In order to investigate the differences between domestic and foreign commercial RS satellites, evaluate the capability of data provision, data acquisition and application effect, measure the extent of their achieving the basic needs of RS in China, the authors conducted a comprehensive investigation and statistic analysis of RS satellites used in China and abroad and set some indices, such as satellite type, band coverage and satellite resolution, with the purpose of making quantitative analysis and comparison of the capability of domestic and foreign satellites. The results show that the types of domestic satellites and spectra are relatively complete, but the number of satellites is less and the band coverage of domestic satellites is less than that of foreign satellites. In addition, the gap of capability of obtaining ultra-high spatial resolution image between domestic and overseas RS satellite is relatively large, and China lacks decimeter level resolution RS satellites. As for application effect, the number of papers on CNKI about the foreign satellites is five times that about domestic satellites. In each field, the utility ratio of single domestic satellite is lower in comparison with that of the foreign satellite. Nevertheless, domestic satellites have higher application potential than foreign satellites in some aspects, and hence they will play a powerful role in the future.

Quantitative inversion of the main lunar mineral abundance is an important issue in the field of lunar science, which has great guiding effect on lunar mineral information interpretation in the future. In this paper, a method of linear unmixing for hyperspectral remote sensing image is proposed to obtain the mineral abundance. Firstly, based on Hapke radiative transfer model, the authors transformed the non-linear mixed reflectance spectra into the linear mixed single scattering albedo of five end-member minerals (clinopyroxene, orthopyroxene, plagioclase, olivine and ilmenite) in the Relab spectral library, and then generated mixed pixels according to the linear proportion randomly; in this way, the statistical relationship models of mineral unmixing abundance and real abundance for the above five minerals can be established respectively based on fully constrained linear-unmixing method. The verification result with the data measured by Apollo sampling points indicates that the correlation coefficient between mineral abundances inversed and measured in Apollo of pyroxene, plagioclase, olivine and ilmenite are 0.83, 0.86, 0.72 and 0.77 respectively. With this method, the authors acquired the lunar mineral abundance distribution maps in Sinus Iridum using Chandrayaan-1 M³ hyperspectral data, which shows that the fully constrained linear-unmixing method is a kind of effective approach to mineral identification and inversion with hyperspectral data.

According to the different band characteristics of ASTER data, lithologic and alteration information was extracted respectively. After silica content was extracted quantitatively by the band ratio method from TIR bands,the information of mafic-ultramafic rocks was extracted quantitatively by the band ratio lithologic index(LI) method, and the alteration information such as kaolin-sericite, chlorite and serpentine was extracted qualitatively by principal component analysis method from VNIR and SWIR bands. Then, on the ArcGIS platform, the alteration information extracted was made quantitative grading, and an integrated anomalous information figure was compiled after stacking process. The range and intensity were very consistent with the known mine. Finally, the ore prognosis of the Jinchuan copper-nickel deposit was conducted using the integrated anomalous information, and three prospecting prediction areas were delineated, which can provide a reference in the search for the same type of deposits.

In order to monitor the change of land cover with remote sensing technology, the authors studied a method which is based on single-temporal remote sensing image in different years for extracting differences between the images and determining the change threshold automatically to extract the change area. The research took Landsat8 OLI images of Nantong City as an example. Principal component analysis (PCA) was carried out respectively on two images. After the PCA transformation, the first three components were operated based on change vector analysis (CVA) to get the difference image for change detection, which was compared with the extraction results based on the traditional PCA method and CVA method. Overall minimum error probability threshold determination method and local minimum error probability method were utilized to automatically determine the threshold of the three difference images and to get six change area images. The accuracy was evaluated by visual interpretation, and the results show that the overall accuracy of the new method can reach 92.78%, with kappa coefficient up to 0.8426. This method is proved to be feasible and effective for extracting change area by single-temporal remote sensing image in different years.

