Table of Content

25 February 2022, Volume 0 Issue 2

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The influence of image control point layout on the accuracy of real scene modeling in complex area of survey and demarcation

ZHOU Shiyang, WU Xiangyang

2022, 0(2):  1-4,15.  doi:10.13474/j.cnki.11-2246.2022.0033

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In order to study the influence of the layout of image control points in the complex area of survey and delimitation on the accuracy of real scene modeling and whether the modeling can meet the requirements of measurement accuracy, according to the actual situation that the buildings in the survey area are dense in the west and sparse in the east, five image control point layout schemes are designed for image acquisition and three-dimensional modeling, and the accuracy of the models made by each scheme is compared and analyzed from three aspects: plane accuracy, elevation accuracy and side length accuracy. The results show that the survey area models made by the five layout schemes can meet the accuracy requirements in plane accuracy, elevation accuracy and side length accuracy; On the basis of edge layout, appropriately increasing the number of image control points in dense areas such as buildings can improve the accuracy of the model. This study can provide a guiding scheme for the layout of image control points in complex areas.

Scene recognition of photovoltaic panels based on model migration and convolution neural network

WANG Shengli, ZHU Shouhong, JIANG Yi

2022, 0(2):  5-9.  doi:10.13474/j.cnki.11-2246.2022.0034

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The acquisition of spatial information of photovoltaic (PV) panels is of great significance to the monitoring of resources and environment and the assessment of energy structure. It has been proved that it is feasible to extract spatial information from remote sensing images based on scene units. The traditional PV power plants recognition depends on the middle and low level characteristics of artificial design. It can not overcome the problems of spectral uncertainty and complex object space structure. The algorithms have problems of low robustness and low efficiency. Although some scholars have used the depth model to classify the image scene, most of the algorithms are based on a few standard remote sensing image scene databases, which do not take into account the influence of the image quality, the scene boundary and the scale on the depth feature of the image scene in the actual application and it restricts the deep application of remote sensing technology in urban structure,economic and social knowledge mining. To this aim, this paper adopts the strategy of transfer learning and model adjustment to identify the scene of PV panels in medium resolution remote sensing images. The results show that the proposed method can extract the multi-level features of the PV panels and achieve good recognition results in the PV panels with complex morphological structure.

Automatic building extraction from oblique photogrammetry data by combining height and spectral information

WANG Zhen, ZHANG Tao, DING Lele, PAN Yuming, SHI Furong

2022, 0(2):  10-15.  doi:10.13474/j.cnki.11-2246.2022.0035

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Building is a major component of 3D model and its vectorization mainly relies on manual delineation. Some studies have investigated the building extraction using deep learning methods, however, such methods require large volume of labeled training samples. To solve these problems, this paper proposes a method for automatic building extraction by combining height and spectral information of oblique photogrammetry data in typical areas of Tianjin. The method employes height threshold segmentation, vegetation elimination, and morphological post-processing to gradually refine the building extraction results, which achieves the overall accuracy of 94%. The extracted building footprints are vectorized and regularized, and then the individual building can be queried in geographic information system which can promote the application of 3D real-scene model.

Curved surface measurement by integrating 3D laser scanning and architectural design coordinates

XU Yanbo

2022, 0(2):  16-19,49.  doi:10.13474/j.cnki.11-2246.2022.0036

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In view of the complex hyperboloid structure of the track, there is no BIM model for reference and the accuracy of surface detection is high, this paper takes snowmobile and sled track of Beijing Winter Olympic Games as an example, proposes to use 3D laser scanner to scan the finished surface of the track, combined with the architectural design coordinates to complete the feature point detection. And the design 3D coordinates are modeled, the model is compared with the scanning point cloud data. The deviation value of any point can be grasped by generating 3D chromatogram. The results show that this method can not only solve the detection of key feature points, but also fully grasp the deviation of the whole complex surface, and meet the requirements of high-precision measurement, which provides ideas and technical reference for such complex surface detection engineering in the future.

