High-resolution satellites have tremendous application potential in China's environmental protection. In order to improve the application level of China's environment remote sensing, the authors summarized the application status of three satellite perspective types of high resolution optical satellites, high resolution Radar satellites and hyper-spectral satellites in the field of atmospheric environment, water environment and ecological environment in combination with the characteristics of China's environmental protection. The deficiencies of systematic and operational application are pointed out; the future key research fields seem to include the high accuracy imagery processing, scaling effect and information extraction, high accuracy inversion technique, ground truth verification and validation techniques. The technical development of high resolution satellites and remote sensing as well as the launch and utilization of China's high resolution earth observation satellites will greatly improve the quantitative and refinement level of environmental monitoring and supervising in near future.

In content-based image retrieval (CBIR), the feature selection of target retrieval and similarity computing is a hot issue of current research. As the object-oriented image processing methods are conducive to describing the spatial relationships between objects, the authors proposed an parameterized evaluation model of similarity for multi-target retrieval on the basis of an analysis of multi-feature descriptor. This model not only takes into account the global spatial relationship between image objects but also considers the local features of image targets. The model organizes the multi-dimensional features for an image using the analytic hierarchy process (AHP)method under moving picture expert group (MPEG7)standard, then the eigenvalues are calculated using existing methods, and finally the weighting coefficients are set for calculating the overall similarity on the basis of user preferences so as to evaluate the effect of multi-target retrieval. Thus it can provide a powerful reference and experience for multi-target retrieval in an image database. The experimental results show that target retrieval is not only related to the method of similarity calculation but also related to the complexity of the image itself.

In combination with discrete wavelet transform(DWT) and two-dimensional multi-stage median filtering(TMMF)algorithms, the author proposes a self-adaptive remote sensing image de-noising algorithm in this paper. Firstly, the remote sensing noise image is conducted with the single layer DWT so as to obtain the low-frequency wavelet sub-image and high-frequency wavelet sub-images. As the low-frequency sub-image is not polluted by noise, the low-frequency sub-image should be kept unchanged. Signal layer DWT is conducted again for high-frequency sub-images, and therefore the secondary low-frequency sub-image and secondary high-frequency sub-images are obtained. Then, the secondary low-frequency sub-images are filtered by the improved TMMF algorithm, and the secondary high-frequency sub-images are processed by the improved wavelet hard threshold function model. Finally, the wavelet reconstruction image is acquired. Three remote sensing images with detailed information were adopted to test the performance of the method proposed in this paper, and the results of theoretical analysis and test show that the filtering performance of the algorithm proposed in this paper is superior to TMMF algorithm and its improved algorithm as well as wavelet transform hard threshold de-noising algorithm.

In this paper, the strategy to extract accurate road centerlines from acquired road stripe image was explored. The workflow is as follows: Firstly, road candidate points are obtained based on probabilistic boosting tree algorithm, and smooth and integrated road stripes are immediately acquaried by morphology. Secondly, thinning algorithm is introduced to automatically detect road centerlines; nevertheless, the output contained spurs and local curvature of centerlines change much. After that, geodesic distance theory is used to remove spurs. Thirdly, initial results are refined on the basis of Dijkstra algorithm. Lastly, the ultimate road centerlines are obtained according to direction consistency and road continuity. The authors performed an experiment on a high resolution aerial image. The result is satisfactory and shows that the strategy proposed in this paper is an effective method.

The airborne LiDAR system integrates the global positioning system (GPS), inertial navigation system (INS) and Laser Ranging system. Nevertheless, in the process of measuring the system, many errors are inevitably produced, and hence the influence of the observational error caused in the process of measurement must be considered and eliminated, which is called data calibration. The traditional calibration method is stable and reliable, but its disadvantage is that the calibration field flight is requisite, and it has a higher demand for ground objects. In some areas it is difficult to find an appropriate calibration field. In view of such a situation, the authors employed a calibration method of cloud data without calibration field, which is based on Burman model and stripe adjustment theory; through the Placement Angle correction and 3D coordinate correction, it can eliminate the systematic error. Tests in Xiaojiang experimental area of Yunnan Province show that the cloud point data after calibration can completely meet the 1:2 000 DEM mapping precision.