BJ-1 micro satellite can adjust CCD exposure by altering the imaging integration time, which not only can affect the digital numbers(DN)and the image quality but also can bring about the uncertainties in retrieving the land surface parameters quantitatively. Taking the HJ-1 CCD datasets as references, the authors calculated and analyzed the spectral characteristics and image quality of the high reflective targets in BJ-1 CCD images. Some conclusions have been reached:The image quality will be improved with a moderate exposure and impaired with over-exposure. The spectral features of the snow in terrain shadow can be enhanced with the increasing imaging integration time, while the spectral characteristics of the snow on the sun side would be weakened as a result of the image "saturation". On the basis of the spectral features of the snow and the data characteristics of the multi-exposure BJ-1 CCD imageries, a normalized model of the multi-exposure imageries for extracting the snow cover is proposed with the accuracy (classification success index, CSI)of 89.95%, which is superior to the accuracy (CSI)of 82.25% of mono-exposure model and the accuracy(CSI) of 75.95% of supervised classification. The results achieved by the authors will greatly facilitate the design of the more target-specific intelligent sensor and the development of more accurate inversion theory and techniques in retrieving the land surface parameters quantitatively.

In view of the facts that the high resolution image is usually lack of shortwave infrared wavelengths and that the first two components of KT transformation have the characteristics of high contrast, this paper proposes a ratio build-up index (RBI) with GF-1 images as the data source. Under different temporal-spatial conditions, the ratio build-up index was used to extract the build-up land information of Zhongxiang City and Fancheng District of Xiangyang City in Hubei Province, and the result was compared with results of the common classifiers and the common build-up index's extractions. It is shown that the accuracy and Kappa of RBI extraction are better, and RBI has good inhibition capability on bare land information.

Random-forest classification(RFC)method was used to extract the land cover information from the TH-1 satellite remotely sensed multispectral data in Beitun Town and its adjacent areas within the arid region of Altay,Xinjiang. Owing to the mixture of the impervious covers and the exposed soils inside the city, the textural and vegetation features were derived from the TH-1 panchromatic image and multispectral bands and subsequently applied to creating optimal feature set so as to implement the RFC classification. The optimized classifier can achieve better identification of some confused land cover classes. The results show that the RFC possesses higher accuracy than the conventional maximum likelihood classification(MLC)with the same TH-1 image, with their total accuracy being 82.26% and 72.61%, respectively. In addition, favorable applicability is observed in the land cover classification in the arid urban region using optimized combined multi-feature methods, which can provide land cover information for the urban development and planning in the medium and small cities of Xinjiang.

The upscaling methods for land cover classification data are still based on mode number selection or principle proportion choice; nevertheless, blocked at multiple modes, map information will be largely distorted under randomly choice. In order to maintain spatial information before and after generalization, this paper introduces land cover priority guidelines and semantic proximity norms to the upscaling method. A new upscaling method can be obtained by adding both rules to the aggregation processing. Firstly, through setting land cover priority guidelines and semantic proximity norms, the output category at the corresponding spatial location can be calculated on the coarse scale. The results show that, based on the majority aggregation method, and by adding the priority of the neighboring and semantic rules, the consistency of the spatial distribution of the feature can be better maintained after generalization, and the similarity of original maps is relatively high.

The change information of buildings is vital for map updating and statistics of geographical features. First, the information of buildings was extracted from airborne LiDAR data and the edges of buildings were detected by the alpha-shapes algorithm. Then the edges were compared with those in GIS vector data using multi-level change detection strategy to detect the slight changes of buildings automatically. The experiment results show that not only qualitative change detection can be accomplished but also the quantitative statistics of changed features can be obtained, with the accuracy of detection results reaching 95%. Compared with previous methods based on image, this method has advantages of high automation, simple processing procedures and high efficiency.

Road intersection is one of the most important parts of road network, and extraction of road intersection information plays a significant role in such aspects as road network extraction, image registration and vehicle navigation. However, the research on extracting road intersections from remote imagery is insufficient. In view of the characteristics of road intersections in high resolution remote sensing imagery, the authors propose an approach to auto-extraction of road intersection in this paper. On the basis of image preprocessing, detection of homogeneous circular area by multi-scale structure elements was firstly used to extract alternative road intersections, which included gradient transformation and morphological transformation. Secondly, feature extraction for alternative road intersections was processed in order to further refine the result and get the central position for each choice. Finally, angular texture signature was extracted for each central position and road intersections were identified by valley finding. The experimental results show that the method presented in this paper can extract urban road intersections efficiently and has fairly good accuracy for complex urban context.

