Acta Geodaetica et Cartographica Sinica

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Generalized photogrammetry of spaceborne, airborne and terrestrial multi-source remote sensing datasets

ZHANG Yongjun, ZHANG Zuxun, GONG Jianya

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 1-11. DOI: 10.11947/j.AGCS.2021.20200245

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Since the 21st century, with the rapid development of cloud computing, big data, internet of things, machine learning and other information technology fields, human beings have entered a new era of artificial intelligence. The subject of photogrammetry has also followed the tide of the new round of scientific and technological revolution and developed rapidly into the brand-new generalized photogrammetry and entered the era of integrated intelligent photogrammetry. Its carrier platform, instruments and data processing theories as well as application fields have also changed significantly. The multi-sensor and multi-level integrated stereo observation technologies from spaceborne, airborne and terrestrial platforms have been greatly developed. In this paper, the novel concept of generalized photogrammetry is first put forward, and its subject connotation, development characteristics and some key technologies and applications are discussed in details. Under the brand-new generalized photogrammetry framework, data acquisition presents the characteristics of multi-angle imaging, multi-modal collaboration, multi-time integration, multi-scale linkage, while data processing presents the trends of multi-feature coupling, multi-control constraints, multi architecture processing, and multi-disciplinary intersection. The all-round development and intelligent service of the general photogrammetry still need to make greater breakthroughs in the aspects of spaceborne, airborne and terrestrial multi perspective or multi-modal image processing, intelligent information extraction and monitoring, combined 3D modeling with point cloud and image, autonomous control of unmanned system, visual inspection of intelligent manufacturing system, etc. Finally, new theories and technologies from real-time or quasi real-time intelligent geometric processing of multi-source remote sensing datasets to information extraction and intelligent service need to be established, which will make a well foundation to meet the new eara of intelligent surveying and mapping.

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Accuracy assessment method of geoid based on GNSS-leveling and gravity field error characteristics

ZHANG Chuanyin, MA Xu, ZHANG Lei, DING Jian

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 12-17. DOI: 10.11947/j.AGCS.2021.20200211

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The lack of an effective accuracy assessment method of geoid is a key problem in the modernization of height datum and its application. In this paper, according to the error characteristics of GNSS-leveling height anomaly and gravity field in frequency domain, the technical requirements for the fusion of GNSS-leveling and gravity height anomaly are studied. Furthermore, a method of error expression and accuracy evaluation of geoid is proposed. Through the example test and analysis, the main conclusions are as follows: ①The accuracy of the fused height anomaly should be expressed by the error curve of height anomaly difference varying with the distance. ②For accuracy assessment of quasigeoid, two error indicators and two error curves are recommended, namely, the error of gravity height anomaly difference, the internal error of the fused height anomaly, the error curve of the fused height anomaly difference and the error curve of GNSS-levelling height anomaly difference. ③When the distance between two terrestrial points is close to or less than the average distance between GNSS leveling points, GNSS-levelling height anomaly plays a major role in the contribution of the fused height anomaly. ④The accuracy of the fused height anomaly in large scale is mainly controlled by gravity height anomaly.

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Android smartphone GNSS high-precision real-time dynamic positioning

GAO Chengfa, CHEN Bo, LIU Yongsheng

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 18-26. DOI: 10.11947/j.AGCS.2020.20200107

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Based on the quality and peculiarity of smartphone GNSS measurements, the existing methods of real-time dynamic PPP and RTK positioning are improved, and better smartphone GNSS positioning results obtained. Both positioning methods use a constant-acceleration dynamic single-frequency Kalman filter model with unfixed carrier phase integer ambiguity. Improvements include using smartphone carrier phase observation uncertainty for gross error processing, adopting the strategy of between-satellite single-difference to eliminate the influence of that the differences between smartphone pseudorange and carrier phase observations are not fixed, and modifying the value of smartphone measurements noise variance in the Kalman filtering process. Using one selected smartphone for experimental verification, the results show that its real-time dynamic PPP can reach a stable positioning state within 99 s, the horizontal and vertical RMS positioning error after stabilization are 1.21 and 2.79 m, respectively. RTK positioning can reach a stable state in 29 s, the horizontal and vertical RMS positioning error after stabilization are 0.73 and 0.78 m respectively. The experimental test results show that the current GNSS positioning module of smartphones could provide more accurate location services, and even has the potential for mapping operations in certain specific scenarios.

