Table of Content

25 July 2019, Volume 0 Issue 7

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Research on surface snow depth retrieval of new L5 signals from GPS

HUANG Liangke, ZHOU Wei, LIU Lilong, CHEN Jun, WANG Haoyu

2019, 0(7):  1-5,11.  doi:10.13474/j.cnki.11-2246.2019.0208

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Global Positioning System multipath reflected signals can be used to measure surface snow depths, which has all-weather and high spatial-temporal resolution characteristics. Therefore, GPS-R technology can be used as a new method for monitoring surface snow depths instead of meteorological stations. However, most previous studies have only used the signal-to-noise ratio (SNR) data of GPS L1 and L2C signal to detect snow depth. In order to test the superiority of GPS-R technology based the new L5 signal in snow depth retrieval, this paper describes the basic principles of GPS-R technology for retrieving snow depth and uses Lomb-Scargle periodogram method to calculate spectral amplitude of the SNR data of the reflected signals affected by the snow surface. Snow depths are obtained by using the relationship between the spectral characteristic value and the antenna height. Finally, the retrieved snow depths are compared with the results of GPS L1 signals and in situ measurements, respectively. The results show that the performance of GPS-R technology with the new L5 signal is high better in snow depth retrieval when compared with that of GPS L1-SNR signals. In addition, it is of great value for snow depth variations and freshwater resource around the GNSS station to use GPS-R technology to detect land-surface snow depths.

A spectral unmixing method of using spatial information to select optimal endmember subset

XU Jun, WANG Cailing

2019, 0(7):  6-11.  doi:10.13474/j.cnki.11-2246.2019.0209

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The traditional spectral unmixing algorithm considers that each pixel contains all the endmembers extracted from the image, which does not conform to the actual situation. In fact, most of the mixed pixels in the image are only mixed by a small number of endmembers. Because of the influences of endmember extraction precision and noise, if all endmembers are used in spectral unmixing, it will make the abundances of the endmembers which are not involved in the mixed pixel are not zero, the spectral unmixing results have large errors. Because most of the mixed pixels are located at the junction of different ground objects, this paper proposes a method to select the optimal endmember subset of mixed pixels by utilizing the spatial information of the image. Using a spatial structure element, this method starts to search pure pixel spectrum from the adjacent domains of the mixed pixels, then compares the searched pure pixel spectrum with the previously extracted image endmembers to determine the endmember subset of the mixed pixels. According to the variation of RMSE, the size of the structural element is gradually expanded, and the search scope is constantly adjusted until the optimal endmember set is obtained. The experimental results of the simulated data and the real data show that the proposed method has a relatively better spectral unmixing effect compared with the traditional spectral unmixing method using all endmembers.

Discussion on classification methods of urban features based on GF-2 images

WANG Fang, YANG Wunian, WANG Jian, XIE Bing, YANG Xin, REN Jintong

2019, 0(7):  12-16.  doi:10.13474/j.cnki.11-2246.2019.0210

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The GF-2 image has higher resolution as well as more detailed characteristics of spectral, features, geometric and texture. In order to explore the classification method of the GF-2 image in urban features, an object oriented classification method based on optimal scale and rules is proposed in the study area of Longchang County, Sichuan Province. Based on segmentations, the evaluation function is constructed, combining with the maximum area method, optimal segmentation scales are selected to construct multiple layers. The spectral, geometric and texture features of the image are extracted to establish rules for classification and compared with the classification methods of object-oriented with the single scale and pixel based. The results show that the overall accuracy and Kappa coefficient of the proposed method are 93.33% and 0.92, respectively.

