Table of Content

25 November 2021, Volume 0 Issue 11

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Research on temporal and spatial variation of fractional vegetation cover in Golden Camellia National Nature Reserve using linear fusion method

CHEN Wei, WANG Zhe, ZHAO Haimeng, LI Lihe, ZHANG Xuepeng, LI Guangchao

2021, 0(11):  1-6.  doi:10.13474/j.cnki.11-2246.2021.328

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When using high spatial resolution images to study FVC changes in a small area, due to the influence of sensors, imaging conditions, and cloud cover, continuous long time series image data is missing or unavailable. At the same time, the low time resolution of the image also greatly limits the study of continuous time series FVC changes in small areas. In response to this problem, this paper uses a linear fusion method to fuse continuous long time series FVC images, which solves the problem of the lack of continuous time series data and low time resolution of Landsat images due to cloud cover and banding when studying FVC spatiotemporal changes. And using Sen+Mann-Kendall trend analysis, it is found that the FVC of the Golden Camellia Natural Reserve showes an overall increase from 2000 to 2016. The area with a significant increase in FVC accounted for about 37.32%, and the area with no significant increase accounted for about 58.56%. The FVC image obtained by the linear fusion method can finely characterize the changes of the surface FVC, and better solve the limitation of the lack of continuous time series data of the high spatial resolution FVC image, which is conducive to the study of long time series spatiotemporal changes of FVC in small areas.

Evaluation of ecological environment quality of Golden Camellia National Nature Reserve from 2005 to 2019

GUO Jinyuan, ZHAO Haimeng, HAN Xuerong, LI Jiali, LI Lihe, YANG Haiju, YANG Bin

2021, 0(11):  7-11.  doi:10.13474/j.cnki.11-2246.2021.329

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Ecological evaluation is of great significance for the scientific and effective management and sustainable development of nature reserves. Based on Landsat images with a spatial resolution of 30 meters and GLASS data with a time resolution of 8 days, this paper uses ecological quality index (EQI), which is calculated as weighted ecological function index, ecological stability index, and ecological stress index, to evaluate the ecological environment quality of Fangcheng Golden Camellia National Nature Reserve in Guangxi from 2005 to 2019. The results show that the overall ecological quality of the reserve is good. The quality of the ecological environment is continuously improving during 2005-2019. Areas with poor and low ecological grades are mainly distributed around the protected area, and their proportion has increased year by year since 2014. This is closely related to the human disturbance activities of the surrounding residents.

New ecological index evaluation based on remote sensing data

SUN Caixia, YANG Fan, HU Jin

2021, 0(11):  12-15,53.  doi:10.13474/j.cnki.11-2246.2021.330

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According to the problems of difficulty in obtaining eco-environmental assessment index and different evaluation criteria, a new ecological index (NEI) is put forward. The index synthetically reflects the regional eco-environment status by biological richness index, vegetation coverage index, dryness index, wetness index and air quality index, and uses principal component analysis to objectively determine the weight. The results indicate that NEI's index selection and results have strong comparability with EI in "Technical Criterion for Ecosystem Status Evaluation". However, the NEI's index has the characteristics of quantification, visualization and real-time results, and has a good application prospect for evaluating the regional ecological environment.

Assessment of the urban ecological status based on multi-source remote sensing data

WANG Yuan, DU Mingyi, YANG Liuzhong, CAI Guoyin, ZHANG Ning

2021, 0(11):  16-20.  doi:10.13474/j.cnki.11-2246.2021.331

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Urban ecological environment monitoring has the characteristics of multiple data sources, complex monitoring elements, and diverse service objects. How to integrate available data resources for comprehensive monitoring of urban ecology has become a research focus. This article attempts to use high-resolution remote sensing images combined with remote sensing products such as fine classified global land cover and urban boundaries. Based on the existing remote sensing ecological index (RSEI), combined with the black and odorous water index, an integrated remote sensing monitoring model suitable for comprehensive assessment of urban ecological conditions is constructed to realize the comprehensive monitoring of the state of the urban ecological environment. This method can more accurately and objectively reflect the quality of the city's ecological environment, theoretically supplements the urban ecological environment monitoring method based on remote sensing data, and provides technical support for the information construction of urban and rural ecological environment monitoring.

