Table of Content

25 February 2018, Volume 0 Issue 2

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Pedestrian Motion Modes Recognition of Smart Phone Based on Support Vector Machine

GUO Jiming, WANG Wei, ZHANG Shuai

2018, 0(2):  1-5.  doi:10.13474/j.cnki.11-2246.2018.0033

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It is an important method in the field of intelligent recognition to use the built-in multiple integration sensors of smart phones as data acquisition tools,and to identify pedestrian motion modes combined with support vector machine(SVM). In this paper,walking,up/down stairs,up/down elevator,up/down escalator are selected as the common indoor motion modes.After effective features are selected,the linear kernel function SVM is used to establish the classification model to recognize the test data.The results show that 13 features are extracted from the data collected from pedestrian motion modes,and 96.4% recognition accuracy can be obtained at the 3 s data sliding window with 0.5 s data sampling interval.

An Improved Fingerprint Indoor Localization Algorithm Based on Combination Weight

CAO Xiaoxiang, CHEN Guoliang

2018, 0(2):  6-10.  doi:10.13474/j.cnki.11-2246.2018.0034

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Under the influence of complex indoor scene,unstable WiFi signal and other factors,there are some mismatches in neighbor points selecting based on the algorithm of K-nearest.For these mismatch errors,there will be direct impact on the results of localization.In this paper,we proposed an improved fingerprint indoor localization algorithm based on combination weight.Firstly,analyze the geometrical structures of K-nearest points,and then remove the points which have the longest distance between the center of K-nearest points and itself.Secondly,analyze the geometrical location of unknown point and the center of K-nearest points,and use the geometrical distance between neighbor points and the center of them,the Euclidean distance between neighbor points and the unknown point to determine the weight of algorithm collectively.Finally,obtain the weighted localization results.Compared with the localization results of KNN and WKNN algorithm,the improved algorithm gets higher localization accuracy and robustness.

A Semi-supervised Fingerprint Localization Algorithm Based on Manifold Regularization

ZHU Shuntao, LU Xianling, YU Danshi

2018, 0(2):  11-15,20.  doi:10.13474/j.cnki.11-2246.2018.0035

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Due to traditional fingerprint localization algorithms cost too much on collecting training dataset with labels,a new semi-supervised fingerprint localization algorithm based on manifold regularization is proposed.Firstly,the graph laplacian is initialized with the labeled and unlabeled training dataset under the manifold hypothesis.Subsequently,combined with the extreme learning machine,the hidden layer is constructed by using random mapping.Finally,the output weighted matrix between the hidden layer and output layer is solved under the framework of manifold regularization,so that the location estimated model is established.The simulation results show that,compared with INN,SVR and ELM,the proposed algorithm need shorter training time and testing time.In addition,it can maintain the high accuracy and reliability while labeled training dataset is sparse.

Robots' Indoor Trajectory Correcting and Controlling Algorithm

PENG Yitang, ZHU Dunyao, TANG Jian, MAO Dazhi

2018, 0(2):  16-20.  doi:10.13474/j.cnki.11-2246.2018.0036

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The application of indoor mobile robots has greatly improved people's working efficiency and lifestyle,but there is still no absolute solution for robots' indoor motion trajectory deviations.In order to enable mobile robots move precisely on preset trajectory for indoor mapping,based on the realization of SLAM(simultaneous localization and mapping) algorithm,this paper proposes significantly improve the trajectory precision with a novel PID feedback control model,which utilizes robots' attitude,position and trajectory deviation information to formulate a closed-loop control algorithm.Aiming at several typical trajectories of robot indoor motion,we carry out a large number of trajectory deviation tests,further optimize the robots' motion control parameters of the algorithm,and effectively reduce the indoor mobile robots' trajectory deviations.Compared to the indoor robot motion control system which only relies on the odometer,the modified algorithm makes full use of the location information of the laser radar,not only meet the demands of indoor mapping,but also obtain an accurate robots indoor-motion control scheme which has high reliability and stability.