Scene classification of high-resolution remote sensing image based on deep convolution neural network

MENG Qingxiang, WU Xuan

2019, 0(7):  17-22.  doi:10.13474/j.cnki.11-2246.2019.0211

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Scene classification makes great sense to the understanding and information extraction of high-resolution remote sensing images. The traditional method has used low-level, middle-level or semantic features to distinguish the class of the image scene, but the low or middle level features can't exactly describe the image which are more detailed and complex. In this paper, a DCNN scene classification model based on deep convolution neural network is proposed. The convolution layer is used to extract the image texture, color and other low-level features firstly. Then we use the pool layer to select important features. Finally, the extracted features are merged into high-level semantic features which are used to classify the high resolution remote sensing images. To solve the problem of over fitting, data augmentation, regularization and Dropout are used to improve the generalization ability. This method has obtained 91.33% accuracies on UC Merced-21. Compared with traditional method, the classification accuracies is effectively improved. At the same time, the superiority of deep convolution neural network in remote sensing image classification is proved.

Research on geographically weighted regression based on IGGⅢ

YU Zhiying, ZHANG Fuhao, QIU Agen, ZHAO Yangyang

2019, 0(7):  23-27.  doi:10.13474/j.cnki.11-2246.2019.0212

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Aiming at the problem that the geographically weighted regression model has poor fitting effect when the outliers exist, a geographically weighted regression method based on IGGⅢ is proposed. The core is to use the weight function in the IGGⅢ scheme to calculate the weight matrix, and the weight factor is used in the geo-weighted regression parameter estimation model. The simulation data and the real data are used for the test, compared with GWR and ACV-GWR, and the results were evaluated by MSE, MAE and R². The simulation results show that the performance of IGGⅢ-GWR is increased by 51.14%, 23.77% and 28.4% than GWR, increased by 49.96%, 22.57% and 27.1% than ACV-GWR. The actual experimental results show that IGGⅢ-GWR is 12.65%, 7.44% and 0.37% higher than GWR, respectively, and 11.85%, 6.96% and 0.34% higher than ACV-GWR. The experimental results show that the IGGⅢ-GWR can improve the robustness and fitting effect of GWR.

Power line identification algorithm for aerial image in complex background

ZHAO Haocheng, LEI Junfeng, WANG Xianpei, ZHAO Le, TIAN Meng, CAO Wenbin, YAO Hongtai, CAI Bingbing

2019, 0(7):  28-32.  doi:10.13474/j.cnki.11-2246.2019.0213

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How to completely and accurately identify the power line from the aerial image of the drone with complex background has become one of the key issues for the unmanned inspection of the power line. After analyzing the characteristics of the power line in the aerial image, a new algorithm of power line detection and identification in complex backgrounds is proposed. Firstly, the original image is histogram equalized to improve the contrast ratio. Then, the edge image is detected by the EDPF algorithm improved by the LoG operator, with the background noise filtered out and the power line edge detected. Finally, the power lines in the image are completely extracted using the Radon transform and prior knowledge. The experimental results show that the proposed method has higher recognition accuracy, more complete recognition effect and better robustness compared with the traditional Canny operator and Hough transform and the LSD algorithm.

Fractional vegetation cover estimation in aird and rare vegetation area aided by GF-2 remote sensing data

SHEN Qian, ZHU Changming, ZHANG Xin

2019, 0(7):  33-38.  doi:10.13474/j.cnki.11-2246.2019.0214

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The dimidiate pixel model has been widely used in the estimation of fractional vegetation cover because of its simple form and strong applicability. However, studies have shown that selecting parameters in model from 250 m spatial resolution images is very difficult in arid area with low fractional vegetation cover and desert. The estimation result is generally overestimated by using the parameters in model, NDVI_veg and NDVI_soil, acquired by the commonly used histogram accumulation method in the low fractional vegetation cover area with more bare soil and desert. So, this paper firstly used GF-2 high-resolution images of the same time with MODIS to map vegetation cover pixel. Then, Pixel Aggregate method was used to resample vegetation cover map from 0.8 m to 250 m spatial resolution to map pure vegetation cover pixels and pure bare soil pixels with 250 m spatial resolution. The maximum value of MODIS NDVI data corresponding to the spatial position of pure vegetation and pure bare soil pixels was taken as the NDVI_veg and NDVI_soil parameters required by the model to estimate the vegetation cover in the study area to estimate fractional vegetation cover. The estimation accuracy of linear regression method, nonlinear regression method, dimidiate pixel model based on histogram accumulation method to get parameters and based on GF-2 images to get parameters were compared.The results of experiment indicate that dimidiate pixel model based on GF-2 images accurately selected the parameters, NDVI_veg and NDVI_soil, in the low fractional vegetation cover area. This method improves the estimation accuracy of fractional vegetation cover in the arid area, and suppresses the result overestimation in low fractional vegetation cover area due to the effect of the higher NDVI problem in the sparse vegetation area.

