Table of Content

25 July 2023, Volume 0 Issue 7

Previous Issue    Next Issue

Dual response of the Loess Plateau ecosystem to climate change and human activities

JIANG Xiuwei, SHI Yun

2023, 0(7):  1-6.  doi:10.13474/j.cnki.11-2246.2023.0192

Asbtract ( )  

References | Related Articles | Metrics

In the context of climate change and increasingly intense human activities, to assess the spatial and temporal changes of ecological and environmental quality in the Loess Plateau region, this study takes the Loess Plateau as the study area based on the GEE platform, selects MODIS product data from 2000 to 2020 to construct the RSEI index, and uses the trend analysis method, standard deviation ellipse method, and residual analysis method to analyze the spatial and temporal changes of ecological and environmental quality in the Loess Plateau. The results show that: ①The RSEI of Loess Plateau has shown an increasing trend in the past 21 years, and its growth rate is 0.005/a (p<0.01).②spatially, the RSEI is mainly increasing, accounting for 92.78% of the total area of the region, and keep improving trend in the future.③In terms of migration, the migration distance of poor grade is the largest, at 85.67 km, followed by good grade with 49.05 km; the smallest migration distance is medium grade with 30.18 km.④Both climate change and human activities have positive effects on the RSEI of Loess Plateau, and human activities are the main driving factor.

Spatial and temporal dynamic change and influencing factors of ecological environment quality in Chaohu Lake basin based on GEE

WANG Ying, LI Daiwei, ZHANG Fan, ZHU Huizi, LI Longwei, LI Nan

2023, 0(7):  7-13.  doi:10.13474/j.cnki.11-2246.2023.0193

Asbtract ( )   HTML ( )   PDF (6645KB) ( )  

References | Related Articles | Metrics

Taking Chaohu Lake basin as the research area, remote sensing ecological index (RSEI) is constructed through Google Earth Engine cloud computing platform, and large-scale and long-time dynamic monitoring analysis and evaluation of ecological environment quality in Chaohu Lake basin are carried out by means of spatial autocorrelation and geographic detectors based on Landsat TM/OLI series remote sensing data from 2000 to 2020. The results show that:①The average value of RSEI increased from 0.70 in 2000 to 0.74 in 2020, showing an overall improvement trend, and the ecological environment level is mainly excellent and good. ②The global Moran's I index of the study area is all greater than 0, and the ecological environment quality in Chaohu Lake basin presented a clustering trend on the global autocorrelation, with a significant spatial positive correlation. In the past 20 years, the low-low aggregation area had a trend of increasing firstly and then decreasing. ③The ecological environment is affected by many factors, among which human factors had a great impact on the ecological environment of Chaohu Lake basin in 2010, which leaded to the decline of ecological environment quality.

Temporal and spatial evolution characteristics of land desertification sensitivity in Inner Mongolia autonomous region from 1980 to 2020

FU Qiang, ZHANG Haiming

2023, 0(7):  14-17,24.  doi:10.13474/j.cnki.11-2246.2023.0194

Asbtract ( )   HTML ( )   PDF (1347KB) ( )  

References | Related Articles | Metrics

Ecological sensitivity evaluation is one of the important foundations for studying the ecological status of territorial space and identifying different kinds of ecological protection spaces. This paper studies the spatio-temporal evolution of desertification ecological sensitivity in Inner Mongolia autonomous region from the year 1980 to 2020 at 1 km×1 km spatial grid scale based on quantitative evaluation method of desertification ecological sensitivity. The results show that: ①The spatial distribution of desertification sensitivity grade represents a basic pattern of lower in the east and higher in the west and north of Inner Mongolia;②38.3% of the grids remain the same sensitivity grade unchanged, and 37.9% of the grids maintain the sensitivity grade below moderate, and 38.8% of the grids maintain the sensitivity grade above moderate sensitivity (inclusive); ③Places such as mountain area of the northern section of great Khingan mountains, northern part of Hulunbuir grassland, West Liaohe plain, Hetao-Tumochuan plain and eastern and southern part of Ordos plateau remain low sensitivity grade or continue to reduce, while places such as southern part of Alxa plateau, the region on the north of hunshandake sand land remain high sensitivity grade or continue to increase. This study can provide scientific methods and spatial basis for delimitation of ecological protection and related policy-making.

Exploring the spatio-temporal variation of the regional environment and driving factors based on ecological sensitivity: taking Ding'an county as an example

SONG Peilin, XIE Jibo, YANG Tengfei, MOU Naixia, CHEN Mo, WANG Xiaoyu

2023, 0(7):  18-24.  doi:10.13474/j.cnki.11-2246.2023.0195

Asbtract ( )  