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Centimeter precise orbit determination for the Swarm satellites via undifferenced kinematic method

ZHANG Bingbing, NIU Jiqiang, WANG Zhengtao, XU Feng, TIAN Kunjun

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 27-36. DOI: 10.11947/j.AGCS.2021.20190165

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Using dual-frequency satellite-borne GPS observations from May 24 to May 30, 2015, the linear combination of Melbourne-Wübbena and ionosphere-free linear combination, based on the basis of precise point positioning technology, the batch least squares estimation method is used to precisely determine the Swarm undifferenced kinematic orbits with different orbital attitudes. The orbit accuracy is assessed using three methods, which include satellite-borne GPS phase observation residuals analysis, comparison with ESA reduced-dynamic orbits and external evaluation with SLR measurements. The results indicate: ①Swarm satellite-borne GPS phase observation residual RMS is in the range of 6~7 mm level. ②Comparisons with reduced-dynamic orbits computed by European Space Agency (ESA), radial, along-track and cross-track orbit difference RMS are in the range of 2~4 cm level. ③Comparisons with kinematic orbits computed by ESA, Radial, along-track and cross-track orbit difference RMS are in the range of 1~2 cm level. ④The external validation with satellite laser ranging (SLR) measurement shows RMS errors are in the range of 3~4 cm level. Therefore, it is feasible to use the undifferenced kinematic orbit determination method and the orbit determination strategy provided in this paper to carry out the precise orbit determination of swarm series satellites. The orbit determination accuracy is centimeter level.

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GPS time series inversion of the healing process of the middle segment of the Longmenshan fault after the 2008 Wenchuan earthquake

ZHAO Jing, ZHAN Wei, REN Jinwei, JIANG Zaisen, GU Tie, LIU Jie, NIU Anfu, YUAN Zhengyi

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 37-51. DOI: 10.11947/j.AGCS.2021.20200047

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The analysis of post-seismic fault healing process is important for deepening our understanding of seismogenic mechanisms, seismic faulting theory, and seismic cycles. In this study, by using time series of continuous GPS stations from 2010.30 to 2013.30 between the Wenchuan earthquake and the Lushan earthquake, the dynamic evolution of fault locking and slip deficit rate in the middle-southern segment of the Longmenshan fault zone were inverted and analyzed by the negative dislocation program of TDEFNODE, and the healing process of the middle segment and the background of major earthquakes of the southwest segment were discussed based on the inversion results. The results show that the locking fraction of the ruptured area around the epicenter of the Wenchuan earthquake gradually increased, which was basically in creeping state in 2010, and then in state of strongly locked in 2013. The locked area also gradually increased from the southwest of the Wenchuan earthquake epicenter to the epicenter, which indicates that this part of the fault has been healing rapidly. Most of the ruptured zone in the northeast of the epicenter is still in creeping state and the fault has not yet begun healing. The fault near and southwest of the epicenter of the Lushan earthquake has been in state of strongly locked, and the slip deficit rate of the completely locked area has been decreasing year by year, probably indicating that the healed region shares part of the compression effect of the Bayan Har block on the Sichuan Basin. The above results indicate that the healing process and activity characteristics of different segments of the Longmenshan ruptured fault are significantly different after earthquake. The southwest segment of the Longmenshan fault zone is in state of strongly locked and the background for a major earthquake has strengthened in the case of rapid accumulation of compressive elastic strain.

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A cesium atomic clock frequency anomaly detection algorithm based on clock prediction and its performance analyses

WU Yiwei

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 52-60. DOI: 10.11947/j.AGCS.2020.20190322

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A cesium atomic clock frequency anomaly detection algorithm based on clock prediction is proposed. The theory is based on the analytical expression of clock prediction uncertainty. Prediction errors are used as the test statistics and a binary hypothesis test is adopted. The test statistics all follow standard normal distributions. By means of setting a false alarm probability ( P _FA) value and acquiring the distribution function of normal distributions, the detection threshold can be determined. According to the detection threshold and the distribution function of the test statistics when anomalies appear, the expression of the detection probabilities ( P _D)s with different mean frequency jump levels ( Y _a)s is derived. Simulations and experiments validate the theoretical analyses. Based on the analyses, the methods of improving the detection probability are summarized.