Leaf area index (LAI) is the key parameter to signify the growth condition and canopy structure of vegetation. Inversion of LAI using remote sensing technology is always one of the hotspots and difficulties in the field of remote sensing. In this paper, the first and second order derivatives of hyperspectral data of wheat were calculated, and several vegetation indices (RVI, NDVI, EVI, DVI and MSAVI) and trilateral variable parameters were built for the analysis. The correlation analysis between the parameters and wheat LAI data was carried out, and the method of cross-validation was used for multiple regression analysis so as to determine the sensitive parameters for wheat inversion of LAI and choosing model type of inversion. At last, the inversion models of all the samples were built by using these sensitive parameters, and their imitative effects were comparatively studied. The results show that the majority of root mean square errors(RMSE)of the inverse models using cross-validation are larger than those of the models which do not use cross-validation. In addition, among all the models built by the sensitive parameters, the cubic regression model of RVI is the optimal model for inversion of wheat LAI with remote sensing data.

COCTS is a Chinese ocean color and temperature scanner which is carried on the 2nd oceanographic satellite (HY-1B) launched by China. HY-1B/COCTS images have the alternate dark and bright lines due to the difference of the detectors within COCTS responding to spectral signal reflected by ground objects. In this paper,the authors analyzed the spectrum of ground objects in visible and near infrared bands of COCTS, retrieved the water information by the normalized difference water index (NDWI) constructed with the 4th and 8th band of COCTS, and then removed the stripe noise for waters in COCTS image by the moment matching. Finally, 7 indexes, namely, mean, standard deviation, signal-to-noise, skewness, kurtosis, information entropy and average gradient, were selected to evaluate the de-striped image quality. The results show that the moment matching based on waters performs well in removing the stripe noise in COCTS image, the contrast of digital number is decreased, and the image quality is improved.

As an effective tool for extracting the texture, the variogram can be used to describe the properties of structure and randomness of the images. The utilization of the traditional variogram texture extraction method with a moving window has the border effect and also has difficulty in determining the appropriate window size. To solve this problem, the authors tentatively selected the WorldView-2 image of the bare rocks in Yingisar County, Xinjiang, extracted the variogram textures based on three scale segmentation results with multi-resolution segmentation algorithm, and then superimposed them on the original multi-spectral images for lithological discrimination. The authors further compared the results of multi-resolution segmentation with moving window. The experimental results show that the texture information extraction based on segmentation could eliminate the border effect, relieve the shadow effect and improve the accuracy of lithological classification. It is found that there are some differences in identifying the effects of extracting the textures on different segmentation scales based on multi-resolution segmentation. The method proposed in this paper is more stable and reasonable than that of moving window method once an appropriate segmentation scale is set.

It is necessary and valuable to study the effect of influencing factors of crop classification on crop acreage estimation from both qualitative and quantitative points of view. Therefore, the authors analyzed the resolution effect on the acreage estimation accuracy by using RapidEye imagery. Spatial statistics methods and manifold accuracy evaluation indices were used respectively to analyze the data with different index statistics of crop proportion, crop fragmentation and shape. The results show that decreased crop proportion and increased crop fragmentation and shape index will lead to reducing regional accuracy under all resolutions. And in order to keep the accuracy higher than 85%, we can select any resolution higher than 150 m data when the crop proportion is higher than 50%, so as to achieve the accuracy requirements. As merely improving resolution cannot guarantee the crop acreage estimation accuracy when the crop land exhibits long and narrow distribution, other technology must be adopted in this case. Finally the quantitative influence model of the four factors for crop acreage estimation accuracy is built. The results of this paper would provide academic reference for resolving the problem of data selection and accuracy improvement in crop acreage estimation by remote sensing.

The workflow technology was tentatively applied to the terrain factor extraction. The authors chose the extensible markup language (XML) as modeling language to study and model the process of terrain factor extraction. A set of models and modeling methods suitable for terrain factor flow extraction was formed by structured organization and description of the relationship between data transfer, input data, output data, parameters, factor model and driven execution from terrain factor extraction. The model with 5 m×5 m resolution based on traditional terrain factor algorithm automatically extracted terrain factor from DEM data of the experimental area, with good results achieved. At the same time, the river network extraction was conducted to test the terrain factor extraction model. The results show that the model has strong adaptability and scalability.