References | Related Articles | Metrics

Ecological sensitivity is one of the main methods for analyzing the stability of regional ecological environment, and its evaluation results are of great significance for regional ecological protection and decision-making. This article focuses on Ding'an county as the research area. It selects 9 sensitive indicators from four aspects of soil erosion, habitat, terrain, and water resources to construct an ecological sensitivity evaluation system. The combination weighting and analysis of the ecological sensitivity spatio-temporal distribution and changes in 2013 and 2021 are conducted using the AHP (analytic hierarchy process) and entropy weight method. Furthermore, it analyzes the spatial agglomeration, regional changes in ecological sensitivity, and the main driving factors behind them using geographic detector analysis. The results show: From 2013 to 2021, the ecological sensitivity of Ding'an county was the distribution pattern of high in the south and low in the north, and the overall ecological sensitivity showed a downward trend. The spatial agglomeration effect of ecological sensitivity is significant, but the spatial agglomeration decreases with time, and both high-value and low-value agglomeration areas tend to shrink. The transfer of ecologically sensitive areas mainly occurs in medium-sensitive and high-sensitive areas, and the level of change is mainly first-level increase and decrease. Compared with other sensitive indicators, the driving force of land use and vegetation coverage on ecological sensitivity is larger, and with the passage of time, the driving force of land use and vegetation coverage on ecological sensitivity tends to play a leading role.

Shallow sea water depth inversion from WorldView-3 multispectral images based on seabed sediment classification

YAO Chunjing, YU Zheng, WANG Jie, QIAN Chen, XU Junhao

2023, 0(7):  25-31.  doi:10.13474/j.cnki.11-2246.2023.0196

Asbtract ( )   HTML ( )   PDF (1559KB) ( )  

References | Related Articles | Metrics

In recent decades, sea water bathymetry inversion method based on remote sensing image has been a hot research topic. This paper uses WorldView-3 high-resolution satellite imagery, combined with satellite altimetry data, to focus on Wuzhizhou island which is near Hainan Island, China, and its adjacent waters as the main study area. After data preprocessing and substrate classification, multiple linear regression model, Stumpf logarithmic ratio model and BP neural network model are used to invert and analyze the water depth around the island. Results show that: for the three model, after the bottom sediment classification accuracy will be improved significantly. Among them, BP neural network model has the highest accuracy (root mean square error range of 0.2～0.7 m), followed by multiple linear regression model (root mean square error range of 0.3～0.8 m), and log ratio model has the lowest accuracy (root mean square error range of 0.6～1.1 m).

InSAR observations constrained coseismic slip distribution and Coulomb stress variation of Mw 6.7 Menyuan earthquake in 2022

WANG Xin, LI Shuiping, KANG Jing

2023, 0(7):  32-38.  doi:10.13474/j.cnki.11-2246.2023.0197

Asbtract ( )  

References | Related Articles | Metrics

In this paper, the line-of-sight (LOS) co-seismic deformation field of the Mw 6.7 Menyuan earthquake in Qinghai province on January 8, 2022 is obtained by using synthetic aperture radar differential interferometry (DInSAR) technology based on the Sentinel-1A satellite ascending and descending data. The non-negative least squares principle is used to retrieve the geometric parameters and co-seismic slip distribution of seismogenic faults. Finally, the Coulomb stress variation is calculated based on the fault slip distribution parameters and Coulomb fracture criterion. The results show that the Menyuan earthquake caused significant surface deformation, the coseismic deformation area is about 33 km×22 km, and the maximum LOS shape variables of ascending and descending data are -60 and 85 cm, respectively. Co-seismic sliding model display, the Menyuan earthquake is a left-lateral strike-slip event with a little thrust, and caused a co-seismic rupture about 36 km long (24 km for the main fault and 12 km for the branch fault) on the surface. The main rupture area is concentrated in 0～15 km depth, and the maximum slip of the main fault is 2.94 m, corresponding to 1.5 km depth.The maximum slip of the branch fault is 1.43 m, corresponding to 4.5 km depth. The seismic moment releases by inversion is 1.37×10¹⁹ N·m, which is equivalent to a Mw 6.73 earthquake. Based on the results of field investigation and fault inversion, it is preliminarily determined that the co-seismogenic fault is the west end of Lenglongling fault and ruptures to the east end of Tuoleshan fault. The results of coseismic Coulomb stress variation and aftershock distribution show that the Coulomb stress at the east end of Lenglongling fault and the west end of Tuoleshan fault are obviously under loading condition, and the risk of strong earthquakes in the future is high.

A deep learning method for nearshore bathymetry with ICESat-2 and Sentinel-2 datasets

ZHONG Jing, SUN Jie, LAI Zulong, SHEN Yifu

2023, 0(7):  39-43.  doi:10.13474/j.cnki.11-2246.2023.0198

Asbtract ( )  

References | Related Articles | Metrics

Currently, satellite-derived bathymetry (SDB) is widely used for nearshore bathymetry. However, the commonly used empirical models are too simple to be applied to various complex shore environments. To break through the limitations of traditional methods, this paper proposes a deep learning method for nearshore bathymetry with ICESat-2 and Sentinel-2 datasets. Cat Islands (CI) and Buck Island (BI) are used as the study areas. ICESat-2 is used to extract a priori bathymetry points, and then a one dimensional convolutional neural network(1DCNN) is trained on the Sentinel-2 data to obtain a bathymetry map of the study area. band ratio (BR), random forest (RF) and multilayer perceptron (MLP) are also used as comparison methods. Through quantitative analysis of accuracy, the root mean square error and coefficient of determination of water depth measured by the proposed method in CI and BI are 0.20 m, 0.94 and 0.95 m, 0.95, respectively, which verify the accuracy better than other comparative methods and improved the accuracy of water depth inversion.