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Modeling and assessment of GPS/BDS/Galileo triple-frequency precise point positioning

ZHOU Feng, XU Tianhe

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 61-70. DOI: 10.11947/j.AGCS.2021.20200146

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With careful consideration of time-varying characteristics of pseudorange and carrier phase hardware biases, more rigorous undifferenced and uncombined observation equations are derived, and the mathematical expressions of the two types of GNSS biases in uncombined mode are given. Based on this, this contribution studied independent parameterization methods of three commonly used triple-frequency precise point positioning (PPP) (i.e., ionosphere-free combination IF1213 and IF123 as well as uncombination UC123) function models in detail, and systematically analyzed the relationship among these models. Subsequently, the positioning performance in terms of positioning accuracy for GPS/BDS/Galileo triple-frequency PPP in static and kinematic modes was assessed. The experimental results showed that the positioning accuracy after convergence for static PPP was better than 1.0 and 1.5 cm; while that for kinematic PPP was better than 2.0 and 5.0 cm in horizontal and vertical components, respectively. Moreover, the positioning performance of triple-frequency and dual-frequency PPP was comparable.

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Seafloor classification based on combined multibeam bathymetry and backscatter using deep convolution neural network

YANG Fanlin, ZHU Zhengren, LI Jiabiao, FENG Chengkai, XING Zhe, WU Ziyin

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 71-84. DOI: 10.11947/j.AGCS.2021.20200065

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Seafloor classification is of great significance for the development and utilization of marine resources and marine scientific research. At present, multibeam detection is one of the effective methods to achieve large-scale seafloor classification. Seafloor classification is usually based on the angular response (AR) features and backscatter image features extracted by using multibeam backscatter. Because the feature source is relatively single and classifier structure is simple, the classification accuracy is often not high. This paper proposes a seafloor classification method based on convolutional neural networks (CNN). In addition to backscatter features, bathymetry features are also used to classify. The feature vectors are converted into waveform maps, and then input to the convolutional neural network for training and classification. The experiment compares different feature combination models and four conventional classifiers: BP network, support vector machine (SVM), k-nearest neighbor (KNN), and random forest (RF). The overall classification accuracy of the experiment reaches 94.86%, the kappa coefficient up to 0.93, and it takes 1 min 25 s. The accuracy has obvious advantages and the efficiency is relatively high. This method can effectively obtain the seafloor information in two different data types, give full play to the characteristics of convolutional neural network weight sharing, high efficiency, and achieve high-resolution seafloor classification. This paper provides a reference for the seafloor classification based on multibeam.

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Block adjustment of satellite imagery with line-of-sight vector rectification

WU Yang, ZHANG Yongsheng, LI Kai, YU Ying, LAI Guangling

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 85-96. DOI: 10.11947/j.AGCS.2021.20190093

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Considering the traditional bundle block adjustment of rational function model is highly constrained by small error of attitude and orbit, narrow field camera and good image intersection angle, a block adjustment method of satellite imagery based on line-of-sight vector rectification was presented. Firstly, the light ray of an image point is calculated by using the rational polynomial coefficients attached to the image, and then the pseudo orbit and attitude of sensor is restored when the point was acquired, then an error compensation model is constructed for the virtual orbit and attitude, and finally the model parameters and object coordinates of tie points are solved simultaneously by the least square method. As the compensation model is modelled from the reason of system errors, it can avoid approximation assumptions and constraints of traditional strategy. Several comparative experiments of simulation data, mapping satellite and non-mapping satellite data are designed. The results show that this algorithm can achieve higher accuracy than the traditional method under various severe conditions such as images with large attitude angle error, large field angle and weak intersection angle.

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Urban villages extraction from high-resolution remote sensing imagery based on landscape semantic metrics

ZHANG Tao, DING Lele, SHI Furong

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 97-104. DOI: 10.11947/j.AGCS.2021.20190463

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Urban villages (UVs), a special type of informal settlement in China. In this study, we proposed a method for UV extraction from high-resolution remote sensing imagery using landscape semantic metrics that can describe the complicated scene of UVs. In addition, an “uncertainty-feedback” strategy was proposed for large-scale practicable UV mapping. The experiment was performed in the urban areas of Guangzhou, with overall accuracy larger than 90%. The results reveal that the landscape semantic metrics have better ability to describe the essential characteristics of UVs compared to the traditional spectral and textural features. Besides, the “uncertainty-feedback” strategy can make full use of the classification reliability output by the machine learning, and produce more accurate UV mapping results with limited manual intervention. Thus, the proposed method can be effectively applied to large-scale UV extraction and mapping.