An Algorithm for Automatically Calculating the Coordinate of Indoor Access Points

ZHENG Jiazhu, GAO Yehemin

2018, 0(2):  21-24,29.  doi:10.13474/j.cnki.11-2246.2018.0037

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With the application and development of location-based service,outdoor and indoor positioning technology has been developing rapidly.Indoor positioning technology has been widely utilized especially in the continuous improvement of WiFi positioning technology.But two positioning methods of WiFi positioning technology are required to know the exact coordinates of the indoor network access points.This requirement cannot meet some emergency location requirements.Therefore,this paper presents an algorithm for automatically calculating the coordinate of indoor access points based on M estimation.The algorithm utilizes the satellite location information and the RSSI value of WiFi signal at the junction of indoor and outdoor,uses the segmented RSSI ranging algorithm to improve the accuracy of long distance RSSI distance and combines the residual absolute and minimum M estimation to improve distance intersection positioning algorithm.Finally the three-dimensional coordinates of the indoor access points were calculated,to achieve automated projection process.The experiment results show that the positioning accuracy of this method is 50% higher than conventional distance intersection least squares algorithm and the coordinates of the indoor access points can be calculated more accurately in real time,and the WiFi positioning technology is further improved.

A Method of WiFi Indoor Positioning Based on Omnidirectional Fingerprint Database

BI Jingxue, WANG Yunjia, CAO Hongji, WANG Yongkang

2018, 0(2):  25-29.  doi:10.13474/j.cnki.11-2246.2018.0038

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WiFi indoor positioning technology is an attractive research topic in the domain of navigation and location service.Human body has a great influence on WiFi signal attenuation in indoor environment.In this paper,we propose a method of WKNN positioning based on omnidirectional fingerprint database considering signal strength variations caused by user's orientation.The experimental results show that the proposed method has a better performance than fingerprinting localization based on orientation recognition.When the value of K is 4,the mean localization error is 1.44 m,and the confidential probability with 1 m is almost 54%,the confidential probability with 2 m is almost 88%.

A Smooth Transition Method for Indoor and Outdoor Seamless Positioning of GNSS/Magnetic Combination

CAI Jin, CAI Chenglin, ZHANG Shougang, MENG Ping

2018, 0(2):  30-34.  doi:10.13474/j.cnki.11-2246.2018.0039

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In view of the problem that indoor and outdoor seamless positioning at the transition point has low precision and cannot switch smoothly and automatically,this paper combined GNSS(Global Navigation Satellite System) positioning technology and indoor geomagnetic fingerprint nodes to achieve indoor and outdoor seamless positioning and navigation.Due to the decreasing number of the satellites that receivers can search and the increasing GDOP(Geometric Dilution of Precision) value and positioning error from outdoor into indoor,the precision of indoor geomagnetic positioning is better than that of GNSS positioning gradually and can be switched stably by analyzing and calculating the GDOP optimal range value at the two critical positioning points.The simulation results of this experiment show that the positioning precision increased by 85.7% and 82.6% compared with single GNSS positioning or geomagnetic positioning methods,thus realized to achieve the seamless indoor-outdoor positioning with high precision,and filled blanks in the definition of indoor-outdoor seamless positioning switching both at home and abroad.

An Indoor Location Method of Monocular Vision Assisted by Camera Calibration

WANG Yong, CHEN Guoliang, LI Xiaoyuan, TIAN Peng, ZHOU Yu

2018, 0(2):  35-40.  doi:10.13474/j.cnki.11-2246.2018.0040

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At present,with the development of indoor positioning technology,people put a higher demand for the accuracy of indoor positioning.High precision and low cost indoor positioning technology has become a hot research.In this paper,a kind of monocular vision indoor positioning technology is proposed,which combines the indoor environment according to whether or not the area is divided and the camera is calibrated.The moving target of the video acquired by the camera is used to obtain the target pixel coordinates.And it uses the moving target to detect the acquired pixel coordinates and the positional relationship between the camera and the space and combine the plane constraint equation for the target position.The experimental results show that the accuracy of the algorithm is less than 0.15 m in the X direction and less than 0.35 m in the Y direction,and the average single point positioning time is less than 5 seconds,and a good indoor positioning effect is obtained.