Spatial and temporal change of water use efficiency and its response to air temperature and precipitation in the Mu Us Sandy Land

YANG Meihuan, LI Yang, WANG Tao, WANG Yuyao, LI Qihu, XIA Zhengqing

2023, 0(7):  44-50,79.  doi:10.13474/j.cnki.11-2246.2023.0199

Asbtract ( )  

References | Related Articles | Metrics

Water use efficiency (WUE) is an important index to study the coupling relationship between water and carbon cycles in terrestrial ecosystems. Based on MODIS data of gross primary productivity (GPP) and evapotranspiration (ET), the temporal and spatial distribution characteristics of WUE and its response to climate change in the Mu Us Sandy Land from 2001 to 2019 are studied. The results show that: ①GPP and ET in the Mu Us Sandy Land show a significant linear increasing process from 2001 to 2019, while vegetation WUE showes a weak linear decreasing process. Spatially, the WUE of vegetation in Mu Us Sandy Land is dominated by a decreasing trend, accounting for 64.53% of the total area of the region and concentrated in the central and western and southern regions. ②Among the different vegetation types WUE, woodland and scrub WUE show a linear increasing trend, while wetland, farmland, grassland and desert show a linear decreasing trend. ③There is a threshold effect on the sensitivity of vegetation WUE to precipitation in the Mu Us Sandy Land, with a threshold value of 300 mm, i.e. the vegetation WUE increases with precipitation within the threshold value, and decreases with precipitation after the threshold value is exceeded.

Spatial and temporal changes of forest cover and its driving factors over the Yellow River basin

MA Jingjing, GAO Meiling, LI Zhenhong, XU Huihui, PENG Jianbing

2023, 0(7):  51-57.  doi:10.13474/j.cnki.11-2246.2023.0200

Asbtract ( )  

References | Related Articles | Metrics

To investigate the spatio-temporal changes and driving factors of forest coverage from 1990 to 2020 in the Yellow River Basin, this study employs land use and land cover data, natural factors, and human activity data, and uses transfer matrix, Theil-Sen Median and Manna-Kendall trend analysis, and geographic detectors for research. The results show that: ①The forest coverage area has expanded in the Yellow River basin, with an increase of nearly 20 000 km². ②From 1990 to 2020, the forest coverage rate of 168 counties increased in the Yellow River basin, with only two counties showing a decrease in forest coverage. ③Based on geographic detectors, shortwave radiation has the greatest explanatory power for the distribution of forest coverage, while the interaction of rainfall and elevation has the strongest explanatory power in the analysis of factor interaction. This study can provide a scientific reference for the high-quality development of the ecological environment in the Yellow River basin.

The filtering method of airborne LiDAR point cloud for tidal flat DEM construction

FENG Xiaoke, Lü Peixian, ZHANG Ka, SHEN Huakang, YE Longjie, ZHAO Na, YANG Ying

2023, 0(7):  58-62.  doi:10.13474/j.cnki.11-2246.2023.0201

Asbtract ( )  

References | Related Articles | Metrics

In the process of constructing DEM based on laser point cloud, point cloud filtering is very important to distinguish ground points and non-ground points. Considering the requirement of high-precision DEM construction based on airborne LiDAR point cloud for coastal tidal flat regions, the paper proposes an improved slope filtering algorithm of airborne LiDAR point cloud. Firstly, a statistical outlier removal (SOR) method is used to remove noise from the original airborne LiDAR point cloud data. Secondly, utilizing the slope and elevation threshold of regular grids, the slope filtering method of ground points is designed for tidal flat point cloud data. Lastly, actual airborne LiDAR point cloud of the tidal flat in Changsha portof Rudong city is selected as experimental data to carry out the construction of tidal flat DEM and its accuracy is test, so as to verify the proposed method of point cloud filtering. Experimental results show that the accuracy of DEM constructed by LiDAR point cloud by the proposed methodmeets could meet the requirements of national and industrial standards.

Automatic extraction algorithm of step lines from point cloud in open-pit mine based on gradient of scalar field

ZHANG Bingjie, CAI Lailiang, WANG Xin, WU Jingdong

2023, 0(7):  63-68.  doi:10.13474/j.cnki.11-2246.2023.0202

Asbtract ( )  

References | Related Articles | Metrics

In order to efficiently analyze the terrain characteristics of open-pit mine, using UAV LiDAR to scan mine, this paper proposes an automatic extraction algorithm of step lines from point cloud in open-pit mine based on gradient of scalar field,which is referred to as scalar field gradient method. Firstly, the elevation information in point cloud is used as the scalar field corresponding to each point. Then calculate modulus of gradient of scalar field at each point, after analysis the ranges of modulus of gradient of the road and slope scenes are [0.00, 0.03] and [0.28, 0.35]; and then screen out the feature points of step lines according to the range of modulus of gradient.Finally, the feature points are indexed by a quadtree, and least-squares fit straight line in space for each leaf node, and fitted step lines is output. By comparison with step lines extracted by existing software,scalar field gradient method proposed in this paper has the advantage of less manual intervention, and the error rate of extracted step lines can be lower than 10%, and the position accuracy is better than 0.6 meters. The research results can greatly improve the automatic generation efficiency of open-pit mine surveying and mapping products, and have a good application prospect.