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A divided and stratified extraction method of high-resolution remote sensing information for cropland in hilly and mountainous areas based on deep learning

LIU Wei, WU Zhifeng, LUO Jiancheng, SUN Yingwei, WU Tianjun, ZHOU Nan, HU Xiaodong, WANG Lingyu, ZHOU Zhongfa

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 105-116. DOI: 10.11947/j.AGCS.2021.20190448

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Cropland is a scarce land resource in hilly and mountainous areas, which has the characteristics of complex topographic conditions and diverse planting structures, leading to the difficulty of rapid and accurate acquisition of cropland information in mountainous areas. Therefore, it is difficult to extract the cropland information in mountainous areas quickly and automatically based on the traditional remote sensing data and remote sensing monitoring methods. Aiming at this problem, this paper takes Xifeng County of Guizhou Province in the southwest mountainous area as the experimental area. According to the heterogeneity of geospatial space, this paper proposes the idea of cropland morphological information extraction by geographical division control and stratification extraction, and constructs a method for extracting cropland morphological information based on geographical division control and stratification extraction under the constraints of geomorphic unit. Firstly, according to the geomorphology-vegetation characteristics, the experimental area is divided into three geographical zones: flatland, hillside area and forest. Then, on the basis of each type of partition, the cropland is divided into different types according to the visual characteristics presented by the cropland, and different deep learning models are designed for hierarchical extraction of different types of cropland. The experimental results show that this method has a good suppression effect on the background noise of complex terrain in mountainous areas, and the extracted cropland plot information is more consistent with the actual distribution pattern of the actual cropland compared with the traditional method, which effectively reduces the rate of missing extraction and wrong extraction.

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Spatial relation reasoning and representation for image matching

LI Qin, YOU Xiong, LI Ke, WANG Weiqi

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 117-131. DOI: 10.11947/j.AGCS.2021.20190497

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The spatial relationship in the paper means the spatial adjacency relation between the objects in word space, and the paper proposes a novel image matching method based on analyzing the spatial adjacency relation between the object contained in the image pair. In the method, the feature extraction network is first trained based on comparison mechanism, and the well-trained model could produce the deep features for the objects, which could effectively match the consistent objects across images. Then the priori images are employed to deduce the spatial adjacency information between different objects, which is further represented by the spatial adjacency graph. Finally, the spatial relation matching between the image pair is conducted by calculating the spatial adjacency score based on the spatial adjacency graph. The experimental results demonstrate that the spatial adjacency scores of the non-matched image pairs generally equal to 0, and those of the matched pairs are generally greater than 0. As several objects are involved, the proposed spatial relation matching method could achieve high robustness, it outperforms other methods in the comparison experiments, and it could effectively complete the image matching task with high efficiency.

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An improved detecting information model of point annotation labelling in cartography

HU Fengwei, QIAO Junjun, CHEN Zhangjian, GONG Lifang, LI Aiqin

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 132-141. DOI: 10.11947/j.AGCS.2021.20200018

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As one of the media of map information transmission, point annotation is an indispensable part of map. In the past, most of the researches on point annotation labelling automatically only considered confliction problem. However, they ignored the spatial distribution and structural characteristics of background features, which are closely related to point annotation quality. Therefore, we firstly construct a quantitative description of correlation between point annotation quality and background features by starting with the annotation's clarity, explicity, distribution uniformity and attribution correctness rules. Then we proposed an improved detecting information model which takes into account the detecting information caused by feature topological relation, data structure, visual position and district. We experimented the proposed method and compared with the first generation model and Maplex on national 1∶1 million geographic information data, results showed that the model could effectively decrease detecting information in local area and avoid background features maximally, then improve point annotation's clarity and Readability.

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Research on features extraction and simplification from triangle mesh based on Morse theory

ZHANG Chunkang

Acta Geodaetica et Cartographica Sinica 2021, 50 (1): 142-142. DOI: 10.11947/j.AGCS.2021.20190491

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AOD adaptive prediction method based on GNSS PWV

ZHAO Qingzhi, SU Jing, YANG Pengfei, YAO Yibin

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1279-1289. DOI: 10.11947/j.AGCS.2021.20210052

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Aerosol optical depth (AOD) is a basic parameter of total aerosol content, which plays an important role in the study of atmospheric air quality. In order to explore the impact of different types of AOD on air quality, this paper proposes two adaptive AOD prediction methods based on GNSS PWV. The proposed method considers the temporal autocorrelation of AOD between adjacent epochs, and the model coefficients can be updated adaptively. One method is to model the 550 nm AOD directly based on GNSS PWV, which is called TAF (total AOD forecast) model. Another AOD modeling method takes into account the sensitivity of five different types of AOD to PWV, referred to it simply as FTAF(five type based AOD forecast) model. The model first establishes the functional relationship between PWV and five types of AOD. Secondly, according to the relationship between 550 nm AOD and five types of AOD, the weight of different types of AOD in 550 nm AOD was determined. Finally, PWV is used to predict five types of AOD, and the final 550 nm AOD is obtained by weighted average. 16 GNSS stations in Beijing, Tianjin, Hebei region are selected to verify the accuracy of the proposed model. The results show that the two 550 nm AOD prediction models have high accuracy, and the FTAF model is better than the TAF model. The AOD prediction model proposed in this paper can effectively apply the tropospheric parameters retrieved from GNSS to remote sensing monitoring of atmospheric environment, which provides a new idea for the study of atmospheric environmental quality.