Remote sensing monitoring evaluation of ecological environment in debris flow disaster prone area

WANG Xuqing, SHI Yanxin, PAN Jianyong, GUO Yingping, GAO Youlong, WEI Jianpeng

2021, 0(11):  21-24.  doi:10.13474/j.cnki.11-2246.2021.332

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Debris flow disaster has a strong destructive effect on ecological environment factors such as vegetation, soil and water in the basin,then how to quickly and effectively monitor the changes of ecological environment in the disaster-affected area is of great significance for disaster prevention and mitigation. In this paper, we take the debris flow disasters in Bailong River as the research object, extract the information of ecological factors from multi-stage remote sensing images, and construct the ecological quality evaluation model. The results show that the remote sensing monitoring based on time series images can effectively describe the regional ecological change before and after disasters, which has practical application value for the ecological monitoring and restoration of geological disaster areas.

Scale effect analysis of carbon emission simulation based on NPP-VIIRS images in Guangdong province

WANG Yanjun, WANG Mengjie, LI Shaochun, LIN Yunhao

2021, 0(11):  25-30.  doi:10.13474/j.cnki.11-2246.2021.333

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Carbon emission estimation is one of the most important fields of energy conservation and global climate change research. NPP-VIIRS night light image can reflect the intensity of human activities and is widely used in the spatial estimation and analysis of carbon emission. This paper constructs and compares the fitting models of energy consumption and carbon emissions estimation in Guangdong province based on NPP-VIIRS night light images in 2015, and focused on the scale effect of NPP-VIIRS images, and discussed the accuracy of model results at 500 m, 1000 m, 1500 m and 2000 m resolution. The results showed that:①The quadratic polynomial fitting model is a better method for carbon emission estimation, and the fitting results of 21 cities in Guangdong province are quite different. ②The root mean square error of Guangdong province carbon emission estimation results from NPP-VIIRS nighttime light image with 1000 m resolution is the smallest, and the absolute error of 2000 m resolution is smaller, and the model operation efficiency is improved by scaling up. ③Estimation results of carbon emissions show fluctuation from night light images with different spatial resolutions increasing continuously from 500 m to 2000 m at an interval of 100 m and tend to balance at the resolution of 1000 m. This paper analyzes the carbon emission estimation model of Guangdong province based on NPP-VIIRS night light images, and reveals the scale effect rules of different spatial resolution images, which can provide a reference for spatial scale optimization and result refinement of carbon emission estimation of night light images.

Glacier deformation inversion before disaster using SBAS-InSAR technology in Sedongpu basin along the Yarlung Zangbo River

ZHU Bangyan, REN Zhizhong, ZHANG Qi, LI Yun, WANG Xiao

2021, 0(11):  31-35.  doi:10.13474/j.cnki.11-2246.2021.334

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Glacier deformation in Sedongpu basin from April 2018 to October 2018 is retrieved by SBAS-InSAR technology using 30 sentinel-1 SAR images. The inversion accuracy is verified with statistics in bedrock area and the RMSE is 9 mm. This shows that SBAS-InSAR technology has good reliability in glacier deformation monitoring.The sensibility of ascending and descending orbit data for deformation monitoring in different aspects is analyzed. Spatial distribution and temporal evolution characteristics of glacier deformation before the occurrence of glacier debris flow are analyzed. The main glacier movement is in the central axis along intersection of east and west aspects.The results shows that the average deformation of glacier area is -34.8 mm. On the typical section line, with the altitude decreasing, the glacier deformation decreases slowly at first, then increases rapidly, and then decreases slowly. Before the occurrence of glacial debris flow disaster, the glacier deformation had an obvious accelerating trend,which can provide scientific data support for early identification of glacier disaster.