Modeling and geomorphological inversion of shallow gully erosion based on multivariate data in Imperial Mausoleum site of Weibei dryland

YANG Bo, YANG Xiaofeng, XIE Ruilian, LI Meng, REN Yitong, CHENG Jianglong

2023, 0(7):  69-73.  doi:10.13474/j.cnki.11-2246.2023.0203

Asbtract ( )  

References | Related Articles | Metrics

Guanzhong Eighteenth Tang Dynasty Imperial Mausoleum is a valuable historical and cultural heritage in ancient China.In the past thousand years, soil and water loss existed in different degrees in the Imperial Mausoleum site area, which destroyed the landscape of the imperial Mausoleum.In order to protect cultural heritage, using satellitie and UAV imaging products to estimate the development rate of shallow gully erosion in the past 53 years.The volume-area relationship model and soil erosion level are established.The results showed that: ①The site area benefite from the project of returning forest and grass, the land use slope farmland continued to decrease, and the grassland and forest land increase.The NDVI index of the forest area in the lower reaches of Sima road reaches 0.8, and the ecological environment of the site area improve significantly.The level of water loss will change from the severe one in 1968 to the mild one in 2021.②In Beishan area of Guanzhong, it develops into egg shape gully and its vertical cut, with a good fitting relationship between perimeter and area.③The gully development model of the site area of Tang Emperor's Mausoleum in Guanzhong Beishan area, on the southern edge of the Loess Plateau, has a good power function relationship between area and volume, y=0.040 5x+1.493 6, and the determination coefficient is R²=0.82。 The annual development of gully cutting in the past 53 years is 0.36 m/a.The above model can be used as the gully development model in the southern edge of the Loess Plateau and the northern mountain area of Guanzhong.④ In the whole site area and its surrounding areas, the ratio of water and soil loss and soil sediment volume is 38.5∶1.The area ratio of erosion and soil deposition is 11.5∶1.

Optimization of land surface temperature inversion algorithm for Landsat 9 data

WEN Yafei, LIU Yu, WANG Guanghui, ZHANG Qiuzhao

2023, 0(7):  74-79.  doi:10.13474/j.cnki.11-2246.2023.0204

Asbtract ( )  

References | Related Articles | Metrics

As a key parameter of energy exchange between surface and atmosphere, land surface temperature (LST) is widely used in many fields. Based on the Landsat 9 TIRS data, this paper optimized and updated the parameters of single window algorithm model and split window algorithm model to realize surface temperature inversion, and combined the measured data of SURFRAD site and the land surface temperature products for accuracy verification analysis. The results show that the determination coefficients of the two algorithms are both greater than 0.96. The split window algorithm model has higher accuracy and the error (RMSE) is about 1.45 K, while the single channel algorithm model has lower accuracy and the error (RMSE) is about 1.61 K. Compared with the single channel model, the split window model is less sensitive to the parameters. In the range of high water vapor content, the results of the split window model are better than those of the single channel model. The error (RMSE) values of the land surface temperature inversion method proposed in this paper and the official land surface temperature products are both within 2.5 K, which can meet the application requirements of producing land surface temperature products with thermal infrared remote sensing data.

Co-seismic deformation extraction and accuracy analysis of the Maduo Earthquake based on the combined of different global navigation satellite systems

TAN Mingming, FAN Yaling, Lü Kexin, HAO Shang, XU Tao, CAI Guotian, ZHANG Jie, LI Zhicai

2023, 0(7):  80-84.  doi:10.13474/j.cnki.11-2246.2023.0205

Asbtract ( )   HTML ( )   PDF (1431KB) ( )  

References | Related Articles | Metrics

At present, high frequency global navigation satellite system (GNSS) signal has been widely used in co-seismic deformation monitoring of major earthquakes. In this paper, the accuracy of seismic deformation monitoring by different satellite navigation system combinations is comprehensively analyzed. Based on the high frequency (sampling rate of 1 Hz) GNSS observation data of eight regional CORS stations in the near and far fields around the Qinghai Maduo Earthquake (Mw 7.4), the co-seismic deformation achieved and accuracy improvement ratio from single system to multi-system combination are preliminarily analyzed by precision point positioning technology processing strategy. Then, the co-seismic deformation error and accuracy improvement ratio of multi-system combination with the same number of systems and different satellite navigation system combinations are compared and analyzed. Finally, based on the combination of GREC2 (GPS/GLONASS/Galileo/BD-2) and GREC3 (GPS/GLONASS/Galileo/BD-3), the accuracy difference between BD-2 and BD-3 is analyzed. The results show that the accuracy of co-seismic deformation observation by multi-system combination is better than that by single system, among which GEC2+3 (GPS/Galileo/BD-2/BD-3) combination has the best accuracy. Compared with single system GPS, the accuracy of co-seismic deformation observation by GEC2+3 combination can be improved by 30%～60% in horizontal direction, while the vertical accuracy can be improved by 30% on average. The satellite navigation system combination with Beidou has the best performance. Among the satellite navigation system combination with 3 systems, the error of the combination with Beidou in horizontal direction and vertical direction can reach 5～6 mm and 6～9 mm, respectively.