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Characteristics of the short-term temporal variations of multi-constellation and multi-frequency GNSS receiver differential phase biases

MI Xiaolong, YUAN Yunbin, ZHANG Baocheng

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1290-1297. DOI: 10.11947/j.AGCS.2021.20200489

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With the completion of the BeiDou-3 Navigation Satellite System (BDS-3) and the development of Galileo and quasi-zenith satellite system (QZSS), more and more satellites can be used to retrieve the atmospheric ionosphere. Generally, the short-time variation of receiver differential code biases (DCB) is considered as an important error source for ionospheric inversion using Global Navigation Satellite System (GNSS). However, some studies have shown that the short-time variation of receiver differential phase biases (DPB) may also affect the accuracy and reliability of ionospheric inversion. This paper presents a method to estimate the receiver DPB based on the single-differenced (SD) model without changing the reference satellite, which can realize the continuous estimation of the receiver DPB. DPB of the overlapping frequency combination of BDS-3, Galileo, GPS and QZSS is analyzed based on data collected from several multi-frequency and multi-constellation receivers capable of tracking the new signals of the BDS-3. The results show that ① The intraday changes of DPB of BDS-3, Galileo, GPS and QZSS are obvious and have a strong correlation with temperature. ② There is a strong correlation between the DPB of the overlapping frequency combinations of BDS-3, Galileo, GPS and QZSS. ③ There is a significant correlation between changes in DPB based on the baseline of the same type of combination.

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Preliminary study on theory and method of ground-based GNSS-IR wind speed

WANG Xiaolei, HE Xiufeng, CHEN Shu, ZHANG Qin, SONG Minfeng

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1298-1307. DOI: 10.11947/j.AGCS.2021.20200586

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With the development of Global Navigation Satellite Systems (GNSS), the multipath effect that was once regarded as one error source has been proven can be used to monitor reflecting surface parameters such as water level, snow depth, vegetation water content, and soil moisture using a technology named GNSS-interferometry reflectomety (GNSS-IR). In order to expand monitoring objects and applications of GNSS-IR, this paper proposed the theory and method to retrieve wind speed using ground-based GNSS-IR. The theory includes the signal-to-noise ratio (SNR) multipath oscillation theory, the scattering model theory, and wave spectrum theory. This paper simulated the mathematical model between the SNR cutoff elevation angle and the wind speed, and used the wavelet analysis to extract SNR cutoff elevation angle and a unified method to unify reference of cutoff elevation angle. Data of HKQT station, located in Hong Kong, during the period of "Mangkhut" and "Hato" were used. The results showed that the variations of GPS L5 SNR cutoff elevation angles had a good corresponding relationship with the measured wind speeds, and the correlation coefficient reached 70%~85%. Also, the variations of cutoff elevation angles can describe the change of wind speed from low wind speed to high wind speed and there was a specific mathematical relationship between them. Finally, this paper discussed two difficulties to overcome in the GNSS-IR wind speed retrieval technology.

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Some numerical quadrature for singular integral of the altimetry gravity in the innermost area

ZONG Jingwen, LI Houpu, JI Bing, OUYANG Yongzhong

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1308-1319. DOI: 10.11947/j.AGCS.2021.20200564

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In order to simplify the calculation process and improve the calculation efficiency of inverse Stokes formula method and the inverse Vening-Meinesz formula method to invert the gravity anomaly, the numerical quadrature method is adopted. A new study on the investigation of singular integral of inverse Stokes formula and inverse Vening-Meinesz formula based on Simpson formula and Cotes formula is done and the formula of gravity anomaly in innermost area are derived systematically. The analysis based on the theoretical model of geoidal height and vertical deflections shows that the formula can directly use the geoid height and vertical deviation at the grid node to calculate the gravity anomaly which have simple form, high precision and high calculation efficiency.These research results can provide theoretical basis for high-precision satellite altimetry inversion of gravity anomalies.