Using Sentinel-1A/1B radar data to monitor the retreat of Antarctic grounding line

XU Zhida, WANG Zhiyong, TAN Jianwei

2019, 0(7):  39-43,49.  doi:10.13474/j.cnki.11-2246.2019.0215

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The accurate determination of the position of Antarctic grounding line is of great importance to the calculation of Antarctic material balance and the glacial dynamics. The basic principle of the DDInSAR extraction ground line is described, and the ground line of ice shelves along the Queen Maud Land of the east Antarctica and Dotson on the west of the Amundsen Bay of the west Antarctic are extracted using the Sentinel-1A/1B radar data. The extraction results are compared with the existing ground line product MEa-SUREs. The results show that using the Sentinel-1A/1B radar data based on DDInSAR method can extract and update the Antarctic ground line, and continuously monitor the grounding line retreat. Through monitoring, it can be found that in the area of Dotson Ice Shelf, the grounding line has undergone a large retreat, approximately 2~5 km back over the 22 years from 1996 to 2018, with a maximum retreat of 7.4 km.

Airport detection using convolutional neural network and salient feature

YU Donghang, ZHANG Ning, ZHANG Baoming, GUO Haitao, LU Jun

2019, 0(7):  44-49.  doi:10.13474/j.cnki.11-2246.2019.0216

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Existing algorithms of airport detection using handcraft features perform time-consuming and poor robustness. In view of these problems, this paper proposes a method using convolutional neural network and salient feature. First, a deep convolutional neural network is used to extract the regions of interest (ROI) from complex remote sensing images. Then, saliency detection based on frequency-tuned is introduced to get saliency map of those regions. Through segment on the saliency map and marking the connected region on the binary image, the maximum connected region which is most likely be area of the airport is extracted. Different kinds of airports are used to test and the results show that the proposed method has obvious advantages in precision and speed. With the aid of saliency detection, the precise boundary of the airport and runway can be obtained effectively and the effect and practical value of the airport detection are hugely improved.

A settlement prediction model of high-speed railway pier based on GA-BP-MC neural network

FENG Shaoquan, HUA Xianghong, TAO Wuyong, XUAN Wei, WU Wei, XU Dong

2019, 0(7):  50-53,82.  doi:10.13474/j.cnki.11-2246.2019.0217

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A genetic BP neural network prediction model (GA-BP-MC) based on Markov chain modification is proposed. The weights and thresholds of BP neural network are initialized by the global optimization ability of genetic algorithm, and the prediction model of GA-BP neural network is established preliminarily. The predictive value of model is modified by the invalidity of Markov chain to form a high precision deformation prediction model of GA-BP-MC neural network. Combined with the settlement data of high-speed railway piers, and compared with the BP neural network and GA-BP neural network prediction models respectively, the results show that the accuracy of the prediction model is highest.

The method of mining subsidence deformation monitoring and prediction based on D-InSAR with GIS technology

CHEN Yincui, XU Liangji, YU Liren

2019, 0(7):  54-58,63.  doi:10.13474/j.cnki.11-2246.2019.0218

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Synthetic aperture radar differential interferometry (D-InSAR) technology can monitor large-scale surface deformation information, but a single D-InSAR technique cannot accurately analyze the range and location of the settlement distribution.Firstly, we selected two images of the C-band Radarsat-2 from July to December and the six-monthly Sentinel-1 images from April to May 2015 as the number of interference images. According to the composition of the six interferometric pairs, they were differentially interpolated by the second-track method. Processing and phase unwrapping to extract interferograms. The D-InSAR differential interferograms were imported into ArcGIS with mining planes and mining plan maps to analyze the spatial dynamic distribution of mining subsidence areas in the mining area and quantitative analysis. And finally using a grey theoretical model prediction.The results show that the D-InSAR overlay analysis can reflect the location and distribution of the settlement area during coal mining. The maximum relative error and variance ratio between the predicted and measured D-InSAR values are 11.5% and 0.097 respectively.

