Table of Content

20 December 2023, Volume 52 Issue 12

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Geodesy and Navigation

Inversion of current locking degree and slip deficit of fault zone in northern Qaidam Basin based on GPS data

LIU Yang, QIU Yuxuan, WANG Junyi, LI Hanghao, ZHANG Yu, WEN Yangmao, XU Caijun

2023, 52(12):  2015-2027.  doi:10.11947/j.AGCS.2023.20220714

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The fault zone in northern Qaidam Basin is an essential geological boundary of the northeastern margin of the Qinghai-Tibet Plateau, and its geometry is complex. At present, there are few studies on the current locking degree and slip deficit of regional integral faults. In this paper, a dense regional GPS data is collected and fused, and a geometric model including the Saishiteng-Lüliangshan fault section, Xitieshan-Amunikeshan-Maoniushan fault section, the northern Elashan fault section, the southern Elashan fault section, and the Akesai-Delingha block, the Qaidam block and the Elashan block is established. The negative dislocation model is used to invert the current locking degree and slip deficit of the fault zone in northern Qaidam Basin. The results show that the locking degree and slip deficit of the Saishiteng-Lüliangshan fault section gradually decrease from the central (the average locking coefficient within 15 km depth is about 0.7) to both ends. The locking degree and slip deficit of Xitieshan-Amunikeshan-Maoniushan fault section increase gradually from northwest to southeast. The average locking coefficient within 15 km depth in the central and southeast parts is about 0.99, and the average slip deficits are about 3.34 mm/a and 3.80 mm/a, respectively. The locking depth of the northern most part of the northern Elashan fault section is shallow, the locking depth of the central and southern parts is deep (about 19 km), and the slip deficit of central part is enormous. The locking depth at both ends of the southern Elashan fault section is up to 20 km (the average locking coefficients within 15 km depth are about 0.9 and 0.99, respectively), the locking depth of central part is shallow, and the slip deficit of northern part is enormous. Based on the comprehensive inversion results and the analysis of historical seismic distribution, the seismic risk of central and southeastern parts of Xitieshan-Amunikeshan-Maoniushan fault section, the central part of northern Elashan fault section, and the northern part of southern Elashan fault section may be high, which should be paid attention to.

In-layer equivalent two-segment line substitution method for sound velocity profile considering area difference

XIAO Yuanbi, PENG Rencan, DONG Jian, MA Zhengwei, LIU Ju

2023, 52(12):  2028-2038.  doi:10.11947/j.AGCS.2023.20210342

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Sound velocity profile is an important parameter in multi-beam sounding system. In this paper, an adaptive layering optimization method of sound velocity profile considering the area difference between layers is proposed, which is the in-layer equivalent two-segment line substitution method. Based on the method of maximum acoustic velocity offset, a calculation model of the equivalent two-segment line in the optimal layer is constructed through model analysis and derivation. The algorithm is validated by using measured multi-beam sounding data. The results show that this method can control the percentage of standard deviation of water depth between the whole water depth data and the interlayer water depth data within 1%. Because the method can accurately calculate the sound velocity of complex multilayer seawater, it has important engineering application value in high precision measurement of special seabed topography with large fluctuation.

Applying least square collocation method to predict seafloor topography in the unknown sea area

FAN Diao, LI Shanshan, FENG Jinkai, HUANG Yan, FAN Haopeng, ZHANG Jinhui, LI Xinxing

2023, 52(12):  2039-2053.  doi:10.11947/j.AGCS.2023.20220644

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The least square collocation (LSC) method is introduced to address the problem in seafloor topography (ST) prediction without shipborne bathymetry data. That is, cross covariance function between shipborne bathymetry and gravity in the known sea area can be applied to the unknown sea area with no shipborne bathymetry data if the gravity anomaly in the two areas is similar. The ST model (BAT_LSC_1) is constructed based on LSC in the western Pacific Ocean where shipborne bathymetry and gravity anomaly are known. The evaluation results showed that the checking accuracy of BAT_LSC_1 is equivalent to that of the ST model constructed by admittance function, and the checking relative accuracy is better than 4%. Then, sea surface gravity anomaly in the sea area is grayed out and the unknown area where shipborne bathymetry is missing is identified by gravity anomaly image coarse matching and fine matching. The cross-covariance function in the known area is applied to the unknown area, and the LSC is also used to predict the ST model (BAT_LSC_2). The results show that BAT_LSC_2 is better than ETOPO1 model and the ST model constructed by admittance function, which verifies the feasibility and applicability of the proposed method.