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An empirical model for the vertical correction of precipitable water vapor considering the time-varying lapse rate for Mainland China

HUANG Liangke, MO Zhixiang, LIU Lilong, XIE Shaofeng

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1320-1330. DOI: 10.11947/j.AGCS.2021.20200530

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Atmospheric precipitable water vapor (PWV) plays a key role in the study of global climate change and numerical weather prediction. However, the vertical correction of PWV mainly relies on a simple empirical correction model at present, which limite the high precision fusion of multi-source water vapor products and the comparisons between different water vapor products in a way. In this paper, for the characteristics of highly undulating terrain and diverse climate in China, the PWV vertical correction models which considering the time-varying lapse rate according to the whole areas in Mainland China and geographical divisions, named as C-PWVC1 model and C-PWVC2 model respectively, are established using ERA5 reanalysis data provided by the European Center for Medium Range Weather Forecast (ECMWF) from 2012 to 2017. Taking the profiles of 86 radiosonde stations in China in 2017 as reference values, the ERA5 and MERRA-2 reanalysis gridded data are interpolated into radiosonde stations to evaluate the performance of the newly established models, respectively. The results show that the performance of C-PWVC1 and C-PWVC2 models in PWV vertical correction is comparable. Compared with the condition without vertical correction, the performances of the C-PWVC model for ERA5 and MERRA-2 are improved by 16% and 8%, respectively. Compared with the commonly used PWV vertical correction model, C-PWVC model has little improvement for ERA5, but 12% for MERRA-2. C-PWVC model shows significant advantages when the height difference between two kinds of PWVs is large, and the correction capability for MERRA-2 is greater than ERA5. Moreover, for the ERA5 with different spatial resolutions, C-PWVC model has better interpolation precision and stability when compared with the commonly used PWV vertical correction model, especially in southern and western China. Therefore, the C-PWVC model has a good performance in PWV vertical correction for Mainland China, which can provide important application for the comparison and fusion of multi-source water vapor products in China.

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Analysis of glacier changes in the Nyainqentanglha Mountain based on the combination of satellite gravity and optical remote sensing

ZHOU Miao, CHANG Xiaotao, ZHU Guangbin, QU Qingliang, LIU Wei

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1331-1337. DOI: 10.11947/j.AGCS.2021.20200463

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The GRACE and GRACE-FO gravity satellite data were used to retrieve the glacier quality changes in the Nyainqentanglha Mountains from August 2002 to April 2020, and combined with remote sensing technology to estimate the glacier area and reserves changes in the western Nyainqentanglha. The main conclusions are as follows:①The glaciers in the Nyainqentanglha Mountains showed an overall retreat trend during the study period, and there was an accelerated melting trend after 2013. ②The correlation between temperature changes and glacier melting curves can be found by comparing with summer temperature changes and precipitation anomalies better, the precipitation continued to decrease during the study period, indicating that the increase in temperature and the decrease in precipitation are the main reasons for the continuous decrease in the mass of glaciers in the Nyainqentanglha. ③The glacier area of the West Nyainqentanglha Mountains decreased by 72.30 km ² from 2003 to 2017, with an average annual decrease rate of 5.16 km ²/a. The glacier area retreats most obviously in the altitude range of 5600~5800 m. ④The coordinated application of satellite gravity and optical remote sensing technology can complement each other's advantages. It can not only estimate changes in glacier quality, but also detect changes in glacier area and elevation. At present, there are still some shortcomings in the joint application of the two technologies, which need to be further studied.

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Processing and preliminary accuracy validation of the GF-7 satellite laser altimetry data

LI Guoyuan, TANG Xinming, CHEN Jiyi, YAO Jiaqi, LIU Zhao, GAO Xiaoming, ZUO Zhiqiang, ZHOU Xiaoqing

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1338-1348. DOI: 10.11947/j.AGCS.2021.20210025