Soil moisture is very important for the global water cycle in that the fast obtaining of large area's soil moisture content becomes very significant. Due to the advantages of microwave remote sensing, this technique can be applied to the inversion of soil moisture. In this paper, the authors built the BP neural network based on Matlab and, through improving the neural network's weights, threshold and the network structure, optimized the BP neural network. According to the measured data of the study area, IEM model, Oh model and Shi model were used to train the neural network so as to build soil moisture retrieval model, and the measured soil moisture content was used to test it. The result shows that the improved BP neural network algorithm obviously improves the inversion results, and Shi model is better than the other two kinds of model in training the network, with its absolute error being 2.47 and relative error being 7.78%.

Vegetation extraction plays a key role in such aspects as agricultural monitoring, ecological and environmental function evaluation. Traditionally, it is a labor input task before remotely sensed images are involved. Yet it is difficult to deal with conditions when clouds exist. Therefore, scenes become hopeful when unmanned aerial vehicle(UAV) images emerge in vegetation extraction, and hence this means is a low-cost and flexible way with high spatial resolution. High efficiency methods are therefore required to extract vegetation area automatically using UAV images, preferentially with various color indices always involved. The problem is that there is no evaluation of the effects of vegetation extraction with different color indices. In this paper, Weishan County of Shandong Province was chosen as the study area and four color vegetation indices comprising normalized green-red difference (NGRDI), excess green (ExG), excess green minus excess red (ExG-ExR) and green leaf index (GLI) were selected to extract vegetation information from UAV images with OTSU threshold values. The results show that all the color indices are capable of extracting vegetation area with accuracies above 90%. ExG-ExR index could more likely generate higher accurate results than other indices. ExG and GLI indices generate relatively high accurate and stable results, and could also be used for effective vegetation extraction. For images with high RGB value contrast between vegetation and background, all the color indices work especially well. Further analysis has revealed that accuracies of vegetation extraction have positive relationship with the proportion of winter wheat in images, and exhibit negative relationship with the proportion of broadleaf trees, buildings and roads.

In full consideration of the characteristics of the UAV tilted images, this paper presents an UAV tilt image matching method based on POS. Compared with existing matching method, this paper firstly introduces the global SRTM data as auxiliary to forecast the images overlap area, and secondly set up an approximate relationship of epipolar line between images to exclude the gross error. As known to all, the SIFT matching algorithm has large computation and spends a lot of time, so this paper replaces it with SIFT GPU to improve operating efficiency. Specially, this paper refines the accuracy of POS step by step, because the initial accuracy of POS is not high. The experimental results of UAV tilt images from different tilt cameras shows that this method can provide a sufficient number of corresponding points which are evenly distributed and correct.

With the development of the unmanned aerial vehicle(UAV)technique, currently UAV data have been gradually used in application and research fields. Differing from the current UAV matching method that integrates Photogrammetry and Image control points, the novel method presented in this paper is based on the color scale-invariant feature transform (CSIFT) feature to collect the key match points in the reference image and the image to be matched, followed by using the random sample consensus algorithm (RANSAC)method to extract the match points for the final matching result. The authors use an example to verify the feasibility and the validity of the method. Compared with the SIFT method, the accuracy could be increased from 70% to 88%, and the algorithm proposed in this paper can not only guarantee the matching result but also produce less matching points and use less working time.

In this paper, not only the topographic maps of 1971 and 1981 but also the remote sensing images of 1981, 1990, 2001 and 2011 were used for investigating the land use change of reclaimed mud flats of Jiaojiang-Taizhou Estuary in the past 40 years or so. Based on the topographic maps and satellite images and supported by the GIS spatial analysis functions, the authors acquired the current land use status of five periods and the land use change matrix between each period of reclaimed mud flats. The remote sensing survey results showed that in the past 40 years or so the trend of reclaimed mud flats of Jiaojiang-Taizhou Estuary was totally exacerbated and the types of land use were gradually increased. From 1971 to 1990, the land use types of reclamation zone mostly were converted into cultivated fields, breeding farms and reclamation land. After 1990, the upsurge of developing the reclamation of mud flats appeared. The beach and the reclamation land were converted into other land use patterns, such as cultivated fields, residential land, port land, and breeding farms. From 2001 to 2011, 80.77% of the beach was converted into the reclamation land. The area of beach was reduced heavily. The expanding speed of reclamation of mud flats achieved the maximum in this period.