Real-time GPS/GLONASS satellite clock estimation with GLONASS inter-frequency biases

ZHANG Tao, LI Guopeng, LIU Zhanke, ZHANG Qingtao, CHEN Xiaoying, LIU Yi

2019, 0(7):  59-63.  doi:10.13474/j.cnki.11-2246.2019.0219

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GLONASS system generates inter-frequency bias (IFB) using frequency division multiple access technology to distinguish satellite signals in the process of GPS/GLONASS satellite clock estimation. Base on the analysis of IFB parameter characteristics in the orbit determination process, the IFB is considered on the real-time GPS/GLONASS satellite clock estimation. At the same time, in order to solve the problem of weak real-time caused by excessive parameters in this estimation process, the mathematical model is improved based on the non-difference pseudo-range observation value and the difference phase observation between the epochs. The results show that the clock estimation needs to consider the IFB and optimize its estimation strategy. The real-time clock is calculated by the MGEX and iGMAS tracking stations data and only costs 1.6 s of an epoch. Compared with the final precision satellite clock provided by GBM, the accuracy of GPS satellite clock is about 0.210 ns, and the GLONASS is about 0.298 ns.

Arctic sea ice freeboard determination from CryoSat-2 satellite altimetry data

WU Xingquan, ZHANG Shengjun, CHE Defu

2019, 0(7):  64-68.  doi:10.13474/j.cnki.11-2246.2019.0220

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The technology of satellite altimetry has made it possible to detect sea ice at large spatial scales, while the retrieved sea ice freeboard is a key parameter for inverting sea ice thickness. Moreover, obtaining accurate freeboard is significant for sea ice detection and the understanding of global climate change. Based on the CryoSat-2 satellite SAR mode altimetry data accumulated in the past three years, this paper selectes the available observation data by setting thresholds in the Arctic within the 60°N-88°N latitude zone, and calculates the average monthly sea ice freeboard during 2015-2017. The results of the calculated freeboard in the research region are reliable according to the verification with the space-time matched measurements of IceBridge projects.

High-resolution remote sensing image classification using OpenStreetMap data

HAO Huaixu, WAN Taili, LUO Nianxue

2019, 0(7):  69-72,126.  doi:10.13474/j.cnki.11-2246.2019.0221

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To address the difficulties of labeling samples for high-resolution remote sensing images, an automatic method of labeling samples employing OpenStreetMap (OSM) data is proposed in this paper. Different from the existing approaches, the proposed method adopts spatial features to supplement the shortcomings of using only spectral features. Firstly, samples are labeled using the category and position information of OSM data. As OSM data may contain errors, cluster analysis is utilized to refine the derived samples. Besides, to exploit the abundant spatial information provided by high resolution remote sensing images, morphological profiles are used to describe the structural features of the images. The spatial features as well as spectral features are combined for classification. Experiments show that the proposed method can significantly avoid the manpower and material resources required for labeling samples artificially. Meanwhile, the derived samples and the spectral-spatial features both contribute to the classification accuracy.

Extraction of high-rise and low-rise building areas from Sentinel-2 data based on full convolution networks