Yanqi basin soil moisture spatial and temporal distribution characteristics in Xinjiang

Dilihumaer Ahanmujiang, Yusufujiang Rusuli

2021, 0(11):  36-41.  doi:10.13474/j.cnki.11-2246.2021.335

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This study takes Xinjiang Yanqi basin as the research area,using field data and Landsat 8 OLI data to obtain soil vegetation index MSAVI and land surface temperature (Ts) to construct Ts-MSAVI feature space combined with dry and wet space equations. The temperature vegetation drought index (TVDIm) is calculated using this feature space, retrieve soil moisture in September, October, and November, analyzes the temporal and spatial distribution characteristics of soil moisture. The result shows that:① The TVDI retrieved from remote sensing images is significantly correlated with soil moisture (a=0.05). TVDIm has the highest correlation with 10~20 cm soil moisture (R=0.588) in different soil layer. ② Humidity level in Yanqi basin is featured with semi-arid(0.60.8). Spatial distribution of soil moisture denotes that the arid area is mainly distributed the southern side of the Yanqi basin, the western and northern part of the Yanqi basin is arid, and the humid area is the middle of the Yanqi basin. For this area, the lake side wetland and the small lake of Bosten Lake have the highest soil moisture, and the sandy area of the southern Bosten Lake has the lowest soil moisture.③ The wetland showes the lowest TVDIm value in October. The TVDIm value of the sandy land is the highest in September. The TVDI model has been applied in Yanqi basin to obtain good results, which can be used to accurately estimate soil moisture. The research results can provide important parameters for the ecological environment and water resources of Yanqi basin.

Reconstruction of reservoir capacity curve by coupling multi-source time-phase remote sensing image data

WANG Jinxin, SANG Xuefeng, CHANG Jiaxuan, PEI Liang, ZHAO Tianwei, BAO Kangni

2021, 0(11):  42-47.  doi:10.13474/j.cnki.11-2246.2021.336

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Remote sensing technology brings new ideas for reservoir capacity curve reconstruction, but there are still problems such as the difficulty of direct application of multi-source remote sensing image data and low efficiency of reservoir batch area extraction, which make it difficult to form a systematic and process-oriented method for wide application. In view of this, this paper proposes a reservoir capacity curve reconstruction method coupled with multi-source time-phase remote sensing image data. The water level-volume relationship curve of Shenzhen Jingxin reservoir is reconstructed by this method. The experiments prove that the deviation rate of the reconstructed reservoir capacity curve is about 4.23%~11.5% in the range of normal water level, which can provide reference for the scheduling management of Jingxin reservoir. At the same time, it has reference significance for reservoirs in the country where the reservoir capacity curve cannot be reconstructed in time.

Line target extraction of synthetic aperture sonar image based on Hough line detection and region growing

OUYANG Quanping, ZHOU Li, WANG Sheng, SONG Shilin, LU Bin, FENG Junjun

2021, 0(11):  48-53.  doi:10.13474/j.cnki.11-2246.2021.337

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A line target extraction algorithm based on Hough line detection and region growing is proposed to solve the problem of small width (diameter) of line target and serious influence of speckle noise on the image in the process of synthetic aperture sonar image line target extraction. Firstly, Otsu algorithm is used to calculate the growth termination threshold of the region and preliminarily suppress the noise; Secondly, based on the Hough line roughness detection of the image, the detection results are divided unevenly, and then the fine detection is carried out to obtain the seed points growing in the region; Finally, region growing is used to restore the line target. Experimental results show that the algorithm can accurately extract line targets, and the number of seed points selected by the algorithm is increased by 5.37 times compared with the traditional region growth, and the line target extraction results have better continuity and integrity.

Application of improved D-LinkNet model in cloud detection of domestic satellite image

LIU Guangjin, WANG Guanghui, BI Weihua, LIU Huijie, YANG Huachao

2021, 0(11):  54-58,64.  doi:10.13474/j.cnki.11-2246.2021.338

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Due to the lack of band of most domestic satellites, cloud detection is difficult using traditional methods. In this paper, a cloud detection algorithm based on improved D-LinkNet model is proposed and applied to domestic satellite remote sensing image cloud detection. Firstly, the binary image label is generated by using ResNeSt50-Block with channel attention mechanism. Secondly, the encoder of D-LinkNet50 is improved by using ResNeSt50-Block with channel attention mechanism to replace the original ResNet50-Block. And then the loss function is weighted, and it is found that the cross-entropy loss is the only loss function with higher precision. Finally, the conditional random field (CRF) is used to post-process the predicted results. The experimental results show that the MIoU and precision of the improved D-LinkNet model are improved by 1.93% and 2.45% respectively, and the cloud edge information is kept well. It can be used in cloud detection, and the effect is obviously higher than that of the original D-LinkNet model.