Fitting of Regional Vertical Deformation Field Based on the Synthetic Model of Multi-surface Function and Movement Method

TIAN Xiao, ZHENG Hongyan, SU Guangli, WANG Jiaqing

2018, 0(2):  41-45,88.  doi:10.13474/j.cnki.11-2246.2018.0041

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Multi-surface function method is a traditional and widely used method in the study of vertical crustal movement.Through the two examples of the capital region and Jin-Ji-Meng region,the synthetic model of multi-surface function and movement method is compared with the multi-surface function model and some other models.The results show that the synthetic model of multi-surface function and movement method has a better fitting precision and more stable errors than other several models and it has practical values.

A Semi-supervised Classification Method for Hyperspectral Images

LI Caihong, ZHAO Yifei

2018, 0(2):  46-49.  doi:10.13474/j.cnki.11-2246.2018.0042

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Based on density sampling and dynamic time warping distance, this paper proposes a semi-supervised fuzzy cluster method to partition hyperspectral data set into several groups. The labeled samples are first obtained by density sampling method. Then the dynamic time warping distance is computed between a pair of samples. Lastly, semi-supervised fuzzy c-means is employed to cluster the hyperspectral image. To validate the proposed method, the Indian Pines and Pavia U data sets are chosen to feed our method. The experimental results show that it can discover the ideal clusters by the proposed method.

Study on the Geo-positioning Stability of GF-1 WFV Images

HAN Jie, XIE Yong

2018, 0(2):  50-54.  doi:10.13474/j.cnki.11-2246.2018.0043

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Through integrating the characteristics of GF-1 satellite WFV sensor which possesses high resolution and wide field view, taking ZY-3 sensor correction production as reference data, analyzing geographic information of homologous points, this paper evaluates the relative geo-positioning accuracy of four WFV cameras in Beijing area and finds the geo-positioning error characteristics. The experiment results show that the geo-positioning errors in one signal image appear obviously systematic errors. However, the geometric error directions of different phase images are irregularity. In view of this phenomenon, basing on the camera imaging principle, this paper theoretically proves that it is difficult to effectively eliminate the system errors of other phase images with compensation parameters of RFM (rational function model) of one phase image.

A Method of SIFT Matching Error Elimination for Heterogeneous Optical Images Based on Neighborhood Voting

SHEN Yuzhen, LI Baishou, LI Lingzhi, YANG Lu

2018, 0(2):  55-60,93.  doi:10.13474/j.cnki.11-2246.2018.0044

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Heterogeneous remote sensing image matching is an important part of the high score image processing and key issues,but the current heterogeneous high score image matching accuracy needs to be improved.In this paper, a method of SIFT matching error rejection for heterogeneous optical images based on neighborhood voting is proposed.First this paper uses the scale invariant feature transform (SIFT) to extract the feature points.Then,the secondary constraint is applied to the matching feature points based on the neighborhood voting.Finally,this paper distinguishes the error to be removed from the matching point,and determines the exact match point.In order to evaluate the accuracy of the method, it researches on the buildings, roads, water body matching respectively. Experiments show that the method can improve the matching accuracy of the above three kinds of land types,compared to the traditional SIFT method increased by an average of 66%, while effectively maintaining the scale of the scale invariance.

Impact Analysis of InSAR Spatio-temporal Baseline on DEM Accuracy

WANG Zhidong, TANG Xinming, LI Tao

2018, 0(2):  61-66.  doi:10.13474/j.cnki.11-2246.2018.0045

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InSAR is an important method of acquiring global DEM.However,the InSAR topographic mapping processing is affected by various interferometric factors,in which baseline is one of the most important elements.We quantitatively analyzed the effect of spatio-temporal baseline in InSAR topographic mapping,and analyzed 40 TerraSAR-X images of Tianjin which composed 780 interferograms after image processing.The experimental results show that the larger spatial baseline is,the higher the accuracy of elevation is,and there is a power function relationship.There is a linear function relationship between temporal baseline and accuracy of elevation,and great temporal baseline comes low accuracy of elevation.Therefore,in the process of topographic mapping,it is necessary to use the longest spatial baseline as long as the coherence is ensured,while ensuring a short temporal baseline in order to eliminate time decorrelation.This paper provides technical reference for the configuration design of homemade SAR satellite.