Performance evaluation of real-time PPP time transfer

LI Xiao, QIN Weijin, YANG Xuhai

2023, 0(7):  85-90,153.  doi:10.13474/j.cnki.11-2246.2023.0206

Asbtract ( )  

References | Related Articles | Metrics

High-precision real-time products provide favorable conditions for the development of the timing terminal based on the real-time precise point positioning (RTPPP) technology. In order to analyze the effect that the timing terminal can achieve based on the time transmission of the real-time product, the quality analysis of the GPS observation data of the existing timing terminal is first analyzed, and then the PPP solution is carried out in combination with the real-time product. The test results show that from the analysis of satellite visible number, PDOP and Multipath, compared with the observation data of the NT02 and BRUX stations, the observation data of the timing terminal is of the same quality, so the data received by the station is stable and available, which can provide effective data for the next step of performance analysis. Subtract the real-time PPP time transfer result of the timing terminal from the post PPP time transfer result, RMS of the zero baseline common clock comparison result can be obtained to be better than 0.05 ns, and the RMS of the long baseline comparison result is better than 0.2 ns. The time transfer results of the two timing terminals in the zero baseline test are subtracted from the time transfer results of two devices with a receiver type of JAVAD TRE＿3, and the RMS is better than 0.07 ns, and the time transfer results of the two timing terminals in the long baseline test are subtracted from the time transfer results of two devices with receiver type SEPPT POLARX5TR, and the RMS is better than 0.2 ns.

Improved stacking filtering method considering multiple weighting factors

LI Xiaotong, LI Wei, XIE Xukang, HUANG Yutong

2023, 0(7):  91-96.  doi:10.13474/j.cnki.11-2246.2023.0207

Asbtract ( )  

References | Related Articles | Metrics

Aiming at the issue that correlation between stations is often neglected when extracting the common mode error of regional GNSS time series, this paper proposes an improved stacking filtering method which considers multiple weighting factors such as correlation coefficient and distance factor on the basis of existing research on stacking filtering, and analyzes the applicability of the method by selecting data from stations in Shanxi province. The results show that using the improved stacking filtering method in this paper, the root mean square of the coordinate residual time series is reduced by 48.53%, 39.42% and 48.61% on average in the N, E and U components, and the effect of the filtering on the velocity in the N and E directions is 0.5 mm/a and 1 mm/a in the U direction, and Compared with regional superposition filtering, this improved method further reduces the root-mean-square of the residual time series by 20%～40% and can extract the common mode error more accurately, which can provide fine and reliable data support for the study of the mechanism of regional crustal motion and dynamics.

Discussion on the management mode of ecological environment big data in Qilian Mountain Nature Reserve

GUAN Lin, WANG Ranghui, LIU Chunwei, ZHOU Limin

2023, 0(7):  97-106.  doi:10.13474/j.cnki.11-2246.2023.0208

Asbtract ( )   HTML ( )   PDF (2419KB) ( )  

References | Related Articles | Metrics

The advent of the era of big data has brought new challenges and opportunities to data management in the field of ecological environment. This paper discusses the data management model suitable for Qilian Mountain Nature Reserve from the perspective of the connotation, characteristics, technology system of big data, and its application in the field of ecological environment. First of all, the ecological environment big data in the protected area has a wide range of sources, diverse structures, and complex data processing methods. It is difficult to effectively collect, process and apply them through traditional technological means. Besides the “5V” characteristics of general big data, it also has geospatial characteristics. Secondly, big data technology runs through the whole process of data collection and preprocessing, data storage and management, data processing and analysis, and data interpretation, which provides technical support for the efficient management and comprehensive utilization of multi-source heterogeneous data in the reserve. Finally, the ecological environment big data technology is applied to solve the complex ecological environment problems, and the GEE cloud platform and ecological environment model simulation technology are combined to scientifically analyze the vegetation change, and the evolution trend of the vegetation coverage of the reserve and the vertical zonal difference rule of different altitudes from 2000 to 2020 are obtained. The management mode based on big data technology is the inevitable choice of ecological environment big data in the face of new situation and new trend, and it is also an important support to solve ecological environment problems.