Estimation and analysis of geocenter motion using BDS-3 data

GUO Shiwei, SHI Chuang, FAN Lei, WEI Na, ZHANG Tao, FANG Xinqi, ZHOU Linghao

2023, 52(12):  2054-2065.  doi:10.11947/j.AGCS.2023.20220518

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Accurate estimating of geocenter motion is an essential prerequisite for the establishment of geocenter-based terrestrial reference frame at millimeter level. With the commissioning of BDS-3 system and the increasing of BDS-3 tracking stations, determining geocenter motion by BDS-3 is of great scientific value to building the independent terrestrial reference frame of China. This paper determines geocenter motion based on the BDS-3 observations, investigating the spurious periodic signals in geocenter motion time series and the correlation between geocenter motion and orbital parameters. The results indicate that the discrepancy of geocenter motion between BDS-3 estimates and IGS combinations is at the level of 7 mm for the X and Y components, and is about 21.6 mm for the Z component. The formal errors of geocenter motion parameters are 2.7, 2.8 and 5.3 mm for the X, Y and Z components, respectively. An evident 7 d signal with the amplitude of about 3 mm is detected over the geocenter X and Y components, which is related to the BDS-3 orbit repeat time. Anomalous odd harmoncis of BDS draconitic year are found in the geocenter Z component. Besides, the magnitude of formal errors of the geocenter Z component is closely related to the geometry of satellite orbit planes, showing the variability with periods at 1/2, 1/4 and 1/6 of the draconitic year. When the absolute values of the Sun elevation angle of all the orbital planes are close, the correlation between the geocenter Z component and orbit parameters gets obviously increased, reaching up to 0.8.

Comparative analysis of Green's functions and Slepian basis functions for GNSS inversion of terrestrial water

CHEN Chao, ZOU Rong, CAO Jiaming, LI Yu, LIANG Hong, FANG Zhiwei

2023, 52(12):  2066-2077.  doi:10.11947/j.AGCS.2023.20220624

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Terrestrial water storage is an important part of water resources. Changes in terrestrial water storage are related to the development of human society. Atmospheric warming has a profound impact on the distribution of global terrestrial water storage, and even worsens the relationship between regional water supply and demand. With the construction of continuous GNSS station network in China, GNSS has become a new type of geodetic method for monitoring terrestrial water storage changes. At present, the methods for terrestrial water inversion using continuous GNSS stations are mainly divided into Green's function and Slepian basis function inversion methods, but there are few reports on the differences and applicable scenarios of those two methods. Starting from the basic principles of the two methods, this paper uses simulated data and measured GNSS data to perform inversion based on the Green's function and the Slepian basis function, respectively. Results show that: ① Based on the simulation data, the number and spatial distribution of GNSS stations are different, and the Green's function inversion results are more affected than the Slepian basis function inversion results. The overall accuracy of Green's function inversion results is better, and the Slepian basis function method is greatly affected by the maximum truncation order. ② Based on the real “land-state network” and the vertical time series data of GNSS continuous observation stations of the Meteorological Bureau, the correlation between the two methods to retrieve the equivalent water height is 0.98, and the amplitude of the Slepian basis function inversion result is 25% larger than that of the Green function inversion result on average. ③ The results of GNSS inversion and the terrestrial water phase inferred by GRACE and GLDAS are all greater than 0.65, and the monthly precipitation data are in good agreement. The peak of the equivalent water height sequence retrieved by GNSS lags behind the maximum rainfall by 1~2 months. Considered the reality in most area of China, the density GNSS stations is not enough for the application for Green's method in TWS inversion, so the Slepian method is the good choice.