Research on Landslides Extraction Based on the Wenchuan Earthquake in GF-1 Remote Sensing Image

HUANG Ting, BAI Xianfu, ZHUANG Qifeng, XU Jinghai

2018, 0(2):  67-71,82.  doi:10.13474/j.cnki.11-2246.2018.0046

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Earthquake induced landslide is the most common and destructive type of earthquake, so it is of great significance to quickly and accurately obtain the distribution of landslides after the earthquake. The traditional method of artificial interpretation of remote sensing is of low efficiency. In this paper, we select the GF-1 image of the Wenchuan earthquake zone and extract the landslide information by using the object-oriented method. Multi-scale segmentation is used to set the different segmentation parameters. The suitable parameters are selected according to the features of spectrum, texture and geometry, and the classification rules are constructed to extract the landslide area. Through the comparison of landslide with landslide points by actual investigating, the accuracy of object-oriented classification method for 84%. The result shows that GF-1 data can be used to extract information of landslide hazard and meet the basic requirements of landslide hazard identification.

Multi-feature Multiple Kernels SVM-based Urban Road Extraction

LI Hongchuan, CHU Heng, HUO Yinghai

2018, 0(2):  72-77.  doi:10.13474/j.cnki.11-2246.2018.0047

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For the complex nature of urban road extraction in high-resolution remote sensing image and the classification performance of SVM,a new urban road extraction method of multi-feature multiple kernels SVM-based is proposed.Firstly,the FCM algorithm is utilized to classify the original image into the built-up areas and non-built-up areas,and the non-built-up areas are removed.Then this paper segments the built-up areas using watershed segmentation algorithm,and extracts the image objects spectral features and spatial features.This paper uses the weighted sum approach to achieve multiple kernels SVM (MKSVM) by the way of combining the global kernel function and the local kernel function.The secondary classification of built-up areas are achieved using MKSVM and remove the non-road information.Finally,the final road information is processed by using mathematics morphology.The result of experiment shows that the proposed method can fairly well extract the urban road information,and the accuracy of classification is much higher than SVM and other extraction methods.

Method for Arid Land Impervious Surface Percentage Estimation by Vegetation Index Adjustment

SHEN Qian, ZHU Changming, ZHANG Xin, HUANG Qiaohua, YANG Chengzi, ZHAO Nan

2018, 0(2):  78-82.  doi:10.13474/j.cnki.11-2246.2018.0048

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DMSP/OLS nighttime light data has been widely used in reginal impervious surface percentage estimation and monitoring. But, in the arid area, because of bare soil, desert and other the low rate of vegetation covered area effect, the accuracy and robustness of the existed algorithm was decreased seriously. In order to solve this issue, this paper used the vegetation coverage as the adjustment coefficient to adjust the light data and NDVI dynamically and build vegetation adjusted impervious surface index (VAISI). Impervious surface reference data were extracted from Landsat image, which was used as the sample data and validation data of model. And then, the non-linear relationship was built between impervious surface reference data and VAISI by SVR model to estimate the impervious surface percentage. The result indicated that the VAISI model solved the problem of higher estimated in arid land because of the bare soil around the city and the low rate of vegetation covered area, improved the impervious surface's space distribution information inside city, and overcame the obstacle of that the non-light area is higher than background values. The average correlation coefficient between the estimated result by the VAISI and the reference data were increased from 0.68 to 0.79 and RMSE was decreased from 0.17 to 0.13.