YAN Zhi, LI Liwei, CHENG Gang

2019, 0(7):  73-77.  doi:10.13474/j.cnki.11-2246.2019.0222

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This paper proposes a fully convolutional networks based method to intelligently exploit Sentinel-2 data for high-rise and low-rise building areas extraction. The building areas are divided into high-rise building areas and low-rise building areas according to their spatial structure in Sentinel-2 data and their real functional types. Four Sentinel-2 data covering the Xiong'an New Area and its surroundings in early 2017 is selected for experimental verification and analysis. The results show that the proposed algorithm can extract the high-rise and low-rise building areas from Sentinel-2 data in an effective and efficient manner. Overall accuracy of the two types of building areas is about 95.30%, of which the high-rise building areas accuracy is about 99.22%, and the accuracy of other building areas is about 91.38%. Compared with the existing texture-based method, the proposed method is more robust and fast. The high-rise and low-rise building areas in the study area covering about 44 000 km² are about 94 and 7351 km², respectively. The high-rise and low-rise building areas in the three core counties of Xiong'an New Area are about 1.25 and 312.24 km², respectively. Our method can be easily extend to extract finer types of building areas given proper training samples of finer types of buildings areas and can realize large scale dynamic monitoring with the large imaging width and the high-frequency observation of Sentinel-2 data.

Monitoring method of bursaphelenchus xylophilus based on multi-feature CRF by UAV image

LIU Jincang, WANG Chengbo, CHANG Yuanfei

2019, 0(7):  78-82.  doi:10.13474/j.cnki.11-2246.2019.0223

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The use of UAV remote sensing technology for forest survey can obtain low-cost, high-resolution, high-time-density remote sensing data, especially for small-scale forest pest monitoring. In this paper, we use the small unmanned aerial vehicle as the image acquisition platform, acquire the RGB image, and study the extraction method of red-attacked pine based on the high resolution image. According to the image characteristics, the color and texture features of the image are extracted, and the CRF method is adopted to identify red-attacked pine. The feasibility and effectiveness of the multi-feature conditional random field method in the monitoring of bursaphelenchus xylophilus is verified by comparing the extraction results of multiple classification methods.

Method of refined 3D model construction of space-ground integration

BIAN Min, XU Liang, LUO Yuanpeng, ZHOU Xiaobo, ZHAO Huifeng, YANG Huachao

2019, 0(7):  83-86.  doi:10.13474/j.cnki.11-2246.2019.0224

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Technique of UAV oblique photogrammetry has become the preferred method for 3D reconstruction of large scene because of its low cost and high efficiency. Model deformation, texture missing and other issues are often accompanied in the process of 3D reconstruction of oblique photography.In the construction of 3D digital campus based on the technology of low-altitude oblique photogrammetry, aiming at the problems arising from different types of ground objects after reconstruction, this paper proposes a method to construct a refined 3D model through the integration of space and ground,the combination of virtual and real by integrating the advantages of various modeling methods, which has important reference significance for the precise modeling of 3D model of low-altitude oblique photography.

The solution and application of 1∶500 high precision three-dimensional mapping based on UAV oblique photography

ZHAO Xiaoyang, SUN Songmei

2019, 0(7):  87-91.  doi:10.13474/j.cnki.11-2246.2019.0225

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This paper presents a plan for 1:500 large scale topographic mapping based on UAV. To control the root mean square error of the point in plane and elevation direction within 5 cm, several improvements have been made for UAVs, including platform stability, accurate positioning and control in flight, aerotriangulation and three-dimensional modeling, as well as image combined multi-view mapping. The application in Mali Village of Guangzhou indicates that, the UAV oblique photography plan shows great potential in the 1:500 three-dimensional mapping in terms of accuracy and efficiency.

Discussion on 3D mapping technology based on tilting image of consumer-grade UAV

WU Xianwen, ZHANG Peng, ZENG Lin

2019, 0(7):  92-95.  doi:10.13474/j.cnki.11-2246.2019.0226

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Tilting photogrammetry, as a new new technology of surveying and mapping, has been applied well in various fields, but the mainstream aerial photogrammetry aircraft used in surveying and mapping is expensive and complex. In this paper, a method of mapping large scale topographic maps using real 3D models made from tilted images captured by consumer-grade UAVs is presented. This method makes full use of the advantages of low cost, simple operation and advantages of automated modeling. It can produce high-quality and high-precision reality 3D models and 1:500 topographic maps in a short time. Practice shows that the method is simple to operate, the technical route is feasible, and the product accuracy meets the requirements of relevant standards and specifications.The overall efficiency of this method is better than that of traditional surveying and mapping methods,it has the significance of popularization.