Structuring methods of geographic entities towards construction of smart cities

WANG Lin, GUO Gongju, LIU Yining

2022, 0(2):  20-24.  doi:10.13474/j.cnki.11-2246.2022.0037

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As a basic unit of government administration, the structuring of geographic entities is crucial contents in the construction of smart cities. This paper elaborates the structuring extent of geographic entities toward city-level application based on analysis into studies and applications concerning geographic entities home and abroad, and takes the two typical entities of yards and buildings as examples to analyze their data characteristics and explore their contents and structuring methods. The study in this paper provides reference for the structuring and intelligent application of geographic entities in the construction of smart cities.

detection based on superpixel segmentation and CRF for high-resolution remote sensing images

YANG Jingyu, JIA Duoke, WANG Yangping

2022, 0(2):  25-30,49.  doi:10.13474/j.cnki.11-2246.2022.0038

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High-resolution remote sensing image change detection algorithms are too sensitive to spectral changes, a new algorithm based on super-pixel segmentation and improved conditional random field (CRF) is proposed in this paper to detect changes in remote sensing images. Firstly, the student's-t mixture model (SMM) with spatial constraints super-pixel segmentation model is used to generate homogeneous patches,which has characteristic of boundary adhesion and brightness uniformity. Then the algorithm obtains change amplitude image by calculating the feature difference between the segmented dual phase image patches. Finally, the change amplitude image is clustered by FCM, and clustering result is used as the first-order potential of CRF, and the spectral spatial similarity constrained function is used as the second-order potential of CRF. Experiments results show that the detection accuracy of the method proposed in this paper is improved by 5%, and the false detection rate and missed detection rate are reduced by 3%, this method can better handle the spectral changes of the input image and keep the edge details of the change detection results.

Accuracy evaluation of UAV tilt photogrammetry compared with traditional low altitude aerial photogrammetry

CAI Jialun, JIA Hongguo, LIU Guoxiang, ZHANG Bo, LIU Qiao, WU Renzhe, XIANG Wei, MAO Wenfei, ZHANG Rui

2022, 0(2):  31-36.  doi:10.13474/j.cnki.11-2246.2022.0039

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At present, the domestic tilt photogrammetry technology is still in the stage of rapid development and promotion, and its accuracy highly depends on the selection of aerial survey parameters in the whole process of aerial survey production, so it is difficult to realize the quantitative analysis of its absolute accuracy index. In view of this difficulty, this paper adopts the way of comparative analysis taking the traditional low altitude aerial survey as the reference, on the basis of strictly unified the external data acquisition conditions and solving parameters, evaluates and analyzes the accuracy of unmanned aerial vehicle (UAV) tilt photogrammetry, and explores the outstanding technical advantages of UAV tilt photogrammetry. The experiment involves 12 kinds of mainstream aerial survey modes and 52 kinds of progressive layout of ground control points in order to compare and analyze the accuracy index of the results, and complete the quantitative analysis of tilt photogrammetry compared with traditional low altitude aerial survey. This study can provide certain reference and practical guidance for the accuracy evaluation of tilt photogrammetry.

Feasibility analysis of using local feature matching for the geo-reference offset estimation of satellite images

U Zepeng, XU Ershuai, WANG Wenliang, XU Zhihua

2022, 0(2):  37-42.  doi:10.13474/j.cnki.11-2246.2022.0040

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Geo-reference offset is one of the important parameters for evaluating the quality of satellite images. In this paper, we estimate the geo-reference offset of satellite images using local feature matching, followed by the analysis of its feasibility. Firstly, the subset of satellite images covering typical ground landmarks are selected as the reference database. Following that, the local point features are extracted for searching for the correspondences between satellite image and the reference database at sub-pixel scale. In order to improve the matching accuracy, the constraints of spatial relation and geometric consistency are taken into the consideration. Next, the interpolation of the correspondences between the satellite image and the reference database is performed to obtain the spatial coordinates of the tie-points in the satellite images. Finally, the rotation and offset parameters of the satellite image relative to the reference database are obtained with quantitative analysis of its feasibility. In this paper, we choose Fengyun satellite for the experiments, where the image subsets including coastline, lakes, mountains, rivers and islands landmarks are selected as the reference database. Three local features, in terms of SIFT, SURF and ORB are used for local feature matching. The experimental results show that the RMSE error of estimating the geo-reference offsets is less than 0.1 pixels, which confirms the feasibility of the local feature matching strategy.

