use information in macroscopic monitoring in 6 typical counties with varied topography characteristics. The authors compared many classification methods and analyzed the impacts of training samples, classification methods, and feature data on classification accuracies. It is found that the simple MLC method can acquire better accuracy, whereas the object-oriented method can improve the accuracy for HJ-1 and BJ-1. For CBERS-02B, the MLC classification accuracy tended to be stable and the Kappa coefficient was above 0.8 when the training samples reached 50. For HJ-1 and BJ-1, the classification accuracy tended to be stable when the training samples reached 60 and the Kappa coefficient was above 0.7. The feature data (i.e. NDVI and DEM) can improve the classification accuracy for CBERS-02B, and DEM can improve the accuracy for HJ-1 and BJ-1. The authors suggest integrating multiple Chinese-made satellite images for acquiring valid images all over the country in macroscopic monitoring. The findings provide scientific basis in accuracy and methods for the macroscopic monitoring.

In order to explore the degree and spatial distribution of landscape ecological security in Longyan City, the authors constructed the ecological security assessment index system of Longyan City based on the "pressure-state-response" conceptual model. And the landscape ecological security comprehensive index distribution in 2001 and 2008 was overplayed by means of multi-temporal remote sensing images, GIS techniques and landscape ecological theory. The results showed that, with the increasing of the outside pressures, landscape structure was stable, and landscape vigor and ecological status were both at a good level. The mean value of landscape ecological security index was 7.27 in 2001, which was located at the high level, while in 2008 the index was 6.65, which was at a medium level. Therefore, it is concluded that the landscape ecological security of Longyan City experienced a slight deterioration during the study period. In order to improve the urban landscape ecological security, the authors suggest optimizing the land use pattern in the future urban planning and construction.

In order to extract area information of the mine development based on processed IKONOS remote sensing data, the authors built 2 bands experience calculation formulas and 2 density segmentation functions after analyzing the spectral features of spectrum sampling data. First, density segmentation functions are used to extract the area information as a whole, which eliminates the background interference, and then the whole area information is divided into smaller pieces, which are then given specific types of meaning standing for the specific use of the area according to visual interpretation. Outdoor verification shows that using computer to extract information of area occupied by mine development can make up the deficiency of the visual interpretation, such as saving human, material and financial resources and time. The extracted information is accurate and has practical significance, and is of reference values for extraction of information concerning land possessed by mines in similar areas.

Small tailing ponds take up 80 percent of China's tailing ponds and have caused severe influence on the environment. Using WorldView-2 high resolution image as data source, the authors extracted the tailing ponds in Chengui town with visual interpretation method. There were 74 small tailing ponds, occupying 58.95 hm². With the nearest distance method, the authors drew a conclusion that the degree of the four ground features affected by pond hazard was in order of road > water > farmland > residential area. Then the DEM of Daye City was selected to simulate the river system and contour profile information, and extracted the data of the hierarchical river stream and catchment watershed. With the watershed as a unit, the area of the environment impacted by the small tailing ponds was marked off, and the acreage area reached 59.96 km². Combining the watershed analysis data with the distribution characteristics and law of the small tailing ponds, the authors further analyzed the effect of the small tailing ponds on the environment, thus providing valuable references for the relevant departments to reinforce environmental supervision and ecology management of the small tailing ponds. It is shown that the remote sensing technology will play an important role in the analysis of distribution characteristics and environmental effect of the small tailing ponds.

In view of the increasing man-made damage situation,the authors employed the high resolution satellite QuickBird-2(resolution 0.61 meters) and IRS-P6(resolution 5.6 meters)remote sensing data and utilized ENVI and MAPGIS software to conduct remote sensing investigation of the part of Guilin city through which the Lijiang River is flowing, and the survey area covered both banks of the Lijiang River between Lanzhou Bridge and Mopanshan Bridge about 30 km in length. Through remote sensing image processing, analysis and human-machine interactive interpretation, the authors made measurement and statistical analysis of three kinds of man-made damage. The results show that until 2009, the natural landscape area had accounted for 6.27% of the whole investigated area, agriculture and forestry land accounted for 57.78% and land for construction accounted for 35.95%. These data suggest that, with the rapid expansion of the Guilin city, Human activities caused serious damage to the Lijiang River's natural landscape, and hence the comprehensive treatment and harnessing of the Lijiang River are urgent.

Based on analyzing the characteristics of spatial data in combination with current spatial data storage technology, this study implements the organization and management of multi-source spatial data and builds the Multi-source Spatial Data Management System. For implementing the system, this study solves the problems of spatial data thematic diversity and data exchange by extending the metadata standards, solves the issues like large amounts of data, distributed source and heterogeneous data format using single machine multiple SDE data storage technology, and finally, in order to solve the problem of fast retrieval localization of spatial data, systematically builds the spatial index database based on single machine multiple SDE. The system lays a good foundation for solving thematic diversity, data sharing and exchange which will be met in the information platform construction of multi-source spatial data for the applications of resource and environmental remote sensing data.

With the application of GIS spatial analysis method, a 3D visualization and early warning system is designed and developed for new generation Doppler meteorological Radar data based on the technology of ESRI ArcGIS Engine and Microsoft VB.net. This system has the main functions of automatic coordinate conversion, statistic and dynamic analysis, 3D visualization, automatic early warning, emergent communication, and special charting associated with geographic information. 3D visualization can provide weather forecasters with detailed terrain information. For the first time, the automatic early warning model is built for the application of Doppler meteorological Radar data, which is based on GIS spatial analysis. The results show that this system can provide a powerful support for refined short-time weather forecasting.