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GF-7 satellite is equipped with the first full waveform laser altimeter of China for earth observation, which is mainly used to obtain sparse elevation control points on the ground, and ultimately improve the stereo mapping accuracy of stereo images without ground control points. The laser altimetry standardization processing of GF-7 satellite is the key step of surveying and mapping application, and the generated laser altimetry standard products are the important premise of subsequent distribution and application. Based on the GF-7 satellite laser altimetry data, this paper studies the method of laser altimetry data processing, and preliminarily validates the geometric accuracy of laser altimetry standard products. Three regions are selected to validate the accuracy of GF-7 satellite laser altimetry standard products, which contain the domestic geometric calibration area, Huayin of Shaanxi province, North Rhine-Westphalia of Germany. The results show that the planimetric accuracy of laser altimetry standard products SLA03 in calibration area is (3.896±1.029)m and (3.286±0.337)m, and elevation accuracy is (0.018±0.099)m,(-0.017±0.096)m in respectively for the two-beam lasers. Moreover, the elevation control point quality control parameter ECP_Flag can effectively identify the laser points that can be used for elevation control. The overall accuracy of Shaanxi Huayin area is (-0.113±2.519)m and (0.191±1.071)m, respectively for the two beams. The elevation accuracy of laser points marked with ECP_Flag=1 is (0.111±0.152)m and (-0.064±0.115)m. The overall accuracy of Norwich in Germany is (-0.897±5.485)m and (-0.202 ±6.207)m, and the elevation accuracy of laser points marked with ECP_Flag=1 is (-0.304±0.190)m and (-0.279±0.220)m, respectively for the two beams. At present, the laser altimetry standard products of GF-7 satellite have been daily produced in the Land Satellite Application Center of the Ministry of Natural Resources.

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Change detection of remote sensing images by combining neighborhood information and structural features

YE Yuanxin, SUN Miaomiao, WANG Mengmeng, TAN Xin

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1349-1357. DOI: 10.11947/j.AGCS.2021.20200130

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In order to improve the accuracy of pixel-level change detection methods, this paper proposes a novel change detection method for remote sensing images by combining neighborhood information (including the neighborhood correlation image (NCI) and matching errors) and structural features. First, a technique of neighborhood correlation analysis is used to obtain the NCI which represents the context information, and the cross-correlation of neighborhood pixels is used to obtain matching errors by a template matching scheme. Then, structure features of images are extracted using orientated gradient information, which are robust to spectral differences between images. Subsequently, the initial change detection results is obtained by using the NCI, the matching errors, and structural features as the classification attributes of a decision tree. Finally, the Markov Random Field (MRF) is used to optimize the results, yielding the final binary map. The proposed method has been evaluated with two sets of bi-temporal remote sensing images from different sensors. Experimental results demonstrate that this method effectively improves the accuracy of change detection compared with the change vector analysis method, the single neighborhood information method and the method combining neighborhood information and texture features.

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Graph convolutional network method for small sample classification of hyperspectral images

ZUO Xibing, LIU Bing, YU Xuchu, ZHANG Pengqiang, GAO Kuiliang, ZHU Enze

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1358-1369. DOI: 10.11947/j.AGCS.2021.20200155

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Existing based on convolutional neural network classification method of hyperspectral images usually rules of the square area of image convolution, not widely adapt to different terrain local area distribution and geometry appearance of the image, therefore, under the condition of small sample classification performance is poorer, and figure convolution can network topology information on the map represent irregular image area of the convolution. Therefore, a hyperspectral image classification method based on graph convolution network is proposed. In this method, the spatial spectral information of the image is considered in the process of constructing the graph, and the feature information of the neighbor node is aggregated by the graph convolution network. Experimental results on three data sets, Pavia university, Indian Pines and Salinas, show that this method can achieve a high classification accuracy with a small number of training samples.

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Water extraction model of multispectral optical remote sensing image

DENG Kaiyuan, REN Chao

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1370-1379. DOI: 10.11947/j.AGCS.2021.20200482

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Accurate monitoring of surface water is an important basic application of remote sensing. The principle of optical remote sensing water extraction is based on different ground features having different spectral reflection characteristics. Some ground features (ice, snow, shadows, clouds) have similar reflection characteristics to water bodies, which leads to the failure of extraction and classification. Aiming at the problem of misclassification and omission of traditional water body index in water body extraction, this paper proposes a normalized difference multi-band water index model. This paper uses two experiments to test the stability of the new index. The area of experiment 1 is the Linzhi area of Tibet. The data source is Landsat 8 and Sentinel 2 satellite images in the same time phase. The experimental results verify the ability of the new index to suppress snow and ice. The Kappa coefficient of the new index is 0.86, the overall accuracy is 0.93, and the misclassification error is 0.03, the omission error is 0.12, the drawing accuracy is 0.97, and the producer accuracy is 0.88, which are better than the existing index. The data source of experiment 2 was GF-1, and Hong Kong Disneyland was used as the experimental area. Experiment 3 extracted water bodies in multiple regions and verified the stability of the water body index in this paper. Water extraction was performed in an environment with a small amount of clouds, which proved that the new index can suppress clouds and their shadows. This paper uses multi-source optical remote sensing image to verify the feasibility of the new index. Without additional auxiliary data, the influence of snow, cloud and shadow can be eliminated, and the water can be more effectively and automatically extracted, which can be extended to coastal resource research, glacier change, inland lake change and other fields.