Identification of surface deformation caused by geothermal resource extraction using SBAS time-series technology

LI Bingfeng, LI Genger, NA Jing, TU Liping, FAN Junlin, WU Yang

2022, 0(2):  43-49.  doi:10.13474/j.cnki.11-2246.2022.0041

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This article takes the Xiongan New Area, which is rich in geothermal resources, as the research object. Using SBAS technology to process 42 Sentinel-1 regional satellite images from July 2015 to February 2019 and 10 ALOS-2 regional satellite images from August 2016 to December 2018 to obtain the time-series surface deformation of Xiongan New Area. The results of the study show the Subsidence of Xiongan New Area is serious, and the subsidence areas are mainly concentrated in Xiong County and Rongcheng County. Among them, Xiong County has the most serious subsidence. The accumulated subsidence of the center exceeds 330 mm. The cumulative subsidence of the subsidence center in Rongcheng County exceeds 120 mm. Combining the location of geothermal wells and the history of geothermal exploitation, time-series analysis shows that large-scale exploitation of geothermal resources will cause surface subsidence.and the accumulated subsidence of the subsidence.

Analysis of the changes in the Beijing-Tianjin-Hebei urban agglomeration's spatial structure using NPP-VIIRS data

LI Yu, CHEN Mi, FU Yingchun

2022, 0(2):  50-55.  doi:10.13474/j.cnki.11-2246.2022.0042

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This paper accesses NPP-VIIRS data to analyze the Beijing-Tianjin-Hebei urban agglomeration's spatial structure from 2015 to 2019, through data statistics, city rank-scale rule, spatial correlation intensity. Also, combined with the city master plan and other documents, discuss the temporal and spatial change. The results showed that: ①The total amount of nighttime light in the Beijing-Tianjin-Hebei urban agglomeration show an overall upward trend. Beijing and Tianjin had the highest lightning growth rates, followed by Langfang and Shijiazhuang. ②The lights are concentrated in the high-ranking cities Beijing and Tianjin. Small and medium-sized towns are underdeveloped. However, in terms of time series, small and medium-sized towns are developing rapidly, the lights of cities were tending towards ZIPF distribution. ③With the advancement of regional transportation integration, the degree of correlation between cities had generally increased. The overall connections between Beijing and Tianjin were dominant. The traffic connection between the northern towns and the central-southern regions is insufficient so that the correlation is weak.

Multi-source and multi-temporal data urban change detection based on ratio method

LE Ying, XIA Yuanping

2022, 0(2):  56-61.  doi:10.13474/j.cnki.11-2246.2022.0043

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Aiming at the problem that conventional classification methods for change detection of medium and low resolution images can not achieve ideal results, this paper proposes a method of urban change detection combining radar data and optical images based on ratio method.The method integrates the advantages of radar data and optical image, takes Dingnan county of Ganzhou as the research object,uses ratio method respectively to detect the urban change of two kinds of data sources. Through the analysis of urban ground object target scattering characteristics of the multiple phase change it composite false color. Finally, the city construction planning is analyzed and verified to complete the real-time dynamic change detection of urban.The results show that the ratio method using multi-source and multi-temporal data can successfully extract the change information of the experimental area, and the texture information is clearer and more accurate in the change detection of urban buildings.

Research on urban land use extraction at the metropolitan scale

SUN Qinqin, CAI Guoyin, YANG Liuzhong, ZHANG Ning, DU Mingyi

2022, 0(2):  62-66.  doi:10.13474/j.cnki.11-2246.2022.0044

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With the improvement of the high resolution of domestic satellites, the detailed description of urban surface elements can be described from different aspects such as geometric form, texture structure, and spectral information. Compared with object-oriented classification method, the rapid development of deep learning technology has continuously improved the accuracy of urban building extraction. However, due to the high buildings and trees on both sides of the road, the extraction accuracy of urban roads is still limited. Based on the use of convolutional neural networks to extract buildings, this paper uses OSM polygon road data and urban boundary data, combined with normalized vegetation index and water index, and with the help of spatial layer overlay and error-tolerant processing, high-precision extraction of urban buildings, roads, vegetation and water bodies within urban built-up areas has been achieved. This study provides an effective approach in supporting for domestic high-resolution image-assisted urban fine management and application.