Research on rapid batch production method of multi-source high-resolution DOM

ZHANG Yaya, MA Xiaoji, ZHOU Yi

2019, 0(7):  96-99,146.  doi:10.13474/j.cnki.11-2246.2019.0227

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With the wide application of remote sensing data in natural resource surveys, there is a higher demand for mass production of "one map" of multi-source high-resolution remote sensing images. This paper takes Yinhai District, Beihai of Guangxi province as test area and uses the "RS + GIS + Photoshop" algorithm of Pixel Engine software. First, according to the characteristics of multi-source and high-resolution remote sensing satellite data, the corresponding data processing process is formulated, and the single scene DOM is produced automatically. Then, taking the county-level jurisdiction as the unit, the county-level jurisdiction DOM produced quickly in batches. Finally, from the two aspects of production precision and speed, the DOM results produced by this method are compared with the manual processing results. By analyzing the feasibility of the method, it turns out to be a fast and effective production method of multi-source high-resolution DOM.

Research on coordinate unification process of indoor panoramic images

LIU Xiaofen, XIE Gangsheng, WANG Dandan, LONG Shaoqiu

2019, 0(7):  100-103,113.  doi:10.13474/j.cnki.11-2246.2019.0228

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Aiming at the problem that NavVis indoor panoramic image and point cloud results must be displayed in its own system, which is not conducive to the promotion of indoor panoramic image and point cloud results in other systems and software, this paper studies the panoramic image results processed by NavVis multi-scan data sets, and verifies the technical route of coordinate unification of NavVis panoramic image results, which is used for NavV. Is panoramic image results unrestricted use in other systems, software provides a solution to promote the practical application of high-precision indoor panoramic image.

Research on optimizing algorithms for massive model of network three-dimensional digital city

CHENG Liangyong, LI Nanjiang

2019, 0(7):  104-108.  doi:10.13474/j.cnki.11-2246.2019.0229

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Large-scale massive 3D model data network transmission and terminal visualization are the key technologies of web-oriented 3D GIS application. This paper proposes a combination of 3D model adaptive surface deletion simplification algorithm and terrain model one-sided automatic generation algorithm to realize large-scale simplified LOD (level of detail model) model library automatic building, effectively solving massive high-precision, large-scale 3D model library. The application of the model to web-oriented 3D GIS has been successfully experimented in Tianjin network 3D digital urban planning management system project, and the results are remarkable.

Analysis and design of online map audit and approval system

BAI Jinghui

2019, 0(7):  109-113.  doi:10.13474/j.cnki.11-2246.2019.0230

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With the development of computer science and the rise of "internet+" industry, E-government has become an important part of facilitating the democratization of approval services. Map audit, as a administrative licensing, is separated by 4 manual business steps:application and acceptance, technological review, approval and service and case record. The work provides a basis for the construction, evaluation and improvement of the system. It could also be used as a reference for the construction of other similar systems.

Tri-level research of natural resources data

ZHOU Guoxin, WAN Baolin

2019, 0(7):  114-117.  doi:10.13474/j.cnki.11-2246.2019.0231

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Natural resource management involves many businesses, with the development of information technology. Corresponding information systems have been established to support different businesses, and gradually accumulate a large number of data resources, including different topics of natural resources. The arrival of big data requires close contact and integration between departments. The application of these data has indeed improved the public service capacity of natural resources. However, the information systems are still independent of each other, which posing obstacles to the application of natural resources. Based on enterprise service bus technology, Guangdong approval system of construction land is taken as a case to study the application patterns of natural resources in the province-city-county levels. The methods, design and work patterns of the technology are comprehensively explored for promoting technology application.