Retrieving water volume changes of shallow inland lakes with dense time-series Sentinel-2 and ICESat-2 data

WU Haoru, LI Junli, BAO Anming, ZHANG Jiudan, MA Yinglian

2023, 52(12):  2078-2088.  doi:10.11947/j.AGCS.2023.20220602

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The inland endorheic lakes in arid regions have shallow-flat basins and complex shorelines, which makes it hard to retrieve high-accuracy water volume changes through traditional 'water level-area curve’ methods. In this paper, a method is proposed to retrieve basin topography and reconstruct time-series water volumes for shallow-flat inland lakes based on multi-temporal ICESat-2 and Sentinel-2 data. Firstly, all the multi-temporal ICESat-2 photons inside the non-water areas of the lake basin were selected and their elevations were retrieved. Secondly, the multi-temporal lake boundaries were delineated from the Sentinel-2 images, and their elevations were interpolated by these ICESat-2 points due to the fact that a lake water boundary is equivalent to a contour line. Finally, the lake basin topography was retrieved based on these densified ICESat-2 photon altimetric points, and the time-series lake volumes were reconstructed according to the basin DEM and time-series lake area extents. The method was tested by the Taitema Lake which is the terminal lake of the Tarim river, and about 132 scenes of Sentinel-2 satellite remote sensing images and 28 phases of ICESat-2 laser beam data were used to reconstructed water volume changes from 2016 to 2022. The result showed that the RMSE error of the lake DEM is 0.103 m, which can provide a way of time series reconstruction of shallow-flat lakes in un-gauged basins.

Analysis of terrestrial water storage variations in Chinese mainland based on HUST-Grace2020 model

MA Wenjing, ZHOU Hao, HE Peipei, ZHENG Lijun, LUO Zhicai

2023, 52(12):  2089-2102.  doi:10.11947/j.AGCS.2023.20210693

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The characteristics of Chinese water resources are presented less per capita and unbalanced distribution. Therefore, it's significant to manage and regulate water based on water storage variation in Chinese mainland. Based on the latest HUST-Grace2020 model released by Huazhong University of Science and Technology, we analyze the terrestrial water storage (TWS) variations of Chinese mainland during January 2003 to July 2016. In addition, we calculate the TWS variations of the newest COST-G model released by the University of Berne in Switzerland, the CSR RL06 model released by Center of Space Research (CSR), the ITSG-Grace2018 model released by Institute of Geodesy at Graz University of Technology (ITSG) and the Tongji-Grace2018 model released by Tongji University during the same time frame. The results are summarized as follows: ①There is a good agreement between the results derived from HUST-Grace2020 and COST-G, ITSG-Grace2018, Tongji-Grace2018 in terms of the TWSs over 15 river basins in Chinese mainland. ②The water storage of Brahmaputra River and Lancang-Nu Rivers which located at the border of southwestern China varies most significantly. The annual amplitudes of these two regions are 13.75 and 9.37 cm, respectively. The positive TWS yearly trends are observed Yangtze River, Zhujiang River and the southeastern coast, which are 0.54, 0.78, 0.70 cm/a, respectively. In contrast, the TWSs of Huaihe River, Haihe River and Brahmaputra River show decreasing trend, with rates of -0.47, -0.88 and -1.30 cm/a, respectively. ③The TWS variations over Chinese mainland show obvious seasonal characteristics. Generally, the water storages are abundant in summer and autumn, but scarce in winter and spring. ④Based on the analysis of TWS in typical basins, extreme drought events of the Yangtze River Basin occurred in 2006 and 2011, and flood events occurred in 2010 and 2016. In the Yellow River, extreme drought events occurred in 2003 and flood events occurred in 2013.

Photogrammetry and Remote Sensing

Deep learning method for large scene DSM generation of GF-7 imagery

HE Sheng, ZHANG Jiankai, CHEN Feng, LI Shenhong, JIANG Wanshou

2023, 52(12):  2103-2114.  doi:10.11947/j.AGCS.2023.20220567

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Stereo matching is an important step to generate DSM from satellite imageries. Recently, studies have shown that deep learning-based methods have better performance. However, due to the fixed and limited disparity range predicted by models and the lack of training data, deep learning is rarely directly applied to the stereo matching of satellite images in large scenes. In this paper, a hierarchical dynamic matching strategy is proposed to dynamically determine the region of image blocks of the current level according to the matching results of the previous level, so that the disparity between the left and right epipolar image blocks is relatively small, which is conducive to the prediction of deep learning models. Besides, a scheme for the production of samples is introduced, and a GF-7 dataset is constructed by using manually edited DSM or LiDAR point clouds to obtain ground truth disparity values. In the experiment, this dataset, together with an existing dataset, is used to train Stereo-Net and DSM-Net, and based on the hierarchical matching strategy, the generation of high-quality DSM from Gaofen-7 imagery combined with deep learning technology is achieved for the first time. Experiments in imageries from three cities show that the average endpoint error is about 1 pixel, and the fraction of erroneous pixels is less than 3.8%. The quality of the generated DSMs is better than that of the traditional method.