UAV Remote Sensing True Digital Orthophoto Map High Precision Mapping

LIU Yu, ZHENG Xinqi, AI Gang

2018, 0(2):  83-88.  doi:10.13474/j.cnki.11-2246.2018.0049

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In recent years,unmanned aerial vehicle(UAV) low-altitude remote sensing technology continues to develop,true digital orthophoto maps(TDOM) generated by UAV images still need to get improved in mapping accuracy and production process.In this paper,images were collected using a fixed-wing UAV and professional camera,and ground control points were laid out.A structure from motion (SfM) and multi view stereo (MVS) workflow was proposed to generate a high-precision digital surface model (DSM) and digital orthophoto map(DOM).We performed shadow tests to determine areas of tilt,perform DSM revision,and compensate for multi-view textures to produce a TDOM.Finally,we used random distributed checkpoints on the TDOM to verify its precision.The horizontal accuracy was 3.3 cm and the vertical accuracy was 7.5 cm.Tilt and shadow parts of the DOM were eliminated so that buildings maintained a vertical viewing angle.The generated TDOM meets precision requirements at the 1:500 scale. Therefore,it can be applied to rural homesteads to define land rights,land use planning,and other factors.

Improved N-FINDR Hyper-spectral Member Extraction Algorithm Based on Pure Pixel Index

YANG Pengfei, LIAO Xiuying, XU Qiheng, CHENG Hui

2018, 0(2):  89-93.  doi:10.13474/j.cnki.11-2246.2018.0050

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In order to solve the low accuracy problem of the quantitative interpretation of remote sensing images caused by mixed pixels,two different mixed pixel extraction algorithms are analyzed and compared in this paper.In consideration of the pure pixel index exponential algorithm efficiency greatly reduces as the number of iterations increases and the random choice of classical N-FINDR algorithm's element will lead to different accuracy of the solution,an improved N-FINDR algorithm based on pure pixel index is proposed.Relative to the traditional N-FINDR algorithm,the improved N-FINDR algorithm can construct the candidate element and obtain the optimal solution more efficiently.Synthesize the characteristics of hyper-spectral image data,first,the improved N-FINDR algorithm uses the pure pixel index to calculate the number of alternate port elements,and then use the classical N-FINDR algorithm to solve the maximal single-body vertex,then use the pure element completes the abundance inversion.Finally,the algorithm is verified by the air-calibrated airborne hyper-spectral data Cup95eff.int in the ENVI products.The experimental results show that the improved N-FINDR algorithm is more efficiently than the traditional N-FINDR algorithm in the aspect of endmember extraction.

Modelling the Spatial Distribution of Epidemic by Search Engine Data

XIAO Yi, HE Zongyi, MIAO Jing, PAN Feng, YANG Hao

2018, 0(2):  94-98.  doi:10.13474/j.cnki.11-2246.2018.0051

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The Internet records people's daily life,and the analyzing and mining of search engine query data with location can discover valuable geographic information hidden in it.In this paper,the correlation between the monthly influenza case data in each Chinese province and the Baidu search index of related keywords were calculated,the most related keyword's index was chosen as the explanatory variable while the influenza case data was chosen as the dependent variable.The principal component analysis was used to eliminate the effect of multicollinearity among variables before the spatial distribution model of influenza was constructed by ordinary least squares regression (OLS),geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR).The GTWR model demonstrated a better goodness-of-fit (0.959) than the OLS (0.737) and GWR model (0.915).The Akaike information criterion (AIC) test also supported that the improvement made by GTWR over OLS and GWR models were statistically significant.Validation results showed that the GTWR model can accurately identify the high prevalence area of influenza.It demonstrates that combining the GTWR model with search engine query data can model the spatial distribution of influenza accurately,and provide a prediction model and statistical explanation for the study of epidemiology.

Embedded GPS/BDS Real-time Precise Point Positioning Method

HAN Xiao, PAN Shuguo, ZHAO Qing

2018, 0(2):  99-102,163.  doi:10.13474/j.cnki.11-2246.2018.0052

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Real-time positioning and dynamic positioning are the key problems of precise point positioning.Based on the real-time track and clock correction product,the mathematical model and error processing method of GPS/BDS real-time precise point positioning are discussed in this paper.Embedded hardware and software platform is built and an embedded device with real-time GPS/BDS dual system,high-precision positioning function is developed.Test results show that for embedded GPS/BDS real-time precise point positioning,the horizontal direction is better than 3 cm and the elevation direction is better than 8 cm under static conditions,the plane direction is better than 12 cm and the elevation direction is better than 15 cm under dynamic conditions.