Research on remote sensing image ship detection and identification based on Faster R-CNN

ZHAO Zhenqiang, HE Shuiyuan, LIANG Yongzhi

2021, 0(11):  59-64.  doi:10.13474/j.cnki.11-2246.2021.339

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With the development of remote sensing, remote sensing big data is playing an increasingly important role in people's lives, but due to the large amount of remote sensing data, data processing is difficult. Machine learning technology with the development of today's hardware technology, makes its own computational processing capacity has been greatly improved, and thus is widely used in various fields. Due to the increase in data and computer capabilities, deep learning is now widely used in remote sensing, while it has also been proved to be an extremely powerful tool in other fields. Combining the characteristics of large remote sensing data, this paper uses the Faster R-CNN method to achieve fast detection of ships and achieves a high detection rate.

Research and implementation of remote sensing intelligent vision platform based on deep learning PaddlePaddle framework

SUN Yumei, LIU Yuhao, BIAN Zhanxin, SUN Liang, CHEN Jingzhou

2021, 0(11):  65-69,75.  doi:10.13474/j.cnki.11-2246.2021.340

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The remote sensing intelligent vision platform supported by Baidu deep learning PaddlePaddle framework is researched and implemented. It can use deep learning technology to realize intelligent modeling, training and interpretation of remote sensing images.Through the deep analysis of the deep learning algorithm model DeepLabV3+, U²-Net and RetionaNet of PaddleSeg image segmentation model library, the remote sensing intelligent vision platform is developed and designed, which realizes the professional functions of parcel segmentation, change detection and oblique frame detection of remote sensing image. The results show that:the total area of the spot extracted by the remote sensing intelligent vision platform is 80% of the visual interpretation, the proportion of effective spot is 76%, and the proportion of error spot is 18%, which realizes the fast and effective remote sensing image intelligent processing.

Frequent trajectory recognition of taxi trajectory data

WU Qunyong, WANG Xiangjian

2021, 0(11):  70-75.  doi:10.13474/j.cnki.11-2246.2021.341

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In order to identify the frequent paths in urban traffic, this paper proposes a method of frequent trajectory identification for taxi trajectory data. The method firstly compresses the trajectory data to reduce the computational complexity. Then calculates the trajectory similarity measure based on longest common subsequence and dynamic time warping algorithm, and generates a distance matrix by using the calculated similarity between trajectories. Finally, the generated distance matrix is clustered with HDBSCAN algorithm to get frequent trajectories. Two areas in Xiamen Island are selected for experimental analysis. The results show that the proposed method can identify the frequent trajectories in the trajectory data set and obtain the frequent paths between urban areas, which is helpful for road planning, path optimization and recommendation, traffic management and other applications.

Rock surface extraction method with multi-semantic of multi-source data

ZHANG Rongchun, YI Xuefeng, LI Hao, YUE Jianping, LU Guanming, ZHANG Xuedong

2021, 0(11):  76-80,105.  doi:10.13474/j.cnki.11-2246.2021.342

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The extraction of complex rock surface in the rock mass environment is the key to the stability analysis of rock mass engineering such as slopes and tunnels. The texture and shape of the rock surface are complicated and irregular, which makes it difficult to extract. This paper proposes a mapping relationship construction method for TLS point cloud and digital images. Multi-geological semantics features are first integrated for homogeneous units extraction, and then homogeneous units clustering based on geological semantics is proceeded. The experimental results show that the method in this paper can achieve rock surface extraction completely and accurately.

Detection of meso-scale structure characteristics of the central plains urban agglomeration based on the network built from toponym co-occurrences in the news

YUE Hanqiu, WANG Qi, LU Di, LI Yuliang

2021, 0(11):  81-86.  doi:10.13474/j.cnki.11-2246.2021.343

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In this study, the central plains urban agglomeration (CPUA) is selected as the study area to construct a city network using toponym co-occurrence in the news. Furthermore, a method framework is proposed to detect community structure and core-peripheral structure of the resultant network. The following findings are obtained:① The CPUA are divided into 5 communities and the provincial boundary has played a major role in hindering the interaction between cities in virtual cyberspace. ② In the core-periphery structure composed of cities in Henan province, the identified core cities are distributed in an oblique "L" shape around Zhengzhou.③The central position of Zhengzhou is more prominent, while Luoyang's sub-center status is not obvious, and the overall multi-center level of CPUA is relatively low. Based on the above findings, suggestions are given from regional planning and urban role positioning for the integration of cities within the CPUA.