Study on the supervision of Internet ‘problem map’ under the mode of situation awareness

ZHANG Yuxin, ZUO Dong

2019, 0(7):  118-121,137.  doi:10.13474/j.cnki.11-2246.2019.0232

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In recent years, the use of maps to cooperate with relevant news reports on traditional media website and emerging we-media platforms such as Weibo, WeChat has shown an obvious upward trend. At present, China's surveying and mapping administrative departments have established a corresponding software supervision platform. A large number of ‘problem maps’ are monitored by the system every day. But when the problem map is detected, the data storage mode adopted by the system is far from suitable for the development trend of the current multi-dimension, three-dimensional digital information storage, analysis era of big data. This paper will study the current situation awareness technology, combined with the specific characteristics of Internet ‘problem map’ supervision, design the format of problem map model and the specification of large database of ‘problem map’. Based on the simulation, several kinds of ‘problem map’ situation analysis models will be developed, to explore the supervision of Internet ‘problem map’ under the mode of situation awareness, so that the relevant work of national Internet geographic information supervision can be further developed.

Calibration for multi-temporal NPP/VIIRS nighttime light remote sensing images

LI Mingfeng, CAI Weiheng

2019, 0(7):  122-126.  doi:10.13474/j.cnki.11-2246.2019.0233

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To solve the problem of ephemeral lights source and background noise for NPP/VⅡRS images, the multi-temporal nighttime light remote sensing images calibration method is proposed based on the radiation characteristics of monthly images. The radiation difference of the images is amplified by the spike characterization. The high-pass convolution operation is used to distinguish the stable pixel from the abnormal pixel. On the basis of this, an adaptive threshold segmentation method called the maximum entropy is used to resegment the aliasing noise at the convolution boundary. Through analysis of experimental results, the abnormal fluctuation of the original image is corrected, and the abnormal pixels are eliminated. After calibration, the correlation between VⅡRS data and quarterly economic data is stronger. The lack of micro-scale research on nighttime light remote sensing data is compensated, and the dynamic assessment for socio-economic data is provided with new ways.

Correction of nighttime light images of DMSP/OLS in China

LU Xiu, LI Jia, DUAN Ping, ZHANG Birong, LI Chen

2019, 0(7):  127-131,159.  doi:10.13474/j.cnki.11-2246.2019.0234

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The nighttime light images acquired by the operational linescan system (OLS) equipped with the Defense Meteorological Satellite Program (DMSP) have strong photoelectric amplification capability, small storage capacity and can directly reflect human activities. It is applied to urbanization monitoring and social and economic factors estimation. However, each sensor that obtains these data sets has not been scaled on the star, there is a problem of pixel saturation, and these data obtained by the sensors lacks comparability and continuity from 1992 to 2013 and cannot be directly used for long-term sequences. The study therefore requires the correction of long-term sequence DMSP/OLS nighttime light images. The correction includes mutual correction, saturation correction, annual fusion, inter-annual correction, etc. among the various light images in China. And the rationality test of the corrected DMSP/OLS nighttime light images. The test results show that the calibration method is feasible.

Application potential analysis of LJ1-01 new nighttime light data

ZHONG Liang, LIU Xiaosheng

2019, 0(7):  132-137.  doi:10.13474/j.cnki.11-2246.2019.0235

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Nighttime light data is increasingly used in areas related to human space activities. The LJ1-01 new nighttime light remote sensing satellite developed by the team of Wuhan University of China is the first professional nighttime light remote sensing satellite in the world. In order to understand the characteristic information and application potential of its data, this paper compares it with SNPP-VⅡRS nighttime light data in satellite parameters, data characteristics, data noise and application accuracy. The results show that the new nighttime light image of LJ1-01 has higher resolution and better detail features, and shows higher correlation in human space activities, reflecting the greater application potential of LJ1-01 nighttime light images. It can make a longer-term contribution to the sustainable development of mankind.