Land surface temperature (LST) is an essential parameter in such fields of research as climate, hydrology and ecology, and it plays a significant role in the understanding of the water and energy balance of the Earth's surface. Because the heterogeneity of the underlying surface is most likely a main source of the uncertainties of the satellite derived LST, this paper aims to evaluate the accuracy of the FY-2C derived LST over the heterogeneous area of Maqu County in the source region of the Yellow River and subsequently to provide solid basis for the future development of the LST inversion algorithm and product. MODIS LST product (MOD11B1) was primarily conducted to verify the FY-2C derived LST over the study area. In addition to the MODIS data, soil temperature measurements from 20 soil samples of the study area were also implemented to validate the FY-2C derived LST. The results indicate that a significant correlation exists between the two datasets, with the coefficient of correlation, varying from 0.72 to 0.95, root mean square error(RMSE) ranging from 0.44 to 3.87 K, and the average RMSE being 1.90 K. The FY-2C derived LST exhibits a consistent variation with the measured soil temperature, and the coefficient of correlation reaches 0.69.

On the basis of normalized difference water index (NDWI) of FY-3/medium resolution spectral imager(MERSI) and normalized difference water index based on blue light (NDWI-B), the authors analyzed histograms and obtained the thresholds for the recognition of water bodies with NDWI. The thresholds were utilized in the monitoring of the snowmelt flood disaster along the Tianshan Mountains in the north of Xinjiang during 2009 to 2011. The results achieved by the authors suggest that it is feasible to monitor the snowmelt flood disaster in Xinjiang with the data both from FY-3/MERSI and from HJ-1A /CCD. The effect of using FY-3/MERSI(NDWI-B_FY) data to identify large area of flood water is the best.

In this paper, the authors conducted an applicability study of water-based information extraction method according to the data features of GF-1 image. Firstly, water index(normalized difference water index, NDWI)threshold method, support vector machine (SVM)method and object-oriented method were used respectively to conduct water information extraction experiments on the Poyang Lake area based on GF-1 image so as to analyze and compare the advantages and disadvantages of these methods. Secondly, statistic analysis of the rate of leakage and error as well as extraction accuracy was made by selecting two representative areas with different scales and complexities, with the manual interpretation of these two water areas as reference. The results show that the above three kinds of methods all have a high accuracy in both areas, with the extraction accuracy of the simple area (area 1) slightly higher than that of the complex area (area 2); A comparative study of these three methods shows that SVM method has the highest accuracy (99.474 2%, 98.099 3%), followed by the object-oriented method (99.316 4%, 97.877 9%), and then by NDWI threshold method(99.145 6%, 97.590 0%).

The Great Dyke in Zimbabwe, which possesses abundant platinum, palladium, gold, chromium, nickel, copper and some other resources, is a major intrusion of mafic and ultramafic rocks formed at 2.5 Ga and one of the key regions for mineral exploration abroad. In order to attain the aim of "going out" for China's mineral exploration and provide basic geological information of geological survey and mineral exploration in the area of the Great dyke, the authors carried out the systematic interpretation of geometric elements and geological characteristics of the Great Dyke in Zimbabwe based on the ETM⁺ data and verified the division of the magma chamber of the Dyke. Combined with the ZY-1 02C high spatial resolution satellite data, the authors identified and interpreted the shape, lithology, interior structures and mining activities of the Selukwe Subchamber. The results achieved show that, because of the difference between the west and east host rocks, the Selukwe Subchamber underwent deformations of different intensities. The ultramafic layers should be regarded as the major layers for the chromite exploration. Furthermore, the authors have discussed the method of "five scales" of the remote sensing technique in the geological survey abroad and provided the technical support for the remote sensing application.