Evaluation of intentional reserved land resources under urban spatial expansion and optimization: a case study of Shima River Basin in Dongguan

CHEN Minghui, HUANG Yan, LI Ganbo

2021, 0(11):  87-91.  doi:10.13474/j.cnki.11-2246.2021.344

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Under the background of regional integration,the evaluation of the land resources to be reserved is beneficial to the intensive and efficient land utilization,maximizing the land economical value,and relieving the financial pressure caused by river basin regulation. In this paper,the potential land available for development in Shima River Basin of Dongguan is investigated and evaluated. Firstly,the screening index system of land is established,and the potential plot for reservation is identified. Then,the planning conditions,reserve potential and economic benefits of the intentional land are evaluated. Finally,some proposals for land reserve is proposed. This study explores and establishes a complete land resources evaluation system of "screening-evaluation-reserve planning",which provides references for the integrated development of river basin and the formulation of land reserve plan.

Multi-spectral remote sensing inversion of soil heavy metal content using random forest regression model

WANG Tengjun, FANG Ke, YANG Yun, ZHENG Xiangdong

2021, 0(11):  92-95.  doi:10.13474/j.cnki.11-2246.2021.345

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This paper takes Daxigou mining area in Zhashui county, Shaanxi province as the research area. By collecting soil samples on the spot, combining with radiation luminance value and spectral derivative index extracted from Landsat 8 multi-spectral remote sensing images, and three topographic factors extracted from ASTER GDEM, modeling factors are determined through correlation analysis. The random forest regression model of arsenic, copper and lead is established by K-fold cross validation. The experimental results show that the prediction accuracy of the established model is better than that of the multiple linear regression model and the CART model, which verifies that the random forest regression model is suitable for the heavy metal content inversion in the case of small samples. Through the field investigation, the spatial inversion results are in good agreement with the actual situation, which proves the accuracy of the random forest regression model based on multi-spectral remote sensing in the soil heavy metal inversion of mining area.

Quarry recognition based on attention mechanism from high-resolution remote sensing imagery

MA Linfei, NI Huan, ZHOU Zihan

2021, 0(11):  96-100.  doi:10.13474/j.cnki.11-2246.2021.346

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Quarrying industry plays a positive rule for national economy. At the same time, it arouses hidden danger to ecology, environment, and human security. Currently, quarry ecological restoration has become an important issue for ecological civilization construction. The precondition to solve this problem is quarry recognition and boundary determination. High-resolution remote sensing earth observation and deep learning techniques provide an efficient way for this task. In this paper, we design an attention pyramid and a detail enhancement module based on residual network to recognize quarry in UAV high-resolution images, using only a small number of parameters and extremely low computational complexity. The experiments employ the UAV images and human annotated ground truths in Nanan city of Fujian province as the data source. Then, we construct a dataset for training convolutional neural networks, and validate the performance of our proposed method. The experimental results show that our proposed method is with high inference speed and accuracy, and can be used to provide supporting material to quarry ecological restoration.

Ground error analysis of DTM extracted by airborne LiDAR in subtropical forest

WU Xiaotian, LI Huizhu, RUAN Fang, FENG Haoning, CHEN Mingqiang, WANG Changwei, WANG Bin

2021, 0(11):  101-105.  doi:10.13474/j.cnki.11-2246.2021.347

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LiDAR is one of the main measurement techniques used nowadays for the derivation of DTM. Ground errors have a significant influence on the accuracy of DTM generated by LiDAR. In particular, due to the complex under-forest vegetation structure of the subtropical forest, the DTM will be more complicated. Therefore, it is necessary to analyze the influence of ground errors on the under forest DTM generated by LiDAR. Taking Zengcheng Teaching and Research Base of South China Agricultural University as the study area, the paper discusses the influence of ground error on the accuracy of under forest DTM generated by airborne LiDAR data from forest canopy density and slope. The results show that the elevation RMSE will increase with canopy closure increasing while the elevation RMSE does not change significantly with the slope rising. However, the slope of 15 degrees is the watershed of the elevation RMSE. When the slope exceeds to 15 degrees, the elevation RMSE will rise rapidly. In general, the influence of canopy closure is more apparent on the accuracy of DTM generated by LiDAR.