Comparison of additional parameter model-based self-calibration bundle block adjustment algorithms

ZHANG Ke, WANG Yongbo, YUAN Kun, QIU Chunping

2022, 0(2):  67-72.  doi:10.13474/j.cnki.11-2246.2022.0045

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Image point offset is one of the main factors affecting the accuracy of bundle block adjustment. For a long time, how to overcome the influence of the offset in adjustment, and then improve the accuracy of the block adjustment, has received close attention and great importance from scholars in this industry. At present, the conventional method to overcome image point offset is to describe it with a specific parameter model, build an additional parameter model-based self-calibration bundle block adjustment and solve the introduced parameters while doing adjustment to realize the compensation of systematic error. Among the existing algorithms, Bauer model, Ebner model, Brown model and optical distortion model are common models to describe image point offset. In order to verify the effect on systematic error of the above four models in block adjustment, this paper designs self-calibration bundle block adjustment models corresponding to the four models based on classic bundle block adjustment, and implements them by programming. Finally, the algorithm results are verified, compared and analyzed through examples. Experiments show that introduction of Ebner model and Brown model can effectively improve the accuracy of bundle block adjustment; introduction of Bauer model is more effective in improving the accuracy of small block adjustment; introduction of optical distortion has a relatively little effect on improving block adjustment accuracy.

Cloth simulation filtering method of dense matching point cloud based on virtual grid classification

SHI Zhuang, DU Quanye, WANG Qingdong, MA Dongling, CUI Yan

2022, 0(2):  73-77.  doi:10.13474/j.cnki.11-2246.2022.0046

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In order to improve the accuracy, efficiency and adaptability of the dense matching point cloud filtering algorithm for oblique images in complex terrain scenes, for the shortage of the traditional cloth simulation filtering algorithm, this paper proposes a cloth simulation filtering method based on virtual grid classification. Firstly, this method constructs a virtual grid with a buffer zone; And then divides the virtual grid into three types: flat ground, gentle slope, and steep slope according to the point cloud slope within its range; Finally, different types of virtual grids use the corresponding cloth parameters for cloth simulate filtering, then realize the point cloud classification of oblique image matching point cloud in complex terrain scenes. The results are compared with the single-parameter cloth simulation filtering. The experiment show that the results of the cloth simulation filtering method based on virtual grid classification are closer to the result of visual interpretation, and this method is suitable for hybrid terrain filtering.

Denoising method of GNSS station coordinate time series based on LMD and EMD

XIONG Changliang, HE Xiaoxing, MA Xiaping, FU Jie

2022, 0(2):  78-82.  doi:10.13474/j.cnki.11-2246.2022.0047

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Aiming at the problem that the signal and noise of GNSS station coordinate time series is hard to separate, based on the traditional EMD denoising method, a new method of coordinate time series denoising combining LMD and EMD is proposed. This method first uses LMD to decompose the original coordinate time series, separates high-frequency noise and low-frequency signals based on the principle of consecutive mean square error(CMSE), keeps the low-frequency components unchanged, and then performs EMD denoising on the high-frequency components. Finally, the sum of the low-frequency signals obtained by the two decompositions is the time series after denoising. Experiments are carried out with simulation data and measured data from 8 GNSS reference stations, and the accuracy is evaluated through a variety of evaluation indicators. The results show that the combined LMD and EMD method can remove the noise in coordinate time series more accurately than the traditional EMD method.

Spatial-temporal change driving forces and distribution prediction of landscape ecological risk in Harbin

ZHANG Yujuan, QU Jianguang, HOU Jianguo

2022, 0(2):  83-89,94.  doi:10.13474/j.cnki.11-2246.2022.0048

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This paper takes Harbin as the research object,constructs a landscape ecological risk and prediction model, analyzes the driving force of temporal and spatial change of landscape ecological risk from 1998 to 2018, and predicts the spatial distribution of regional landscape ecological risk in 2023. The results show that：①The regional landscape ecological risk decreased firstly and then increased in recent 20 years, and the spatial pattern changed significantly. ②Road distance, secondary industry, agriculture and elevation are the main driving forces for the change of landscape ecological risk. From 1998 to 2008, the distance coefficient of roads decreased around the main urban area and increased in the south. No significant change was observed at other times.The overall impact of agriculture and elevation on regional landscape ecological risk was significant, and there were spatial differences. The degree of impact of secondary sector of the economy on regional landscape ecological risk increased first and then decreased. ③The predicted spatial difference of landscape ecological risk in 2023 is not obvious, and the reduced area is larger than the increased area.

Study on inversion model of significant wave height from shore-based GNSS-IR by using NARX recurrent neural network

ZHANG Yi, ZHOU Li

2022, 0(2):  90-94.  doi:10.13474/j.cnki.11-2246.2022.0049

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Significant wave height is the main parameter of marine dynamic environment. This paper proposes a method to build the shore-based GNSS-IR significant wave height inversion model using NARX regression neural network. The method aims to explore how to use the data of a common single antenna measurement GNSS receiver to invert the significant wave height, and this paper gives the relevant processes and methods from data selecting, data processing to model construction. At the same time, this paper uses the two-year data from P231 station in the Stanford University Hopkins marine station for shore-based experiments. The results show that this method is suitable for the inversion application of significant wave height in the range of 0.1~2.5 m, and the min mean squared error of the inversion results of significant wave height is 0.01 m.