In this paper, the satellite remote sensing interpretation of geology and minerals in Pilbara Craton of Western Australia was carried out by using ETM satellite remote sensing images, and the mineral alteration information of the target area was extracted by using ASTER satellite remote sensing images so as to do further research on metamorphosed sedimentary type(banded iron formation, BIF-type)iron deposits in Hamersley Basin of Western Australia from the remote sensing angle. In combination with traditional theory of geology and mineral resources and relevant literatures, the remote sensing geological characteristics and metallogenic mechanism of BIF- type iron deposits in the study area were dissected, contrasted and studied. On such a basis, the remote sensing geological prospecting model of this type of iron deposits was established, and the prospective areas were delineated. It is expected to make a breakthrough in prospecting technology of BIF-type iron deposits and to provide a practical guide in search for this type of iron deposits. During the field investigation of the above-mentioned prospective areas, the authors found that Rio Tinto group in Australia already intended to build a large iron mine in C area of Newman-BHP Billiton and had basically completed the field leveling work, which verifies the practical significance of this paper.

Remote sensing geological interpretation and anomaly information extraction constitute one of the important research fields of remote sensing geology. Based on ALOS, SPOT5, ETM⁺ and other multi-source remote sensing data, and combined with digital elevation model(DEM), the authors carried out remote sensing geological interpretation, remote sensing abnormal information extraction and selection for Shengyuan volcanic basin in Jiangxi Province, with much attention paid to the extraction of uranium and polymetallic mineralization information, such as strata, fracture, volcanic edifice and alteration information. In combination with the available geological data, the comprehensive analysis on ArcGIS platform was conducted so as to understand ore-forming geological conditions and make prospecting prediction. The results achieved by the authors can provide basic data and reference for local mineral exploration and resource evaluation.

The changes of the ecological environment of the Dexing copper mineral resources development area in the past two decades were studied in the aspects of ecosystem structure and ecosystem landscape pattern reflected by the remote sensing images obtained in 1992, 1996, 2000, 2004, 2009 and 2013. According to the results obtained, the development activity in the Dexing copper mining area led to the continuous decrease of forests, grasslands and other natural landscape areas and the unceasing increase of mining field, tailings, field area dump and other artificial landscape areas; regional ecosystem quality became worsen and worsen, the ecosystem fragmentation was aggravated, and the overall performance was towards the increase of the ecosystem mean patch areas and the patch density, together with the decrease of aggregation index. Over the past two decades, mineral resource extraction activities became increasingly intense, the ecosystem damage area was increased year by year, whereas the ecological restoration project for this area was lagging behind.

Aimed at solving the vital social problem of environmental governance in mining areas, the authors used high resolution remote sensing (RS) data to study the comprehensive environmental governance of mines, with the Maoniuping REE(rare-earth elements) deposit in Mianning County of southwestern Sichuan as the study area. The method combining RS interpretation on satellite images of SPOT-6 and field investigation was utilized to ascertain site area, geological hazard, environment pollution, tailings place, restorative governance and mining area situation. Based on the comprehensive analytical method for mine environment, the authors analyzed the RS investigation result of rare earth ore in the Maoniuping deposit. On such a basis, governance measures and suggestions were proposed following the process of regional division for mine governance. The results show that the method proposed in this paper can bring about objective, timely and accurate results, which are helpful to regionalization of mining area governance and recovery. The results achieved by the authors are of valuable significance for the stimulation of the application of remote sensing monitoring results to mining areas.

In order to evaluate the data usability of ZY-3 in geology, the authors chose piedmont fault of the Daqing Mountain as the study area, and assessed the effect of applying the DEM(digital elevation model)of ZY-3 to quantitative study of active structure on the basis of the on-orbit testing work. Consulting 1: 50 000 DEM and high-precision GPS data, the authors assessed the DEM of ZY-3 which has 5m resolution by the check-point method and profile method, in comparison with the GDEM of ASTER which has 30 m resolution. Experimental results show that the elevation accuracy of ZY-3 DEM is slightly better than that of ASTER GDEM,and ZY-3 DEM is affected by the terrain factors more significantly than ASTER GDEM. Statistic analysis and micro-topographic research were carried out on piedmont fault of the Daqing Mountain, and the results obtained show that mountain areas account for about 92% of this region, and most of them are low or medium mountains. This region has four planation surfaces and a piedmont deposition platform, the closer to the last part of the eastern fault, the weaker the activity is. Fractures are distributed in linear form and their activities are mainly in tension with left-level slip. The high resolution optical images, multispectral resolution images and DEM can be widely used in quantitative study of active structures.