Unsupervised domain adaptation alignment method for cross-domain semantic segmentation of remote sensing images

SHEN Ziyang, NI Huan, GUAN Haiyan

2023, 52(12):  2115-2126.  doi:10.11947/j.AGCS.2023.20220483

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Deep learning models rely on a large number of homogenous labeled samples, i.e., limiting the training and testing data to obey the same data distribution. However, when facing large-scale and diverse remote sensing data, it is difficult to guarantee the requirement of homogeneous distribution among data, and the segmentation accuracy of deep learning models decreases significantly. To address this problem, this paper proposes an unsupervised domain adaptation (UDA) method for semantic segmentation of remote sensing images. When the distributions of training data (source domain) and testing data (target domain) are different, the proposed method improves the accuracy of semantic segmentation in the target domain by training deep learning models using only source-domain labels. The method introduces optimal transport theory and global alignment in image, feature and output spaces to mitigate the domain shift between the source and target domains. The experiments employ the Potsdam and Vaihingen datasets provided by the International Society for Photogrammetry and Remote Sensing (ISPRS) to validate the performance. The results show that the method in this paper achieves higher accuracy compared with existing methods. Based on the ablation study, the effectiveness of the optimal transport theory is demonstrated in the UDA framework for semantic segmentation driven by deep learning.

Joint estimation method of time-series InSAR deformation and environmental physical parameters for soft clay area over Dongting lake

ZHU Jun, ZHU Lingjie, XING Xuemin, ZHANG Rui, BAO Liang, ZHANG Tengfei, BAO Haodan

2023, 52(12):  2127-2140.  doi:10.11947/j.AGCS.2023.20220287

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The Dongting lake eco-economic zone is an important national development zone and an important part of national strategic development, but the soils of the Dongting lake region are predominantly soft clay, and long-term continuous safety and stability monitoring of the densely distributed infrastructure in the region is necessary. The current monitoring using PSInSAR is generally based on a linear rate model, but infrastructure deformation in the Dongting lake soft soil region has obvious non-linear characteristics over time and is also influenced by environmental physical factors such as thermal expansion and precipitation. To address this problem, this paper proposes a method for estimating deformation and environmental physical parameters simultaneously using PSInSAR. The method uses the hyperbolic model and the a priori model of thermal expansion effect for the prediction of the deformation of soft soil in Dongting lake instead of the linear rate model in the original method, incorporates both thermal expansion parameters and environmental precipitation parameters, and solves the deformation and environmental physical parameters together in the PSInSAR solution process. The paper also proposes a solution strategy for LAMDBA-SVD-based time-dimensional parameter estimation and Jacobi iteration-based spatial-dimensional parameter estimation. Totally 24 TerraSAR-X radar satellite remote sensing image covering the Dongting lake area in Yueyang city, China, were selected for experiment, and the thermal expansion parameter of the typical infrastructures in this area was obtained and the time-series deformation from November 2011 to April 2013 was generated by the proposed method. The residual phase of the model is used to evaluate the modeling accuracy of the new algorithm. The results show that the residual phase of the improved model is 0.4 rad, with a 36.5% increasement compared to the traditional linear rate model.

Polarimetric SAR target decomposition method based on independent polarization orientation angle integration