Simulation and prediction of land-use change in Nanjing based on artificial bee colony cellular automata model

WU Lüewei, LIU Geng

2022, 0(2):  95-99.  doi:10.13474/j.cnki.11-2246.2022.0050

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This paper builds an artificial bee colony cellular automata (CA_ABC) model with Nanjing as the study area, calibrates CA_ABC model by simulating urban expansion from 2000 to 2007, and validates the CA_ABC model from 2007 to 2015 using the actual land-use data. End-state overall accuracies (OA) are 80.61% for 2007 and 87.79% for 2015, while figure-of-merit (FOM) metrics are 19.25% for 2007 and 21.23% for 2015. This paper uses CA_ABC and Markov chain calculating the total urban land amount in Nanjing in 2025 and 2035, predicts the land-use pattern and analyzes the urban encroachment on ecological land. The prediction results show that urban expansion will mainly come at the expense of cultivated land and forest land in the next 20 years. 80% of the urban expansion in 2025 and 2035 will come from the encroachment on cultivated land, and 17% of the urban expansion area is the encroachment on forest land in 2015. This study shows that accurate simulating and predicting the future urban pattern and evaluating the urban encroachment on ecological land are helpful for decision makers reasonably plan for sustainable urban development.

Quantitative study on geospacial factors affecting high-precision housing vacancy rate

ZHANG Dong, LI Deping, ZHOU Liang, WANG Jiacheng, MA Yu, YI Min

2022, 0(2):  100-105.  doi:10.13474/j.cnki.11-2246.2022.0051

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To reveal the dependence of housing vacancy rate on geospatial factors，this paper uses a 50 m×50 m grid as the basic unit, and calculates the grid-scale housing vacancy rate, natural factors and social factors through modeling and other methods, and divides the study area into different levels and analyzes the correlation.Further research on the influence mechanism of natural factors using the geo-detector method. The results show that: ① The housing vacancy rate in the study area is significantly correlated with the selected geospacial factors, and the impact of other natural factors is generally low, except for the proportion of vegetation on the house vacancy rate. ② Since the non-built-up areas are still in the stage of rapid development and have great development potential, the non-built-up areas are more dependent on social and natural factors than built-up areas. ③ The housing vacancy rate of each street is generally less affected by the slope than other natural factors.The interaction of each factor significantly enhances the explanatory power of the housing vacancy rate.This study provides a reference for the analysis of the influencing factors of the housing vacancy rate in small areas.

Water information extraction in Shanghai by integrating random forest model and six water indices

CUI Qinglin, WANG Mingquan, HUANG Yongjian

2022, 0(2):  106-109.  doi:10.13474/j.cnki.11-2246.2022.0052

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In order to know water distribution information quickly and accurately, this paper selects Shanghai as the study area，constructs a feature set of water extraction based on multi-temporal Sentinel-2 satellite data, uses random forest model with high efficiency and good robustness to extract water in Shanghai. To improve the accuracy of water extraction, six water indices are added into the feature set of water extraction based on the characteristics of existing spectral bands: NDWI、MNDWI、AWEI_sh、WI₂₀₁₅、SWI and RWI. According to the characteristics of 10 spectral bands and 6 water indices, eight experimental schemes are designed to explore the effect of adding water indexes on water extraction. The results show that the scheme which included all the six water indices has the highest overall accuracy, which is 97.910%. NDWI and RWI can also improve the accuracy of water extraction and reduce the rate of leakage and error.

Design of ground-based observation simulation system for LEO satellite navigation enhanced constellation

ZHOU Quan, ZHANG Yang, LI Zishen, HAN Baomin, MENG Hao, DONG Xiaosong, GUO Zhenhua

2022, 0(2):  110-115.  doi:10.13474/j.cnki.11-2246.2022.0053

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Aiming at the restriction of LEO satellite navigation enhancement research due to the lack of the observation data of LEO constellations nowadays, the ground-based observation simulation system of LEO navigation enhanced constellation is designed. Firstly, the observation model of the pseudo-range and the carrier phase are derived, then the process and architecture of the simulation system are introduced, finally the SPP and PPP are calculated respectively based on the simulated ground-based LEO observation data. The correctness of the simulation system and the accuracy of the simulated pseudo range and carrier observation data are verified. The results show that, after considering various error models, the observation data simulated by the designed system owns a higher confidence compared with the ground-based observation data when only the geometric distance is considered. The system can be used to support the LEO navigation enhanced constellation positioning research.