In order to improve the rapidity and correctness of the clue acquisition method for land supervision, this paper proposes a method of automatic construction land change detection based on stable sample database. Stable sample database was constructed by using historical land inventory data. Then the images were associated to dynamically sieve training data so as to tremendously reduce human intervention for the sake of automatic supervised classification. Before change detection, the classification results were discriminated by land inventory data. ZY-3 data obtained 4 months apart were used to carry out comparative experiments. The accuracy of construction land change detection using the method proposed in this paper was 72.82%, while that of the traditional method only reached 33% on equal terms. The results show that the precision of illegal construction land change detection is highly improved.

Cultivated land quality assessment is one of the projects in the new round of land resources surveying, and it is necessary to clarify the quality of cultivated land in Changping District of Beijing. In view of the shortage of cultivated land graduation, the authors combined the fuzzy theory and SOFM with GIS to establish the cultivated land graduation model, and used the model to graduate cultivated land of Changping District in Beijing. The research results show that the method has the advantages of obtaining stable and reliable results. The SOFM-GIS clustering model can be used to evaluate the quality of cultivated land and, with the visualization capabilities of GIS, to display distribution characteristics of cultivated land. In addition, it also provides a reference method for evaluating the cultivated land quality in similar areas.

In order to identify the land use change at the initial stage of exploitation of the Xinjie Taigemiao mining area,the author selected SPOT5 images of 2007,ALOS images of 2011,WorldView images of 2012 and QuickBird images of 2013 to extract change information.Then the land use changes and conversions were made clear through analyzing,and their change rules and driving force were obtained.According to the results obtained, the cultivated land showed rapid increase from 2007 to 2013. In this period, the driving force came from the residents' expectation of the land compensation; in addition, such factors as the settlement area,the water area,the greenhouse and aquatic operations were also directly responsible for the driving force.The forest land and the land for transportation area increased mainly concentratedly in the period of 2007-2011,with the former land attributed to afforestation project,and the latter to the Xinen Railway and the Langa Highway. The land for mining and industry continued to increase because of industrial construction and natural gas exploitation, and it is still maintaining a growing trend now. As the only net decrease of land use types,the grazing land that occupied a large area of the grazing land was being driven by the interests of the inevitable choice.In addition,the wasteland change represented the intermediate process of the conversion of the grazing land into other land use types.

In this paper, the changes of the study area were studied comprehensively using Landsat5 and Landsat8 images from 2001 to 2013 based on the techniques of object-oriented classification and spatial analysis. The results based on quantitative and qualitative analysis show that great changes of the land use have taken place in coastal zone in the past 12 years, and the total length of the coastline has increased by 514 km, with the total area of the coast increasing by 404 km². The results achieved by the authors further show that large areas of green land, wetlands and tidal flats have changed into port, construction land and unused land due to rapid economic development in the coastal zone.

In this study, interferometric point target analysis (IPTA) was used to monitor the surface subsidence of Changzhou City caused by factories' immoderate exploitation of groundwater on the basis of thirty-seven TerraSAR-X high resolution stripmap data collected in this area between October 2011 and July 2013. The results showed that several settlements appeared in Wujin area of Changzhou City, with the largest average subsidence rate up to 31.494 mm/a; A comparison with the average settlement rate of ASAR data shows that TerraSAR-X data could not only improve high density of PS points but also describe detailed changes and the micro-displacement situation of the scattering object, which indicates the advantages of TerraSAR-X high resolution stripmap data applied to monitoring the surface deformation. In this paper, the monitoring of land subsidence along Shenhai expressway of Changzhou by TerraSAR-X data reflects the prospects of TerraSAR-X data in monitoring artificial linear features. The survey results of bench mark verify the consistency of monitoring results and the reliability of IPTA used to monitor the surface subsidence in the city.