Habitat quality assessment of road area of Huma-Shiba station highway in Heilongjiang province

SHI Zhenwu, LI Chi

2021, 0(11):  106-109,114.  doi:10.13474/j.cnki.11-2246.2021.348

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The construction of green highway also inevitably affects the habitat quality of road area, therefore, 30 m global land cover data of 2020 edition, Landsat 8 satellite image, ASTER GDEM with 30 m resolution is selected and operated in collaboration with ENVI 5.3 and ArcGIS 10.2 platforms, the influence on the habitat quality is analyzed from the three perspectives of the habitat suitability of soil erosion degree and the change of vegetation coverage before and after highway construction. The results prove that The vegetation coverage over 75% of the road area decreases from 2 673.8 km² to 2 389.82 km² before and after highway construction, areas with vegetation coverage of 45%~75% decreases from 997.31 km² to 767.19 km²; The erosion degree of soil is mainly moderate erosion and high erosion, moderate erosion and high erosion cover a total area of 3 927.99 km², accounting for 79.04% in total; Habitat suitability is highest in and around Huma River basin on the left side of the highway, and the forest area on the right side of the highway is followed by patches.

Application of deep learning in the unified verification and registration of natural resources rights of Haizhu National Wetland Park

CHENG Xiaohui, LI Changhui, OU Jiabin, LIU Yeguang

2021, 0(11):  110-114.  doi:10.13474/j.cnki.11-2246.2021.349

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To solve the problem that a single-source observation is hard to balance between the spatial and spectral properties of natural resources, this paper proposes a data-fusing classification method based on deep learning. Using limited samples of multi-source data, the method accomplishes the detailed classification of vegetation coverage areas, completes the extraction of natural resource types and the investigation of vegetation quantity in a pilot area, the Haizhu National Wetland Park in Guangdong province. The results show that this method can effectively extract natural resource types and classify vegetation. Its accuracy of forest number detection is better than 87%, which significantly improves the fineness of vegetation classification, and explores the way of detailed investigation of natural resources for ownership confirmation and registration.

Construction and application of city-level real 3D city: a case study of Linyi real 3D city

CAI Zhenfeng, PENG Bin, JI Xia, JI Peng

2021, 0(11):  115-119,144.  doi:10.13474/j.cnki.11-2246.2021.350

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Real 3D cities have become 3D space supporting infrastructure and an important part of the construction of new infrastructure. The construction of real 3D cities is the basis for the comprehensive construction of real 3D China. This paper combines the construction of real 3D Linyi, and proposes the deep fusion technology of laser point cloud and oblique photography multi-source data with low overlap to quickly construct the technical process and system of city-level real 3D city. The data results have been deeply applied in large-scale topographic map surveying and mapping, the construction of the spatio-temporal information cloud platform and the management of 3D real estate registration, which is of practical significance for promoting the construction and application of city-level real 3D cities.

The rapid identification of ground features after the earthquake disaster in Qinghai province

HAN Jianping

2021, 0(11):  120-123.  doi:10.13474/j.cnki.11-2246.2021.351

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Every minute of post-earthquake rescue is precious. Effective use of post-disaster data and accurate assessment of rescue routes can effectively avoid further damage caused by the earthquake. The earthquake did not stop at once, and the aftershocks after the disaster also threaten the lives and property safety of the people in the disaster area. Therefore, formulating a follow-up sustainable rescue plan based on the geology of the disaster area and the distribution of residents is the top priority of post-disaster rescue, which not only enables the rescue to be carried out steadily, but also allows for further planning of residential resettlement. This paper proposes an adaptive method of ground object segmentation algorithm by comparing neural network and traditional machine learning methods. According to the complexity of aerial imagery, neural network and traditional algorithm are combined to compare the identified ground objects with the original measurement data. Differential changes can be used to judge road distortions and geological changes after the disaster and provide an accurate scientific basis for rescue work.