Visible light vegetation extraction of hue saturation and lightness color model

CHENG Tao, GUAN Linjie, ZHENG Xinyan, TAO Shu, GAO Yin

2022, 0(2):  116-120.  doi:10.13474/j.cnki.11-2246.2022.0054

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As remote sensing images that only have three visible light bands: red (R), green (G) and blue (B) cannot use normalized difference vegetation index (NDVI) method to extract vegetation land cover information, a new method based on hue saturation and lightness color model is proposed. The image is transformed from RGB color space to HSL color space by using the self-developed system, and normalized hue lightness vegetation index (NHLVI) is constructed. By analyzing the characteristics of vegetation and non-vegetation information in HSL color space, and the characteristics of NHLVI, H, S, L, R, G, B, the vegetation information is extracted by cooperating with NHLVI and S indexes, and the non-vegetation information in the result is eliminated by using B component feature, so as to realize vegetation information extraction and improve the extraction accuracy. The results show that this method could improve the accuracy of visible light vegetation extraction and the applicability of the method by adding S index to the existing NHLVI index method.

Unmanned image classification in karst area combining topographic factors and stratification strategy

JIA Yu, WANG Hong, CAI Hong, ZHANG Lei

2022, 0(2):  121-127.  doi:10.13474/j.cnki.11-2246.2022.0055

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The karst topography in southwestern China is filled with fantastic caves and curved areas. And the classification of groundobject is relatively fragmented, which leads to the reductionin in the accuracy of the traditional one-time classification of spectral features.Based on the high-definition of UAV orthophoto and terrain factor, this paper makes full use of the spatial, spectral, texture and terrain features of UAV remote sensing images and adopts the object-oriented CART decision tree algorithm and hierarchical strategy to pickup the coverage type of the land inspecific study area. The method of combining spatial terrain factors and hierarchical strategies reduces the interference among the fragment edground objects in the karst area actually has a much higher classification accuracy. The whole classification accuracy reach 91.2%and the Kappa coefficient is 0.87, which is respectively 9.8% and 0.13 higher than the traditional one-time classification accuracy and Kappa coefficient. It shows that this method is suitable for decoding land coverage in southwest karst area, which could provide favorable reference for land-use monitoring.

A dynamic control method of oblique photography service accuracy of I3S standard

ZHONG Nana, TENG Ziqing, HU Zhenbiao, WANG Haiyin, ZHAO Jun

2022, 0(2):  128-130,135.  doi:10.13474/j.cnki.11-2246.2022.0056

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Aiming at the problem of high confidentiality requirements for the sharing of oblique photography data services and complex production process of different precision oblique photography data packets, based on the open source I3S standard specification, by analyzing the structural characteristics of oblique photography online services, this paper researches and realizes a dynamic control method of oblique photography service accuracy based on I3S standard. By controlling the node level of the index tree, a set of data can be used to realize online services with multiple precisions according to service requirements. As an important technical support for real 3D construction, it has good practical value.

Applicability analysis of relative elevation threshold method in recognizing diphtheria aconitum in UAV images

FAN Yuan, FAN Hong, WU Jianguo, LIN Jun, CHEN Jijun, Baris, ZHENG Jianghua

2022, 0(2):  131-135.  doi:10.13474/j.cnki.11-2246.2022.0057

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Taking the typical poisonous grass diphtheria aconitum in the Nalati grassland of Xinyuan county, Ili Kazak Autonomous Prefecture, Xinjiang as the research object, the PhotoScan software is used to process the drone aerial images and obtain the DSM data of the study area. On this basis, the relative elevation threshold is used. The method extracts the optimal threshold range for identifying diphtheria aconitum and verifies its effectiveness. The results show that: ① In UAV images, the relative elevation threshold method can clearly and accurately reflect the distribution characteristics of ground features, and is suitable for extracting ground features with obvious height errors from ordinary grass; ② When 10 cm≤T<20 cm, diphtheria aconitum can be accurately identified, and is basically consistent with the actual distribution of diphtheria aconitum, with a classification accuracy of 92%; ③ The relative elevation threshold method can better separate diphtheria aconitum, which improves the reliability of the classification basis. It also realizes the high-precision identification of diphtheria aconitum. This method can be applied to actual grassland monitoring.