Detecting the Distribution and Alignment of Ground Fissures by DInSAR

HU Bo, CHEN Zhimou, WU Yang, YANG Bin, CHEN Junyu, CHEN Xiongle, CHEN Zhiwei

2018, 0(2):  103-106.  doi:10.13474/j.cnki.11-2246.2018.0053

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Ground fissure is a kind of unique urban geological disaster,which is more and more widely distributed in China,but humans can't stop it.This seriously hinder the development of economic construction and people's life and property.In this paper,we use differential interferometry synthetic aperture radar(DInSAR),taking Langfang city as study area,based on 3 screens RADARSAT-2 data from June 2016 to November 2016 to obtain the information of surface deformation in the area by means of DInSAR,and reference to the ground fissure information in 2009.Besides the distribution and trend of ground fissures will be analyzed and predicted for the production units and local government departments to decision basis on the treatment and prevention of the ground fissures.

Road Surface Data Extraction Based on Mobile Laser Scanning Data Classification

WU Xuequn, NING Jinsheng, YANG Fang

2018, 0(2):  107-110,135.  doi:10.13474/j.cnki.11-2246.2018.0054

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Mobile laser scanning system has become a cost-effective solution for obtaining point clouds of the road surface,building,vegetation,pole,etc.The automatic extraction technique of point clouds is the key to applications of mobile laser scanning system.This paper studies characteristics of road surface point clouds,a progressive mesh method is then adopted to extract road surface point clouds.Experiments show that the proposed method has a desirable solution for road surface data extracting from mobile laser scanning point clouds.

Oblique Photogrammetric Technique Applied in Surveying and Mapping Large-scale Topographic Map

XU Siqi, HUANG Xianfeng, ZHANG Fan, YONG Xiaolong, XIA Zhimin, WANG Tao

2018, 0(2):  111-115.  doi:10.13474/j.cnki.11-2246.2018.0055

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Oblique photogrammetric technique is an emerging technology in recent years in the international surveying and mapping field,already used for quick construction of 3D city model.Given the common methods of surveying and mapping large-scale topographic map cannot simultaneously meet the time and cost requirements,this paper proposes a method based on oblique photogrammetric technique.By the advantages of flexibility,low cost and high-efficiency of unmanned aerial vehicle(UAV) oblique photogrammetric technique,the oblique images can automatically generate the three-dimensional model and point cloud by software.The assessment results of the Kelan County large-scale topographic map in experiment shows that the plane accuracy is 0.140 meters and elevation accuracy is 0.150 meters,meeting the requirements.The method is suitable for surveying and mapping the large-scale topographic map of small areas.

Elevation Accuracy Assessing of SRTM,ASTER GDEM and AW3D Using GNSS Dynamic Precise Point Positioning(PPP)Data

WEI Dehong, ZHANG Yongyi, ZHANG Xingfu

2018, 0(2):  116-119,130.  doi:10.13474/j.cnki.11-2246.2018.0056

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SRTM,ASTER GDEM and AW3D are typical global digital elevation models (DEMs) and they gradually play a critical role in many applications.This paper aimed to assess SRTM,ASTER GDEM and AW3D using GNSS dynamic precise point postioning (PPP) data.Firstly,we collected data by GNSS system fixed on the roof of a car along Guangzhou to Zhaoqing highway and subsequently obtained dynamic measuring data by PPP technology.Secondly,we transformed the ellipsoidal height of dynamic measuring points to orthometric height by earth gravitation model 2008 (EGM2008) and instrument height.Finally,four interpolation methods (Linear,Nearest,Cubic and Spline) are used to validate the orthometric heights of SRTM,ASTER GDEM and AW3D.The results show that the interpolation results of four methods have a good consistency and the standard deviations (STDs) of height of SRTM3 V4.1,ASTER GDEM V2,AW3D30 are better than 3.4,4.1,and 3.3 m respectively.The validating results of three DEMs are better than their target height accuracies of 16,17,and 5 m respectively.The proposed method is quick,efficient,and applicable for assessing DEMs.