In order to strengthen the application of remote sensing to digital mapping and improve the precision and the quality of geological mapping in West Kunlun of Xinjiang, the authors, by using remote sensing image processing (atmospheric correction, geometric correction, image mosaic, image fusion, image cropping, orthophoto correction etc.), and remote sensing image enhancement processing (ratio method, principal component analysis), and the geological information, extracted much geological information from rocks, strata and tectonics, so as to guide the regional geological survey in field work. The methods applied in digital mapping and the effect of remote sensing technology were summed up. It is held that the geological remote sensing technology plays a multiplier effect in regional geological survey. Through the use of high accuracy remote sensing image data, the authors improved not only the drawing of the boundary range of geological body but also the outlining of part of informal mapping units.

In this paper, aimed at the study of the hazards caused by the mining subsidence using remote sensing images,according to the research objective,the coal mine ore concentration located in the east of Jining City, Shandong Province of China was chosen as the study area. Multi stage optical remote sensing images and historical data were used, and necessary field survey were supplemented also. The results show that:1The mining subsidence in the study area is very serious. By 2013, at least 25.095 km² of land was destroyed, 24 villages were forced to move; 2In generally, mining subsidence developed rapidly in the study area. From 2009 to 2013, 4.747 km² of mining subsidence water area was increased in total, and the growth rate was 23.33%; 3 For a single mining subsidence, it is fierce, fast development, great hazard in the beginning. But after the rapid development, the expansion rate will gradually slow down, and gradually transit to the natural balance; 4Optical remote sensing technique can be used to research and investigation of mining subsidence hazard, and the characteristics such as macroscopic and cheap could make up for the lack of ground survey.

TRMM (tropical rainfall measuring mission) precipitation data, covering a wide range with high temporal resolution, is an effective data source to monitor drought on a regional scale. The spatial resolution of 0.25° TRMM 3B43 data was processed using the downscaling method. The downscaling data with 0.05° spatial resolution were used to construct a percentage of monthly precipitation anomalies (Pa index) and Z index, and the two indices were used to monitor the temporal and spatial change of drought from the winter of 2010 to the spring of 2011 in the Huanghuai Hai plain. The standardized precipitation index (SPI) during the same period was also calculated to verify the results. The results showed that the downscaling results had higher reliability with the fitting result R² higher than 0.76. Pa index that emphasizes gains and losses of precipitation can be used for drought monitoring on the regional scale, but it lacks the space distribution of drought; Z index fitting the precipitation based on the Person-Ⅲ distribution is ideal for monitoring the temporal and spatial distribution of drought, but the drought grade is difficult to divide. The drought grade of Pa index was used to correct the drought grade of Z index. Two indices and SPI had higher degree of correlation with R² greater than 0.75, indicating that Pa and Z index is effective for drought monitoring. The results achieved by the authors could provide a practical means for monitoring drought on a regional scale.

The monitoring of the spatial and temporal changes of rural residents is of great significance in serving "three rural issues", land and resources management based on rural remote sensing information. In order to monitor the residential area especially the rural area by using remote sensing technology, the authors chose Taihe County in Jiangxi Province as the study area. On the basis of the RapidEye satellite images after ortho-rectification with spatial resolution of 5 meters, the residential land classification extraction and accuracy evaluation were carried out using the maximum likelihood method. The results showed that the overall classification accuracy reached 84.33%. The producer's accuracy and user's accuracy of the residential land were 76.01% and 82.28% respectively, and the consistency reached 71.0% in comparison with the residential land data of Taihe County in the second national land survey, and the possible causes of errors were also analyzed. The research results show that the resident land monitoring of rural counties using RapidEye images of 5 meters resolution is feasible in that it can provide reference for future similar studies.

As a new kind of active earth-observation system, the technique of airborne light detection and ranging (LiDAR) can acquire accurate three-dimensional coordinates on the surface,and construct the real digital terrain model to provide the direct observation data for the landscape analysis in geological domain. Based on the advantage of LiDAR, the authors mainly deal with the applications of LiDAR data to such fields as surface collapse,landslide and fault structure extraction. It is shown that airborne LiDAR technology is becoming an indispensable tool for above-mentioned issues, especially in the local and large scale investigations of micro-topography. The technology can not only identify the surface collapse, landslide boundary and subtle faulted landform but also extract the filling parameters,the geomorphic parameters of landslide stability evaluation and cracks,thus having extensive application prospect in geological investigation.