Surveying and mapping quality inspection system and demonstration for Z-5 unmanned helicopter aerial survey

QIANG Xinlin, JIANG Sheng, WANG Ji, QIAN Chengyang, FANG Xuan

2022, 0(2):  136-139.  doi:10.13474/j.cnki.11-2246.2022.0058

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It is of great significance to conduct emergency surveying and mapping based on unmanned helicopter. But at present, there is a lack of surveying and mapping quality inspection system and quantitative indicators for unmanned helicopter aerial photography system. This paper proposes a survey and mapping quality inspection system based on Z-5 unmanned helicopter and supporting aerial photography system, including digital aerial photography results inspection, aerial three encryption results inspection and digital orthophoto results inspection. At the same time, this paper defines the quantitative data of important indicators. Through the actual flight verification, the aerial photography system based on Z-5 unmanned helicopter can meet the requirements of surveying and mapping accuracy.Four of them can further improve the threshold of quantitative indicators, so as to meet the requirements of more accurate UAV mapping.

Stability evaluation of ship hull in anchoring state based on GNSS attitude determination

JIANG Junyi, GAO Xingguo, QU Meng, MA Chao

2022, 0(2):  140-144.  doi:10.13474/j.cnki.11-2246.2022.0059

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At present, it is one of the common operation methods of offshore engineering exploration using the anchored hull to carry out exploration operation. Aiming at the current situation that the application research on the stability analysis of anchored hull is relatively less, this paper uses GNSS attitude determination method to study the stability of the ship under anchoring state, and studies the plane position and height of the hull in different sea conditions (Level 2, 3, 4). The stability of the hull is evaluated comprehensively, which has certain practical value in judging whether the stability of the hull is suitable for offshore engineering exploration and whether the drilling rig can be installed.

Multi-strategy chinese address matching method

PENG Yulong, HU Shunshi, WU Tao

2022, 0(2):  145-148.  doi:10.13474/j.cnki.11-2246.2022.0060

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Address matching is a crucial link in geocoding and is one of the key technologies to realize data spatialization. Aiming at the problem that the matching rate,accuracy and time cost of the current Chinese address matching method cannot be taken into account, this study proposes a multi-strategy Chinese address matching method. The main idea is to build a lightweight dictionary for Chinese address segmentation and a multi-tree to store the address data after creating words participle. In the matching process, the fuzzy matching and hierarchical backtracking matching are combined to complete the address matching. Based on real data, this paper conducts experiments, and the results show that this method is more balanced than other matching methods in matching rate, accuracy rate and time cost.

Detection of differences and influencing factors of county economic in Henan province from 2005 to 2019

CHANG Yinghui, ZHU Qingwei, SU Deguo, SUN Lijian

2022, 0(2):  149-153.  doi:10.13474/j.cnki.11-2246.2022.0061

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This paper uses the Nich index to study the differences in the development rate of county economy in Henan province from 2005 to 2019, uses the cold and hot spot model to analyze the evolution of the spatio-temporal pattern of economic development, and uses the geographical detector to analyze the leading influencing factors of the county economic difference in Henan. The results show that the vitality of county economic development in Henan is basically consistent with the local economic development level in spatial distribution, the county economic differences show a trend of polarization, and developed cities have a radiating driving effect on the surrounding counties.The pattern of cold and hot spots of the county economy development in Henan is relatively stable, and the hot spots are mainly distributed in the northwest with Zhengzhou and Jiyuan as the core. The main factors affecting the county economy in Henan are the added value of secondary industry, economic base, per capita disposable income and the general public budget expenditure, and the interaction between factors is enhanced by two factors.

Evaluation and decision analysis of regional land irrigation environment

GAO Chao, GAO Yongming, GANG Hongjun, WANG Chengjia, WANG Lei

2022, 0(2):  154-158,163.  doi:10.13474/j.cnki.11-2246.2022.0062

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Land resources are the material basis for people's survival and development. Land irrigation environment is an important content of land resources surveys, and the spatial configuration of key infrastructure motorized wells has important practical significance for agricultural production. This paper takes Yongledian, Tongzhou, Beijing as the research area, and based on the multi-source spatial data of the land and resources survey, proposes a method for quantitative evaluation and optimization decision-making of the existing land irrigation environment. The results show that the configuration of existing organic wells in the study area needs further improvement. The 183 updated motorized wells given by the optimization plan are reasonably allocated in the set units, which can meet the land irrigation needs of local farmers and provide for the updated configuration of motorized wells in the land irrigation environment.