Subsidence Monitoring for Expressway Network in Beijing Based on Time-series InSAR Technique

LIU Bing, ZHANG Yonghong, WU Hongan, KANG Yonghui, JIANG Decai

2018, 0(2):  120-125,141.  doi:10.13474/j.cnki.11-2246.2018.0057

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In this paper,the ground deformation of the Beijing urban areas from 2011 to 2015 was obtained by using Multiple images Coherent Targets Small Baselines InSAR (MCTSB-InSAR)technique,with the high resolution TerraSAR-X images.By building spatial buffer,the subsidence of 12 freeways and one expressway in Beijing was extracted and analyzed.The roughness of the airport second freeway was analyzed based on the subsidence of the freeways.The monitoring results were verified with leveling data and the accuracy is 4.6 mm/a.Results demonstrated that MCTSB-InSAR technique can not only monitor the subsidence for expressway traffic network over large area,but also has high monitoring precision.

Application of Feature Selection Method in Building Information Extracting from High Resolution Remote Sensing Image

LIU Run, ZHANG Shaoliang, JIA Rong

2018, 0(2):  126-130.  doi:10.13474/j.cnki.11-2246.2018.0058

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The automatic extraction of urban building information is one of the key technologies of urban remote sensing,however,the accuracy of extraction is often unstable due to many factors such as shadows and undersides.Taking the Pleiades satellite image as a basic data source,the paper explores the feasibility of urban building information extraction by advanced Relief F feature selection method.Firstly,the basic feature space of buildings with high resolution remote sensing image is built.Then,the optimal characteristics are selected by the weights which are determined by advanced Relief F algorithm.Finally,the supervised classification,the non-feature selection classification,and the advanced Relief F feature selection methods are respectively used to extract the building information in the study area,and the accuracy of the extraction is verified and compared by site investigation data.The result shows that the advanced Relief F method can reach a higher accuracy with 91.34% and a higher extraction speed with 34.31% and 5.62% higher than the other two methods.The result demonstrates that the advanced Relief F feature selection method has certain reliability and applicability,and can make the work of building information extraction become more automatic and intelligent.

Analysis of Directional Parameters Based on Mini SAR Image

CHEN Jiao, GUO Zengzhang, WANG Shuangting, WANG Chunyang, LIU Pei

2018, 0(2):  131-135.  doi:10.13474/j.cnki.11-2246.2018.0059

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In this paper,the author analyzes the characteristics of small POS data.The measurement error that caused by instrument accuracy can not be eliminated in the imaging process,the remaining phase error causes several targets appear azimuth defocusing and blur,which leads to the coordinate error of the image target point.The author applies the traditional directional parameter calculation method to Mini SAR single image locate,there will the number of ground control points,image coordinates,the tolerance of directional parameter error vector,terrain features,DEM resolution,the accuracy of POS data and other factors will affect the positioning results.When the high positioning accuracy is not necessary,polynomial interpolation of POS data results is more accurate than fitting.

Wallis Dodging and Mosaic Algorithm for Super Resolution Reconstruction Images

FAN You, CHEN Xushuai, WANG Dandan, BAI Mingliang, ZHOU Min

2018, 0(2):  136-141.  doi:10.13474/j.cnki.11-2246.2018.0060

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A sub-block algorithm is usually applied in the super resolution reconstruction of images because of the limitation of computer memory. However, the sub-block super resolution images can hardly achieve a seamless mosaicking image because of the uneven distribution of brightness and contrast among these sub-blocks. An effectively improved weighted Wallis dodging algorithm is proposed, aiming at the characteristics that images after image super resolution reconstruction are non-overlapping gray images with the same size. The algorithm uses an innovative adjustment sequence, and applies a weighted method to calculate the Wallis filter parameters. It can avoid the spatial propagation and accumulation of errors and the loss of image information caused by excessive computation. Subsequently, the improved method is employed to remove the uneven illumination for 900 SR reconstructed images of ZY-3. The results of experiments show that the method gets better dodging effect. Consistency of image brightness and contrast is achieved, eliminating the seam lines.