A multi-density attribute clustering approach for polygons

CHEN Song, ZHANG Fuhao, QIU Agen, ZHAO Xizhi, WANG Yuan, OUER Geli

2023, 0(7):  107-112.  doi:10.13474/j.cnki.11-2246.2023.0209

Asbtract ( )  

References | Related Articles | Metrics

Clustering of polygons is an important means of mining the intrinsic spatial knowledge of polygons. The current problems of varying size, morphology and distribution of polygons lead to less accurate clustering results. At the same time, in order to meet the needs of analysis of large batch of polygons data,this paper proposes a clustering method for polygons with multi-density attribute calculation index. Firstly, according to the different locations (including boundaries) of the internal points of a single polygon, multiple density attributes are assigned to a single polygon. Secondly, based on the tendency of the low density values among the polygons for converge to the high density values, a polygon aim vector is generated, and the tree structure connections of the elements are sequentially generated. Finally, the clustering of polygons is completed by the strategy of connection pruning and merging. It is proved that the method can effectively identify the aggregation clusters of various irregular polygons, and has good accuracy performance in the aggregation of massive polygons data, realizing the clustering needs of recognition of high density polygonal regions.

Assessment of underground drainage pipeline bearing capacity through hydraulic modeling and GIS quantitative representation

XIE Zhiqiang, WANG Hao, ZHAO Lei, FU Xingfeng, JIANG Fengshan, YANG Shouquan

2023, 0(7):  113-118,124.  doi:10.13474/j.cnki.11-2246.2023.0210

Asbtract ( )  

References | Related Articles | Metrics

The underground drainage pipeline is an important urban infrastructure, and the research and evaluation of the bearing capacity of the underground drainage pipeline is the key for the city to survive the rainstorm period smoothly and safely to avoid urban waterlogging. Based on the SWMM model, this paper takes a representative key node in the main urban area of Kunming as the research object. Through the design and calibration of the urban underground drainage pipeline confluence model, the design and model construction of the urban rainfall model and the surface runoff model, combined with GIS to quantitatively express the simulated city The spatiotemporal distribution of the bearing capacity of each element of the drainage pipeline and its bearing capacity. In this paper, the bearing capacity of underground drainage pipelines in the study area is judged through simulation analysis of surface runoff, simulation analysis of pipeline operation, dynamic simulation analysis of water level at nodes at different times, and simulation analysis of discharge caliber flow characteristics. Carrying capacity provides a sufficient reference.

Combined LiCSBAS and machine learning ground monitoring and prediction method for Kunming city

LI Yangyang, ZUO Xiaoqing, XIAO Bo, LI Yongfa, YANG Xu, DONG Yujuan

2023, 0(7):  119-124.  doi:10.13474/j.cnki.11-2246.2023.0211

Asbtract ( )  

References | Related Articles | Metrics

To address the problems of tropospheric delay errors, deconvolution errors and the large amount of time and disk space required to process data over a large area in InSAR during data processing,in this paper, the atmospheric correction data of 134 Sentinel-1 lifting rail images of Kunming city from September 16, 2016 to May 5, 2021 are processed by LiCSBAS and synthetic aperture radar general atmospheric correction online service product, and the subsidence information of the main urban area of Kunming city is obtained.On this basis, five typical land surface subsidence areas are obtained and their temporal and spatial distribution characteristics are analyzed. Then, deep forest and long term memory network models are used to predict the time series values, and absolute error (ε), root mean square error (RMSE) and nash coefficient (NSE) are introduced to evaluate the models. Both the deep forest and LSTM prediction models are within 4 mm, RMSE values are 0.70 and 3.01, and NSE values are 0.92 and 0.81, respectively.The results show that the deep forest prediction model has a good effect. The urban surface monitoring and prediction method combined with LiCSBAS and machine learning model can provide a reference for future land subsidence monitoring and disaster warning.

Monitoring and analysis of the subsidence in Changsha from 2015 to 2021 based on InSAR technique

YANG Jiancheng, HE Yang, LIU Yiming, XIONG Xiong, YAO Haipeng, LI Xueyu, WEN Wufei, WANG Lingjue, HU Miaowen, XU Bing

2023, 0(7):  125-130.  doi:10.13474/j.cnki.11-2246.2023.0212

Asbtract ( )  

References | Related Articles | Metrics

Changsha city is an important central city in the middle reaches of Yangtze River. The geological condition is fragile and the soil is loose. Under the action of construction and rainfall, the soil is easy to consolidate and compact, resulting in ground deformation and threatening the stability of buildings and infrastructure. Land subsidence is one of the main causes of geological disasters in Changsha city. In order to monitor the land subsidence of Changsha city in recent years, we use the technology of MCTSB-InSAR and 151 Sentinel-1 data to obtain the land subsidence results of the main urban area of Changsha City from 2015 to 2021. The results show that the maximum accumulated settlement is about 250 mm, the maximum settlement rate is about 80 mm/a, and the average settlement rate in most areas is below 30 mm/a. The overall stability of Changsha city, local uneven settlement occurred, settlement area mainly distributed in the periphery of the main city, mainly caused by engineering construction.