LI Nengcai, HU Canbin, WANG Wei, QUAN Sinong, XIANG Deliang

2023, 52(12):  2141-2153.  doi:10.11947/j.AGCS.2023.20220552

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The polarimetric decomposition method based on physical models has become one of the mainstream methods for PolSAR incoherent target decomposition due to its clear physical significance and ease of implementation. However, such methods often have the problem of volume scattering overestimation and scattering mechanism ambiguity in urban building areas with large orientation angle. Therefore, a six-component polarimetric target decomposition method based on independent polarization orientation angle integration is proposed in this paper. Instead of using the polarization orientation angle compensation strategy, three independent polarization orientation angles were introduced to describe the double-bounce scattering models, dipole scattering models and quarter-wave scattering models, and the generalized dipole scattering model, the generalized quarter-wave scattering model and the improved double-bounce scattering model were obtained. The surface scattering model and double-bounce scattering model are simplified, and the scattering components are decoupled effectively while the unknown variables are reduced. At the same time, the six scattering models fully explain the nine elements and make better use of the information of the polarization coherence matrix. The rotation invariance of the main diagonal elements of the polarization coherence matrix is analyzed, and the polarization orientation angles is avoided to participate in the calculation by using this property. At the same time, the calculation anomaly caused by division is avoided during the decomposition process, and the stability of the polarization decomposition results is ensured. GF-3 and UAV SAR full-polarization data were used for the experiment, the experiment result shows that thedecomposition method can effectively solve the overestimation of volume scattering of urban buildings, especially in large orientationangle building areas, while ensuring the correct extraction of dominant scattering power from forest vegetation and ocean areas, and the overall decomposition results are more consistent with the actual scattering process of the land covers.

Remote sensing image fusion combining energy attribute and guided filter

SONG Jiawen, ZHU Daming, FU Zhitao, CHEN Sijing

2023, 52(12):  2154-2163.  doi:10.11947/j.AGCS.2023.20220470

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A pan-sharpening method based on energy attribute (EA) and guided filter is presented to solve the problem of spatial and spectral information distortion in multispectral and panchromatic image fusion. First, the intensity-hue-saturation (IHS) transformation is applied to the multispectral image to extract the intensity component. The high and low-frequency components are obtained from the intensity component and the panchromatic image using the mean filter and difference operator. The guided filter enhances the high-frequency information. The decision map is obtained using the rule of maximum pixel value, and the high-frequency image is fused with the decision map by the rule of the weighted average pixel. The EA strategy fuses low-frequency components. The fusion image is obtained by combining the new low-frequency component with the high-frequency component instead of the original intensity component and inverting the IHS transformation. In this paper, many experiments are carried out on SPOT-6, WorldView-2, and Pléiades NEO remote sensing images, and the results are compared quantitatively and qualitatively with four advanced methods. The spectral angle mapping, relative dimensionless global error in synthesis, relative average spectral error, root mean square error, universal image quality index, and peak signal-to-noise ratio values of the proposed methods were improved by 77.13%, 10.78%, 9.57%, 12.20%, 1.35%, and 0.39% compared with the sub-optimal values, respectively. The experimental results show that this method can fully incorporate the spatial information of panchromatic images while maintaining the spectral information of multispectral images and achieve optimal fusion results in visual perception, quantitative indicators, and time efficiency.

An accurate breakline-aware filtering method for airborne laser scanning point clouds

YANG Yuyan, ZANG Yufu, XIAO Xiongwu, GUAN Haiyan, PENG Daifeng

2023, 52(12):  2164-2177.  doi:10.11947/j.AGCS.2023.20220616

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The existing filtering methods often mistakenly filter a large number of ground points in areas with complex terrain and abrupt elevation, which reduces the accuracy of filtering results and seriously affects the subsequent application. For this reason, this paper proposes an efficient filtering method for sampling lines by fusing the breakline constraint model. Firstly, a constraint energy term is created based on the sum of point curvature and distance in the neighborhood, and the Snake energy model is improved, and features of breaklines are extracted by minimizing the energy function. Then, the point cloud sequence is obtained from the survey area to form a sampling line at equal intervals, and the regular triangle model is constructed, the flatness of point clouds is calculated, and the points on each sampling line are filtered by fusing the breakline constraint. Finally, according to ground points on the sampling line, the improved least square method is used to fit global surface, and the non ground points in the region are filtered according to their actual elevation values. In order to verify the effectiveness of this method, this paper uses five airborne laser point cloud data from different regional scenes for experimental analysis. The results show that the proposed method is better than the reference method in terms of efficiency and accuracy, and the average filtering accuracy is as high as 96.58%, especially in the terrain fault area.