A New Mothod to Generate ADS Orthophoto Image

ZENG Yu, SU Xiaobin

2018, 0(2):  142-147.  doi:10.13474/j.cnki.11-2246.2018.0061

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ADS orthophoto image is mainly for the real estate registration to provide the basic base map,but in the production of ADS orthophoto imaging process,the key link is how to quickly and effectively edit the high-precision DEM,DEM directly determines the quality of the orthographic image.The traditional method of processing in the three-dimensional is to edit the feature points,lines,faces manually,the advantages is high precision,but the disadvantage is low,long cycle,put human and material resources.Based on this problem,this paper proposes a method to generate high-precision ADS orthophoto image by using the basic data of geography and national conditions to assist in the rapid editing of DSM.Experiments show that the method can quickly edit the DSM,so as to produce orthophoto images that meet the precision requirements,which greatly improves the work efficiency and has a wide range of promotional value.

A 3D Modeling and Visualization Method of Ground Fissures Based on Shape Parameters

DAI Huayang, WANG Xiang, LI Jun, GUO Junting, YAN Yueguan

2018, 0(2):  148-153.  doi:10.13474/j.cnki.11-2246.2018.0062

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Modeling and visualizing ground fissures caused by mining in three dimensions can facilitate studying the shape and contributing factors of fissures,and also provide scientific support for monitoring mining subsidence and restoring ecological environment.The existing 3D modeling methods and software mainly focus on buildings,pipes,geologic bodies et al.,which can not be directly used to model and represent ground fissures.In view of this problem,using 3D terrain modeling,fractal theory and spatial interpolation,this paper proposes a 3D modeling method of ground fissures based on geometric shape parameters,and implements the 3D visualization of fissures through ArcEngine platform.This paper selects the Dongxia Mining Area in Gansu province as study area,and create 3D models of all ground fissures in this area from the predicted distribution and shape parameters.The comparison results between ground surveyed data,high resolution images and the created models validate the proposed method can accurately demonstrate the shape,stretching and details of ground fissures.

Research on the Application of Leica 3D Laser Scanning System in the Fine Modeling of Buildings

ZHU Shuguang, HE Kuan, ZHOU Jianzheng

2018, 0(2):  154-156.  doi:10.13474/j.cnki.11-2246.2018.0063

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As a new technology of surveying and mapping,3D laser scanning technology has changed the traditional surveying mode.Massive point cloud data can be gained quickly,efficiently and continuously using 3D laser scanning technology and then the 3D model of the target through processing.This paper mainly introduces the application of the software 3D laser scanning system of Leica Scan Station P40 in the fine modeling of complex buildings.Some useful conclusions are drown through the accuracy analysis of point cloud data and modeling.

The Application of Leica 3D Disto in Building Elevation Measurement

ZHOU Huantong, WANG Xin, ZHANG Xibo, DING Guoxin

2018, 0(2):  157-159.  doi:10.13474/j.cnki.11-2246.2018.0064

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With the start of the digital city construction,especially the implementation of the three-dimensional simulation of the digital city,the building elevation measurement has been more and more widely used.Therefore,we often need to measure the elevation of the original building.The points on the elevation are all on a vertical plane.The conventional measurement method is difficult to measure.This paper focuses on the construction of building facade map using Leica 3D Disto through non-contact measurement.The measurement method is simple,fast,time saving and labor-saving,and the precision can also meet the requirements of the mapping.

UAV Integration with Ground Scanner of Terrain Measurement

LI Peng, LIN Jie, LI Huan

2018, 0(2):  160-163.  doi:10.13474/j.cnki.11-2246.2018.0065

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In recent years,there are more and more institutions for topographic survey with UAV as carrier.However,the existing UAV achievements can not meet the requirements of large scale in both elevation and housing.In order to solve this problem,we carries out the operation of combining the ground scanner with the UAV.The result shows that the accuracy of this method can meet the mapping requirements of 1:1000 topographic map.