Rizhao offshore was selected as the study area in monitoring the Enteromorpha Prolifera. Using the floating algae index (FAI) which is based on the remote sensing technology and geographic information system with MODIS global surface reflectance data, the authors interpreted and extracted the Enteromorpha prolifera information in Rizhao offshore. Temporal and spatial evolution characteristics of 2012 and 2013 were studied through these methods. Combined with the sea surface temperature data and the precipitation provided by TRMM satellite, the relationship between Enteromorpha prolifera and the meteorological factors were revealed. The results can provide information about controlling and alleviating the harm of Enteromorpha prolifera. Some conclusions have been reached:The intensity and distribution areas of Enteromorpha prolifera could be well revealed by using FAI index from May to July in 2012 and 2013. The information about Enteromorpha prolifera by using threshold indicates that the intensity and the areas of Enteromorpha prolifera in 2013 was stronger than that in 2013. Temperature and precipitation have great influence on the thriving of Enteromorpha prolifera. The temperature between 20℃ and 21℃ is the best interval for the growth of Enteromorpha prolifera, and the increasing of precipitation is also important for the increasing of Enteromorpha prolifera. In short, hydrographic and meteorological condition in 2013 was more suitable for thriving of Enteromorpha prolifera than that in 2012.

In mountainous areas of Tibet, glacial lake outburst debris flow is one of the main disasters, bringing devastating destruction to downstream settlements and infrastructures, such as roads, bridges and water facilities. Glacial lake outburst debris flow has long drawn great attention; nevertheless, because of the cold climate, steep terrain and terrible traffic condition which bring inconvenience to field investigation, very insufficient real-time literature data or some records inconsistent with the facts have been obtained for most of the glacial lake outburst events. Remote sensing images can really record the traces related to glacial lake outburst debris flow. Based on the high spatial resolution images of RapidEye and the multi-temporal images of Landsat MSS and TM, the authors analyzed the glacial lake outburst debris flow event that occurred in 1982 in Dinggye County, Tibet, which was reported by Lyu Ruren and Cheng Zunlan et al. Through remote sensing interpretation and analysis of dynamic changes of the glacial lake outburst debris flow event, the authors hold that the "Jincuo Lake outburst debris flow event" was actually induced by Yindapucuo Lake outburst. In the field investigation the authors found that Jincuo moraine was not destroyed by debris flow, and there was neither large U-type gully nor new debris flow accumulation settled in its downstream site, which confirmed the analysis of remote sensing. The results show that high resolution and multi-temporal remote sensing images can effectively improve the accuracy of investigation for geological hazards in dangerous areas.

The water quality of the Fuxian Lake basin has been deteriorating during the past 20 years. To evaluate the impacts of land use changes on water quality, the authors used Landsat TM and ETM⁺ from 1992 to 2010, in combination with GIS methods and correlation analysis, to explore the relationships of water quality with land use structure and landscape patterns respectively in the period of 1992-2010. The results showed that the surface water area, forest coverage and cultivated land area all displayed a decreasing trend, with a negative correlation of water quality with water area, forest coverage and cultivated land area respectively. There was a rapid expansion of transportation and construction land, which exhibited a significant positive correlation with water quality. Both the landscape diversity index and Shannon's diversity index (SDI) exhibit a significant positive correlation with water quality, and landscapes become more fragmented with an increase in patch number and shape complexity.

Traditional optical and Radar remote sensing technology fails to acquire the building facade damage in the case of earthquake damage assessment. The capability of identifying the buildings whose structure has been destroyed and whose roof top is basically complete is poor. This reduces the assessment accuracy. However, terrestrial laser scanning could acquire the high precision 3D information of the damaged structure. Using RIEGL VZ-1000 laser scanner, the authors collected laser point clouds data of Bailu middle school on October 23, 2013. The point clouds were used to conduct 3D modeling and analysis through triangular irregular network modeling and texture mapping. On such a basis, a detailed modeling study was carried out on the typical architectural damage characteristics and surface rupture destruction. The authors achieved damaged buildings surface observation at any angle and quantitative measurement of the surface rupture through point clouds 3D modeling. The results truly reproduced the current scene of Bailu middle school after earthquake and permanently preserved the damage information. The results showed that the Qinxue building located on the hanging wall had no significant damage, whereas the Qiuzhi building located on the heading wall was seriously damaged. "X"-shaped conjugate shear fracture, structural column fracture, rebar exposure and other phenomena were widespread. The earthquake scarp settlement was small and the scarp elevation profile showed that the minimum and maximum height was 205cm and 231cm respectively. This was consistent with the GPS measurements.