Cartography and Geoinformation

Revisiting narrative maps: fundamental theoretical issues and a research agenda

SU Shiliang, WANG Lingqi, DU Qingyun, ZHANG Jiangyue, KANG Mengjun, WENG Min

2023, 52(12):  2178-2196.  doi:10.11947/j.AGCS.2023.20220324

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Narrative maps have become a booming branch of contemporary cartography. However, there lacks of convincing conceptualization of basic issues such as “what is a narrative map” and “whether or not a map can narrate”, which not only raises a challenge to the theoretical legitimacy but also leads to an open question regarding “how do narrative maps tell stories”. Aiming to address these gaps, this paper first demonstrated the theoretical rationality of narrative maps, through unearthing the skeleton of narratology and cartography and their continuous interactions; from the perspective of semiotics, then, conceptualized narrative maps and distinguished their essential characteristics after demonstrating the narrative capability of map 'texts’; following, unraveled the narrative systems and proposed a working model for the representation mechanism of narrative maps using a (post-) structuralist approach; and finally made prospects on the key issues of narrative maps in the near future. This paper is believed to open the window for theoretical innovations of contemporary cartography.

A canonical time warping algorithm for building shape similarity measurement

LI Jingzhong, MAO Kainan

2023, 52(12):  2197-2208.  doi:10.11947/j.AGCS.2023.20220539

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This paper proposes a shape similarity measurement model based on canonical time warping (CTW) algorithm. The model combines canonical correlation analysis (CCA) and dynamic time warping (DTW) to align building coordinate sequences with different number of vertices, which can comprehensively evaluate the shape similarity between different shape contours. This method directly uses vector coordinates as model input without constructing complex shape coding and considers the original contour features of building shapes, which can be applied efficiently to shape retrieval and other scenarios. Experiments show that CTW algorithm is invariant to translation, rotation, scaling and mirroring when used to measure the similarity of geometric objects, and can effectively measure the shape similarity between building shapes. The results are consistent with human spatial visual cognition.

Automatic vector polyline simplification based on region proposal network

JIANG Baode, XU Shaofen, WU Yong, WANG Miao

2023, 52(12):  2209-2222.  doi:10.11947/j.AGCS.2023.20220363

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To address the problem of existing vector polyline simplification algorithms lacking intelligence, an automatic vector polyline simplification algorithm based on regional proposal network is proposed. Firstly, a depth-separable convolutional neural network is used to realize the convolutional feature extraction of raster polylines. Then, the generation method of region proposals in the region proposal network is improved by combining the coordinate information of the polylines, which is in order to establish the correspondence between the proposal region and the possible bending combinations. Finally, after unifying the size of the bending feature map, the automatic detection of bending units is completed by binary classification according to the convolutional features corresponding to the region proposals, and polyline simplification is achieved by deleting the bending units. In this paper, the model is trained and tested on the coastline dataset, and the effectiveness of the model is verified by comparison experiments with different rasterization parameters, different backbone networks, cross-scale simplification, and different types of line simplification. Experimental results show that this algorithm can intelligently learn the simplification knowledge from the existing polyline simplification cases, and make full use of the vector and raster features of polylines to identify and locate the bending units, and finally complete the automatic simplification of vector polylines while the network can be trained end-to-end.

Summary of PhD Thesis

Full-link forest echo simulation of domestic spaceborne LiDAR and study on inversion of forest structure parameters

CAI Longtao

2023, 52(12):  2223-2223.  doi:10.11947/j.AGCS.2023.20220517

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Terrestrial time-varying microgravity data processing and field source model interpretation

YANG Jinling

2023, 52(12):  2224-2224.  doi:10.11947/j.AGCS.2023.20220524

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Research on location prediction and recommendation methods of mobile objects based on spatio-temporal context

LIU Chunyang

2023, 52(12):  2225-2225.  doi:10.11947/j.AGCS.2023.20220529

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Method of viaduct expressway construction suitability evaluation in short wall goaf collapse area and its application

GUO Song

2023, 52(12):  2226-2226.  doi:10.11947/j.AGCS.2023.20220530

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Research on monitoring of lake water level and river discharge by wide swath altimetry

DU Bin

2023, 52(12):  2227-2227.  doi:10.11947/j.AGCS.2023.20220544

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Research on inversion method and application of wave and tide parameters based on GNSS technology

SHAN Rui

2023, 52(12):  2228-2228.  doi:10.11947/j.AGCS.2023.20220578

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Multivariate spatio-temporal Kalman filter and its application in deformation analysis

SHI Qiang

2023, 52(12):  2229-2229.  doi:10.11947/j.AGCS.2023.20220595

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Automatic recognition and its application of sloping lands in the Loess Plateau of China based on the prospective of geographic object

NA Jiaming

2023, 52(12):  2230-2230.  doi:10.11947/j.AGCS.2023.20220599

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