Early identification of hidden dangers of geological hazards along oil and gas pipelines combined with InSAR and LiDAR

ZHAO Xun, YANG Mingfeng, WEI Xinnian, WANG Haifang, CHEN Jiangpan, YANG Li

2023, 0(7):  131-135.  doi:10.13474/j.cnki.11-2246.2023.0213

Asbtract ( )  

References | Related Articles | Metrics

Northeast Sichuan has complex geological conditions, and frequent geological disasters. Geological disasters pose a certain threat to the safe operation of pipelines. It is necessary to use scientific and effective methods to quickly identify hidden geological hazards along the pipeline. Taking an oil and gas pipeline in Dazhou City as an example, uses InSAR to carry out regional surface deformation monitoring, and combines high-precision remote optical sensing technology to preliminarily identify geological hazards along the pipeline. At the same time, obtained the refined characteristics and signs of slope deformation in key areas by airborne LiDAR technology, and further confirm the hidden dangers of geological disasters Finally, the early identification of geological hazards is completed through field investigation. Based on survey data, successfully identified 10 potential geological hazards, including 4 historical landslides or unstable slopes near the pipeline and 3 newly discovered potential geological hazards. The results show that the proposed method system can effectively identify the potential geological hazard areas along oil and gas pipelines, and can provide scientific basis for the prevention and control of geological hazards along oil and gas pipelines.

Application of high-density laser point cloud supported by improved U-Net model in asphalt road disease identification

ZHAO Lifeng, WANG Yong, WANG Xiaojing, REN Chuanbin, XU Pengyu

2023, 0(7):  136-141,159.  doi:10.13474/j.cnki.11-2246.2023.0214

Asbtract ( )  

References | Related Articles | Metrics

The neural network model can automatically identify road defects,however the detection accuracy can not meet the needs of road safety operation and maintenance in practical applications, and it is easy to cause missed detection and false detection of diseases. In response to the above problems, this paper proposes an improved U-Net model that combines grayscale images and depth images.Firstly, the data statistics method based on the depth map is used to automatically eliminate the disease-free data and reduce the computational complexity of the model. Secondly, the global context module is added to the traditional U-Net model structure to realize a lightweight network and improve the network performance on this basis. Finally, the elevation information of the road depth map is added to change the training data of the model from one-dimensional to two-dimensional.Based on the disease range and the pavement depth map, the pavement disease depth parameters are obtained.The results show that the improved U-Net model proposed in this paper, which fuses grayscale images and depth images has global recognition accuracy, accuracy, recall rate, and comprehensive evaluation index and mIoU indicators are 99.09%, 84.69%, 81.64%, 91.67% and 84.58%, respectively, which are higher than the other two models tested at the same time. In the test results of crack disease, This paper based on the improved U-Net model of grayscale image and depth map is 99.07%,which is higher than the other four models.Experiments show that this paper based on the improved U-Net network-based pavement disease identification and extraction algorithm can be used in complex scenes with noise interference. It can extract pavement cracks smoothly and efficiently, and has strong robustness. The algorithm proposed in this paper can provide an important reference for subsequent pavement repair work.

The application of PS-InSAR in the monitoring of the settlement of the Yangtze River levee

SHI Yintao, HU Chao, ZHAO Gang, HOU Tingting

2023, 0(7):  142-148.  doi:10.13474/j.cnki.11-2246.2023.0215

Asbtract ( )  

References | Related Articles | Metrics

Implementing and promoting the management and protection of the Yangtze River has always been a major task of the Yangtze River water conservancy work. As an important barrier to protect the development of the economic belt along the river, the deformation monitoring of the safety of the levee along the river is one of the important contents in the operation and management of the Yangtze River. As a new and large-scale monitoring method, InSAR has great promotion value in the investigation of hidden dangers of water conservancy projects. This paper uses PS-InSAR technology and Sentinel-1A image to extract the temporal and spatial distribution of deformation of Meizizhou in Nanjing and its surrounding levee from April 2020 to January 2022, and verify its reliability by combining the leveling data of the same period. The results show that the deformation of the levee on the Yangtze River is more obvious than that on the Jiajiang river, and the deformation rate of the levee near Qianzhou can reach -20 mm/a. Overall, the Meizizhou levee presents a consistent settlement deformation, and the differential deformation is not significant, indicating that the river levee in this area is relatively stable. PS-InSAR observation has a high consistency between the temporal and spatial distribution of deformation and the leveling data, indicating that this technology is suitable for monitoring the settlement changes of the Yangtze River levee, and can be used for large-scale Yangtze River levee risk investigation and analysis. Early identification of hidden dangers provides a feasible technical means.

Research and application of soil erosion monitoring methods in typical regions of Hunan province

WANG Wei, HUANG Huiqing, HU Luanyun

2023, 0(7):  149-153.  doi:10.13474/j.cnki.11-2246.2023.0216

Asbtract ( )  

References | Related Articles | Metrics

The changes in soil erosion are affected by various factors such as land cover, vegetation coverage, and terrain and localforms. We selected Xinhua county as a typical regions of Hunan province for research,based on surface erosion grading indicators, universal soil loss equation models, and slope factor, established soil erosion risk evaluation plan used on land use data and digital elevation model, completed the calculation of soil erosion intensity of Xinhua county in 2020, and completed the time and space analysis combined with soil erosion data in 2008. The main findings are as follows:Compared with 2008, the amount of soil erosion in Xinhua county increased slightly in 2020, but all belonged to mild soil erosion. The distribution of mild, intensity, extremely intensity, and severe soil erosion in the two years is basically the same. Due to afforestation in barren mountains, areas with severe soil erosion in 2020 have been improved, at the same time, due to the increase in shrubs and dry farm, moderate soil erosion in some areas intensified. This method can quickly monitor the trend of soil erosion, providing relevant departments with support and data support, and providing favorable services for the improvement of the ecological environment.