Reclamation is a double-edged sword:on the one hand, it can ease the shortage land resources, but on the other hand, it also brings serious negative effect to the coastal ecological environment. The first step is to make the classification system of reclamation in order that the government can monitor and manage reclamation reasonably for controlling and making decision. Reclamation is an intermediate process from sea to land, and this paper tries to connect sea use classification system and status of land use classification so as to make the classification system used in reclamation annual monitoring by remote sensing based on the level of multi-source high-resolution remote sensing image which can be interpreted, the definition of reclamation, the use properties and formation mechanism of reclamation and other factors. In addition, corresponding to the reclamation classification system of remote sensing monitoring, this paper has established remote sensing monitoring interpretation criteria of reclamation based on multi-source high-resolution remote sensing image.

To understand the rule of evolution of the Dongting Lake, the authors, by using the waters distribution maps in different historical periods and the remote sensing data as well as topographic data obtained in the past decades and applying GIS graphic-image processing and man-computer interactive information extraction method, obtained information scale of water area change in 22 different periods of the Dongting Lake. According to the law of data distribution, the authors established the mathematical model of the Dongting Lake basin evolution on the basis of mathematical statistics analysis method. The future development trend and its influence on the future ecological environment of the Dongting Lake were analyzed and predicted. The research results show that the Dongting Lake will die out in 250 years according to the mathematical model calculation.

Unmanned aerial vehicle (UAV) remote sensing has a great application potential in geological disasters monitoring. A plenty of software for UAV image processing has appeared on the market in recent years. In order to provide a valuable reference for choosing UAV image processing software for geological disasters monitoring, the authors evaluated the mostly used software DPGrid, PixelGrid, DPMatrix and Inpho. A block of 644 UAV images of hilly areas acquired in Longnan County of Jiangxi Province by Cannon 5D MARK Ⅱ camera on board a fixed-wing UAV at a flying height of 600 m were used as test data. The preprocessing, aerial triangulation, DEM and DOM generation of these images were performed by one operator using the aforementioned software in the same test environment, then these kinds of software were analyzed in terms of function efficiency, product quality and workflow. The results show that all of these kinds of software have complete UAV image processing capability and the order of processing efficiency from high to low is Inpho, DPMatrix, DPGrid and PixelGrid. For geological disasters emergency survey, it's better to use DPGrid and DPMatrix to generate fast mosaic. For detailed geological disasters survey, all of these kinds of software can meet the requirement while DPGrid and PixelGrid are more suitable for precision control, Inpho and DPGrid are more suitable for brightness balance and color adjustment, and DPGrid is more suitable for editing DEM and DOM.

To solve the problems of online interpretation and attitude measurement for faults in the application of high resolution remote sensing, the authors developed a platform of online interpretation and attitude measurement for faults by using high resolution remote sensing image and application programmers interface provided by Web Map Service. The platform allows users to analyze the geological structure as well as identify and vectorize the fault. On this platform, vector data are saved as extensible markup language(XML)and can be transformed into typical GIS data formats, and existing GIS data are allowed to be viewed and calibrated after format conversion. Imbedding of Google Earth, through Google Earth Plug-in, enables users to calculate the fault attitude using the DEM on this platform. Multi-point method is adopted to improve calculation accuracy. The results show that the method of interpretation and attitude measurement for faults based on Web Map Service, which takes advantage of fault interpretation using high resolution remote sensing image and breaks through the data source limitation of remote sensing image and DEM data, can accurately extracts geographic information and attitude of geological structure,and the platform possesses data sharing and application portability.

In order to achieve computer automatic checking of stratigraphic spatio-temporal topological relationships in geological map,the authors chose the Geological Formation Structural Map of Yichang City in Hubei Province as an example. The rule set of computer automatic checking of stratigraphic spatio-temporal topological relationships was built by deeply analyzing the spatio-temporal characteristics of the strata in the study area. The computer automatic checking function of spatio-temporal topological relationships of strata was developed using GIS development platform MapGIS67-SDK, the function was integrated into the application software (GEOMAG) of national mineral resources potential evaluation data model and finally the quality checking of spatial database was achieved. The result shows that this software can accurately determine the correctness of topological relationships of the strata and improve the quality of spatial database of geological maps effectively.