Fractional vegetation coverage (FVC) is one of the important indicators for describing the extent of water and soil loss. Dimidiate pixel model assumes that a pixel value is only contributed by vegetation and non-vegetation. Fractional vegetation coverage is defined as the area ratio of vegetation. In this study, Radar vegetation index (RVI) was first derived from Radarsat-2 data by polarimetric decomposition. The FVC was estimated from RVI based on dimidiate pixel model. Then this model with RVI was applied to Hetian area in Changting county of Fujian Province. Finally, the authors verified the results with a reference FVC, which was calculated from the high resolution WorldView-2 image and ground-truth data by field work. The results correlate well to the reference data with R² over 0.8. The result suggests that it is promising to use dimidiate pixel model with RVI to estimate FVC from Radarsat-2 polarimetric data. The method completely based on Radar data has solved the problem of the difficulty in obtaining data in Southern China and is also helpful to monitoring water and soil loss continuously.

Using the daily dataset of snow depth from 1979 to 2010, the authors analyzed the relationship between the spatial and temporal distribution of snow depth and the terrain factors over the Tibetan Plateau by means of Mann-Kendall test and GIS space analysis. According to the results achieved, the distribution of snow depth was significantly affected by topography, the average snow depth was affected mainly by elevation from May to September, whereas in other months it was under the common influence of temperature and elevation. The snow depth amplitude of the same segment elevation reflected the impact of the aspect on snow depth, and the influence was greater when the amplitude was wider. The maximum snow depth kept increasing with the increment of elevation and slope, while the spatial heterogeneity decreased with the increment of elevation but increased with the decrement of slope. From October to May of the next year, the average snow depth at the elevation from 82 to 2 482 meter and 6 082 to 7 682 meter was more affected by slope and aspect than that at the elevation from 2 482 to 6 082 meter. Multiple regression analysis showed that the distribution of snow depth over the Tibetan Plateau was influenced by elevation and slope; furthermore, spatial differences of slope at the elevation of 82~3 282 meter had significant positive effect on the spatial variability of average snow depth; nevertheless, elevation was the main limiting factor of the average snow depth.

Due to irregular flight route, low image quality and unstable flight attitude, it is really difficult to perform UAV imagery data processing using traditional photogrammetric software. For emergency response, a stable,highly automatic and time-efficient software solution is always highly demanded. In this paper, the authors present a UAV imagery solution for emergence using Agisoft PhotoScan Pro software to offer orthomosaic and dense point cloud service. It is held that this method can provide timely and effective scientific image for emergence, as shown by several emergency response practical applications.

In order to attain data sharing between MapGIS and ArcGIS system, this paper puts forward a scheme which realizes the conversion of geological data and geological symbol library from MapGIS to ArcGIS. On the basis of MapGIS and ArcGIS Objects for secondary development, geological symbol library exports the corresponding file as XML by MapGIS software. XML is analyzed and symbolized into the corresponding symbol library. Geological data are converted into shapefiles, with the generation of engineering (MXD) files which save the render information. The conversion of geological data and geological symbol library from MapGIS platform to ArcGIS platform can be finally realized by programming.

Synthetic Aperture Radar (SAR) remote sensing is playing an important role in remote sensing applications for its distinctive properties. However, the depth and breadth of its applications are severely restricted by difficulties in SAR image interpretation, which increase the threshold of applications. The Library of Targets Microwave Properties is proposed by integrating microwave remote sensing models, field measured data, SAR images and interpretation keys, different kinds of priori knowledge and application demonstration. It adopts Browser/Server architecture for data sharing and information expression online that provides an integrated information platform for research on microwave remote sensing theory and applications.

In order to attain geological data accessing and sharing on different platforms and regions and to establish geological spatial information sharing and application service system, China Geological Survey used the GridGIS technology to build China Geological Survey Information Grid Platform and deployed nearly 10 nodes across the country on the basis of the network superlarge distributed GIS software. Through the effective organization and management of mass data, China Geological Survey realized geological space service and sharing of information resources in different regions in the heterogeneous environment. The construction of the geological surveying information grid node in Southwest China has really achieved very good results. The results achieved by China Geological Survey not only verify the feasibility of grid platform for data sharing but also provide reference for further construction of grid nodes.