Construction technology of 3D real scene in whole area of city and county: taking Zhejiang province as an example

WU Houqing, LIU Huadong, PAN Xiaojun, XIONG Chengli, WU Di

2023, 0(7):  154-159.  doi:10.13474/j.cnki.11-2246.2023.0217

Asbtract ( )  

References | Related Articles | Metrics

The construction of 3D real scene in China is an important measure to implement digital China and digital development, it is also a specific deployment to implement the construction of new national infrastructure. Based on the construction of 3D real scene project in whole area of city and county of Zhejiang province, this paper designs a product system that takes into account the geomorphologic characterization and application requirements, studies the production technology system, confirms the scientificity and applicability of the research results through the practice in Xiaoshan district, Hangzhou city, Zhejiang province. The research content gives consideration to the requirements of 3D real scene construction in China & the distinctive characteristics of Zhejiang province, it provides a reference for other regions to promote next work.

Multi-source data fusion and transformation method of provincial fundamental geo-entities based on knowledge-rule

YE Fen, HU Yan, YANG Qilin, HU Xiaodan

2023, 0(7):  160-164.  doi:10.13474/j.cnki.11-2246.2023.0218

Asbtract ( )  

References | Related Articles | Metrics

While Hunan's new fundamental surveying and mapping system is progressing steadily, the transformation and database construction of fundamental geo-entities on the provincial level is one of the important tasks. Under the premise of following the relevant technical standards of the Ministry of Natural Resources, a set of standards and specifications for the classification of fundamental geo-entities applicable to Hunan province has been established. By integrating the 1∶10 000 fundamental geographical information and the annual changes of the third national land resource survey and other multi-source data, taking the geo-entity codes as the unified identifier, the research proposes a knowledge-rule based multi-source data fusion and transformation method for provincial geo-entities after making full use of the existing stock data, and realizing the standardization transformation of provincial fundamental geo-entity data, so as to avoid the waste of resources in repeated production, and greatly improve the production efficiency of fundamental geo-entities. Therefore, it is conducive to the promotion and application of fundamental geo-entities in the industry.

Analysis of equilibrium and affected areas of shared bicycles connected to metro stations at different times

HAN Xiao, WANG Shaojun, WU Xuequn

2023, 0(7):  165-172.  doi:10.13474/j.cnki.11-2246.2023.0219

Asbtract ( )  

References | Related Articles | Metrics

This article takes two consecutive weeks of shared cycling data in Shenzhen as the research object. From the perspective of connecting with subway stations, subway stations are divided into balanced stations, loss stations, and surplus stations, and the equilibrium characteristics of urban subway stations at different times are analyzed; And boundary extraction is performed on the OD points at the non subway end of cycling to obtain the attractive areas for subway station shuttle cycling at different times under different travel modes. The results indicate that:①subway stations have good balance in the central urban area and relatively remote areas with less cycling, while their balance is poor in areas with dense residential areas. ②In the area with a high degree of comprehensive land use in the central urban area, the subway station has a large attraction area for shuttle riding, while in the single land use area (residential area), the attraction area is small.

Exploration and practice on the construction of high-level teachers of geographic information science

DENG Min, LIU Qiliang, SHI Yan, CHEN Jie

2023, 0(7):  173-176.  doi:10.13474/j.cnki.11-2246.2023.0220

Asbtract ( )  

References | Related Articles | Metrics

Teaching staff is the key factor in the construction of first-class majors and the cultivation of first-class talents,and also the implementer of promoting the organized scientific research in China's universities. Taking the geographic information science major of Central South University as an example,this paper discusses the influencing factors and implementation approaches of the construction of high-level teaching staff in the industry featured “double first-class” universities. We also analyze the achievements and problems of the construction of the teaching staff in recent years. This paper may provide some reference for the construction of first-class specialty of geographic information science and the improvement of talent training quality.

Fusing adaptive optimal neighborhoods and convolutional neural networks for 3D point cloud classification

ZHANG Qingbo, YAN Jiadong

2023, 0(7):  177-182.  doi:10.13474/j.cnki.11-2246.2023.0221

Asbtract ( )  

References | Related Articles | Metrics

We propose a 3D point cloud classification method that adaptively selects the optimal neighborhood size of a single point and learns deep-level features with stronger generalization ability. Firstly, we obtain the optimal local neighborhood information of each point based on the adaptive optimal neighborhood size selection, and then extract the low-level features of the point cloud based on the local neighborhood information; then we design a convolutional neural network model with the low-level features of the points to be classified as the input, learn the deep-level features that can reflect the inherent properties of the target features and realize the classification. Finally the experiment is conducted using Topcon's 3D point cloud dataset, which is obtained by a mobile platform equipped with a TOPCON GLS-2200 3D laser scanner. The results show that the overall accuracy of the classification results of this paper reaches 90.48%, which is better than other point cloud classification methods.