Analysis of factors affecting the extraction of relief amplitude by mean change- point method:taking the Yellow River Basin in Shanxi as an example

NING Ting, CUI Wei, MA Xiaoyong

2022, 0(2):  159-163.  doi:10.13474/j.cnki.11-2246.2022.0063

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Relief amplitude factor plays an important role in macro-scale ecological assessments. The mean change-point method is the mainstream method for determining the best fit window (BFW) of relief amplitude, but its influencing factors are still lacking in research. Taking the Yellow River Basin in Shanxi as an example, this paper extracts its relief amplitude based on DEM data and the mean change-point method, and explores the effects of three factors, namely number of analysis window samples, DEM resolution and landform type, respectively. The results show that: ① Number of analysis window samples has an important effect on the value of the best fit window. As the number of samples increases, the area of the best fit window where the change-point located also increases. ② DEM resolution has a certain effect on the best fit window value. When the analysis window area has the same value range, the best fit window area calculated based on 30 m ASTER GDEM is always smaller than the best fit window area based on 90 m SRTM DEM. ③ Landform type has little effect on the value of the best fit window. When the number of analysis window samples is the same, the best fit window for different landform areas and the entire study area is always same or similar. In short, number of analysis window samples is the key influencing factor.

Discussion on GIS experimental hybrid teaching method for surveying and mapping engineering

ZHANG Longqi, GUO Yunkai, ZHANG Yunfei

2022, 0(2):  164-167,173.  doi:10.13474/j.cnki.11-2246.2022.0064

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This paper introduces a hybrid experimental teaching scheme of “GIS principle and application experiment” course for surveying and mapping engineering. The teaching content is firstly reorganized according to the main employment direction of graduates, the needs of the corresponding market and the relevant requirements of engineering education certification. Combined with the current needs of epidemic prevention and control and the characteristics of network teaching, the reform and exploration of online and offline hybrid experimental teaching methods have been carried out based on the “learning link” online teaching platform to combine in and after class and play fully to students' subjective initiative, and finally formed a fresh hybrid experimental teaching scheme. The teaching experiment showed that the scheme has significant advantages in both consolidating theory teaching and improving the practical ability, and can meet the needs of GIS talent training in various industries. It would provide the reference for the teaching of geographical information system in relevant majors．

Development and application of online course of deformation monitoring technology based on Moodle

LI Peixian, YANG Zhonghui, YAN Yueguan, YUAN Debao, ZHAO Yanling, FAN Deqin

2022, 0(2):  168-173.  doi:10.13474/j.cnki.11-2246.2022.0065

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To improve the effect of online teaching and adapt to the needs of online teaching during the epidemic, a widely adapted online course resource library for deformation monitoring has been established based on the Moodle, which is an open-source online education platform. The paper describes the process, methods and issues that should be paid attention to in the construction of Moodle online courses briefly. Then we focuse on the development steps of the test question library, case library and online and offline communication modules. Aiming at the OBE teaching concept of double first-class construction and engineering certification, the basic principles, problems and graduation requirements evaluation methods that should be followed in the teaching construction of deformation monitoring technology network courses are discussed. Research result has shown that the application of online courses promotes the sharing of teaching resources and exchanges between teachers and students, reduces the labor intensity of teachers in class, and enhances students' enthusiasm for learning. The reasonable formulation of course objectives, effective evaluation, and continuous improvement of the achievement of graduation requirements are of positive significance for improving the teaching effect of the deformation monitoring technology course.

Research and practice of digital image processing hybrid teaching

JIA Yonghong

2022, 0(2):  174-176.  doi:10.13474/j.cnki.11-2246.2022.0066

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The design of teaching activities, the implementation of teaching and the evaluation of academic performance of the mixed teaching mode of digital image processing is discussed in this paper.The teaching practice shows that the mixed teaching mode of online and offline digital image processing innovates the teaching mode, strengthens the communication between teachers and students, highlights the centrality of students and the guiding role of teachers， and can teach students in accordance with their aptitude.It can not only improve students’ self-learning ability, but also improve the quality and efficiency of teaching, and overcome the impact of reducing teaching hours, and play a better leading role in the double “first-class” construction.