Correction and fitting of night light images of DMSP/OLS and VIIRS/DNB

LI Xueping, GONG Lu

2019, 0(7):  138-146.  doi:10.13474/j.cnki.11-2246.2019.0236

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In this paper, the DMSP/OLS image data is corrected by mutual invariance, continuity correction and oversaturation correction. The corrected DMSP/OLS data is used as a reference to reclassify the VⅡRS/DNB data. The two image data are used in time. The VⅡRS/DNB data fitted to the overlapping area in the space and the results are evaluated to obtain long-term continuous and stable nighttime lighting data. At the same time, the relationship between image data and social and economic indicators of Xinjiang regional corrections, the total population at the end of the year, total production value, average daily power consumption, construction land use are established, and the ability of nighttime lighting data to simulate social and economic parameters under long-term sequence is explored. The results show that the nighttime light image after correction by the invariant object method is more stable and continuous, which reduces the magnitude difference of the DN value between the VⅡRS/DNB data and the DMSP/OLS data pixel, making the light data under long-term sequence comparable. The correlation between long-term sequential nighttime lighting data and socioeconomic parameters after correction is high, indicating that the corrected long-term sequence light image data is consistent with socioeconomic indicators at the provincial level.

RTSVD algorithm to remove DMSP/OLS image blurring

YU Zhiwen, REN Chao, DENG Kaiyuan, BI Xuanxuan

2019, 0(7):  147-150.  doi:10.13474/j.cnki.11-2246.2019.0237

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DMSP/OLS, as the earliest nighttime light remote sensing data, has great application value and can greatly improve the data quality by solving the blurring problem existing in the data. The blur reason is analyzed, and a new algorithm of regularization truncated singular value decomposition (RTSVD) combining with Pct image luminescence frequency filtering is proposed, which can effectively eliminate the blurring phenomenon and retain the real information of the image. Firstly, considering that the luminescence frequency of the light source pixel must be higher than that of the non-light source pixel, the luminescence frequency of the pixel in the Pct image is used to exclude the non-light source pixel in the average light image, and then the truncation parameter of the regularized truncation singular value decomposition (RTSVD) is obtained by using the L curve, so as to decompose and recombine the image. The experiments show that the regularized truncation singular value decomposition method combined with Pct image luminescence frequency filtering can remove the blurring phenomenon on the basis of preserving the image information.

Fusion of unmanned boat and network RTK technology for the measurement of earthwork volume in open pit

JI Xufa

2019, 0(7):  151-155.  doi:10.13474/j.cnki.11-2246.2019.0238

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The method of combining unmanned boat with network GNSS RTK technology is used to measure the topography and calculate the earthwork of an area, which coveres both land and water. The unmanned boat is used to survey the underwater topography, while the network GNSS RTK is used to measure the landform. Afterwards, the volume of earthwork is calculated through the method of DTM, which is based on irregular triangle network with the fusing data of landform and underwater topography, the underwater relief map is also obtained through the data of underwater topography, which is measured by unmanned boat. Both the volume of earthwork and underwater relief map can provide basis for project construction. The method of combining the unmanned boat and the network GNSS RTK technology proposed in this paper can provide an important reference for measurement practice of related engineering.

Application of UAV aerial survey in coastline surveying and mapping of the Yangtze river

XIE Liang, WU Zhengwei

2019, 0(7):  156-159.  doi:10.13474/j.cnki.11-2246.2019.0239

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UAV aerial survey is a new emerging technology of surveying and mapping, which is in good graces of the production units of surveying and mapping for its advantages of high surveying efficiency,small ground constraintsand and automatic mapping. This paper describes the application of Topcon Sirius UAV aerial survey in coastline surveying and mapping of the Yangtze river of Taizhou. High resolution images, digital elevation model and digital terrain model have been generated, and the accuracy analysis of the result shows that the aerial survey can meet the requirements of large scale mapping, which provides a new method for coastline surveying and mapping of the Yangtze River.The practice has a good guidance and reference function for UAV aerial survey.

Application of 3D laser scanning technology in detailed investigation of 1∶10 000 geological disasters: taking Xingtai Canyon Group National Geological Park in Hebei province as an example

LI Donghai

2019, 0(7):  160-162.  doi:10.13474/j.cnki.11-2246.2019.0240

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Using the latest 3D laser scanning technology to collect data on the geological conditions of the Xingtai Canyon Group in Hebei province.Using 3D point cloud processing software to process and analyze the collected geological 3D point cloud to obtain profile and elevation data, which can provide favorable prevention data for local geological management departments.