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Non-subsampled shearlet transform remote sensing image fusion combined with parameter-adaptive PCNN

CHENG Feifei, FU Zhitao, HUANG Liang, CHEN Pengdi, HUANG Kun

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1380-1389. DOI: 10.11947/j.AGCS.2021.20200589

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In order to solve the problem that the parameters of pulse-coupled neural network can't be adjusted adaptively in pan-sharpening image fusion, a non-subsampled shearlet transform remote sensing image fusion method based on the combination of parametric-adaptive pulse coupled neural network model and energy-attributing fusion strategy is proposed. First, the high and low frequency coefficients are obtained by extracting the Y luminance component of the multispectral image YUV color space transform and transforming it with the panchromatic image. Then, aiming at the low-frequency sub-band coefficients are fused by the EA method, the high-frequency sub-band coefficients are obtained by the PA-PCNN model to determine the optimal PCNN model, and then the high-frequency sub-band coefficients are fused; finally, the fusion image is obtained by inverse transformation of NSST and YUV. In this paper, six objective quality indexes, such as spatial frequency, relative dimensionless global error, ERGAS, correlation coefficient, visual information fidelity for fusion, gradient-based fusion performance and structural similarity index, are selected to evaluate the spectral and spatial detail information of the fused images, compared with SE, DGIF, COF and PA-PCNN fusion methods, the proposed method is validated by using multiple sets of high-and low-resolution panchromatic and multispectral remote sensing images, the results show that this method is generally superior to the traditional fusion method of panchromatic and multispectral remote sensing images in objective evaluation and visual perception.

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A fast matching method of SAR and optical images using angular weighted orientated gradients

FAN Zhongli, ZHANG Li, WANG Qingdong, LIU Siting, YE Yuanxin

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1390-1403. DOI: 10.11947/j.AGCS.2021.20200587

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To solve the problem of matching difficulty caused by the significant nonlinear grayscale differences between SAR and optical images, this paper proposes a fast matching algorithm based on image structural properties named SOFM(SAR-to-optical fast matching algorithm).The traditional methods based on image grayscale are generally difficult to resist the nonlinear grayscale differences between SAR and optical images, but the geometric constructs and shape features can exist stably among different types of images, so in our the proposed method both the magnitude and orientation information of image gradient are used to build a geometric structural feature descriptor named AWOG(angular weighted orientated gradients), then based on the template matching strategy, the sum of squared difference of the descriptors is used to define the similarity metric for matching and then the image matching function expressed in the frequency domain is given. A complete set of image matching process is established based on SOFM, and has been validated using multiple pairs of SAR and optical images, the results show that the proposed method can effectively resist the nonlinear grayscale differences between SAR and optical images, and outperforms the traditional classical image grayscale-based methods and existing image structural-based methods in matching performance and precision.

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Latent semantic understanding of geographical environment spatio-temporal data based on topic model

ZHU Jie, ZHANG Hongjun, LIAO Xianglin, TIAN Jiangpeng

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1404-1415. DOI: 10.11947/j.AGCS.2021.20200380

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Text is an important data mode of battlefield information. Mining spatial-temporal semantic information of geographical environment from battlefield text is an important method for machine to understand battlefield environment, which is helpful to expand battlefield environment spatial cognition and understanding. A method based on topic model is designed to reflect the semantic relationship between geographical spatio-temporal factors and event topics, and different topic classification with its distribution of word features are formed by the method of information extraction to mine the relevant information of topic elements; the joint distribution model of event topic and geographical spatio-temporal semantic features is established to automatically discover the correlation among time, space and event topics, thus generating the latent geographical spatio-temporal semantic topics; through the experimental verification and the application practice, we believe that the law of spatio-temporal distribution under different topics can be seek by using correlation between the event topics and location information with spatial analysis method, so as to provide the basis for the location prediction of new events and the countermeasures of seeking advantages and avoiding disadvantages, and expand the traditional thematic analysis of geographical events.

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Study on optimization problem of Wi-Fi/PDR indoor hybrid positioning on smartphone

BI Jingxue

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1416-1416. DOI: 10.11947/j.AGCS.2021.20200408

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Application of radial basis function in gravity field modeling and data fusion

MA Zhiwei

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1417-1417. DOI: 10.11947/j.AGCS.2021.20200409

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Secular variation of gravity anomalies within the Tibetan Plateau derived from GRACE data

LIU Jie

Acta Geodaetica et Cartographica Sinica 2021, 50 (10): 1418-1418. DOI: 10.11947/j.AGCS.2021.20200410

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