Land surface temperature inversion based on Landsat 7 and GF-1 WFV images

FU Baoling, JU Feng, ZHAO Weizhong, XU Xing

2021, 0(11):  124-127,135.  doi:10.13474/j.cnki.11-2246.2021.352

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Land surface temperature (LST) is the focus of geographical research and plays an important role in the earth-atmosphere system. However, the domestic high-resolution image lacks thermal infrared band, and the image resolution of thermal infrared band is relatively low. Based on this, a low resolution image downscaling method is proposed to retrieve high-resolution land surface temperature. Firstly, the surface temperature of typical objects is extracted from the thermal infrared band of Landsat 7 image. After preprocessing the GF-1 WFV image, least squares under the full constrained method is used to decompose the high-resolution image into mixed pixels. According to the average temperature model, the surface temperature of the high-resolution image is obtained. The root mean square error (RMSE) is 1.40℃, the mean absolute error (MAE) is 0.44℃, and the precision is verified with Landsat 7 image.

An ground-like flight method of UAV based on monocular vision

FU Zhenhua, DENG Ruizhi

2021, 0(11):  128-130.  doi:10.13474/j.cnki.11-2246.2021.353

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Ground imitation flight is a very important issue in aerial survey of unmanned aerial vehicles. Whether the aircraft can maintain a stable altitude relative to the ground which is directly related to the safety and data quality of unmanned aerial vehicles in complex terrain areas. Therefore, a monocular vision based on UAV aerial height estimation method is proposed in this paper. The optical flow method is used to track and analyze the real-time video obtained by UAV, and the motion information is extracted to estimate the real-time aerial height. The experimental results show that this method can estimate the real-time altitude of UAV quickly and accurately, and realize the automatic ground-mimicking flight without the information of surface altitude.

Evaluation of the habitability area of 9 priority protected species in Yunnan province

ZHANG Yan, WEI Xiaoyan, SHEN Liao, ZHOU Junsong, ZHU Daming

2021, 0(11):  131-135.  doi:10.13474/j.cnki.11-2246.2021.354

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In view of land use changes in Yunnan province, natural environment damages, which leads to extremely endangered or even extinction of many species and serious destruction of biodiversity.In this paper, MaxEnt model is used for environmental suitability analysis.Based on the carrying capacity of resources and environment and the suitability of territorial spatial development, we selecte 9 priority protected species with Yunnan characteristics to predict the optimal living environment of each species. The study finds that the extant area of the nine preferentially protected species in Yunnan province total 2100 square kilometers, and MaxEnt model is predicted to reach 54 500 square kilometers, which is 25 times of the extant region.

Quality assessment for land cover classification products based on fuzzy-AHP synthesis model

LÜ Linbing, CHEN Haipeng, CHEN Yuheng

2021, 0(11):  136-139,160.  doi:10.13474/j.cnki.11-2246.2021.355

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This paper proposes a fuzzy-AHP synthesis model to assess the quality of land cover classification products, based on the current qualifications of inspection and acceptance as well the characteristics of the inspection process of this type of results. The model is practiced on a data set that is the inspection results from 27 surveying areas in northern China. By comparing the results with the results from minimum and weighted average methods, this study pays attention on giving the analysing of the reasonability and feasibility of this model on practical uses and to provide a technical reference for quality evaluation of the new-type of fundamental surveying and mapping products.

Lightweight integrated presentation and thematic application of geological big data

YU Guangting, LIU Tongwen, CAO Fawei, XU Jinda, XUE Liming, HU Ziyuan, LIN Yongcheng

2021, 0(11):  140-144.  doi:10.13474/j.cnki.11-2246.2021.356

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Geological big data is the foundation of wisdom geological mining engineering construction, geological work for a long time to form the massive amounts of multi-source heterogeneous data, how to effectively integrate geological big data integration, and applications, has become a key link in the process of mining engineering construction wisdom, this paper respectively in the geological data of the main problems in the integration and solution, the design of large data integration platform and the project application several aspects elaborated. This paper constructs a multi-dimensional dynamic visualization platform, draws the virtual simulated geographical scene in the Web page, superposes the rich geospatial data, carries on the visualization display to the multi-dimensional data, uses the B/S structure, it has realized the non-plug-in, the lightweight Web visualization page display, and has realized the scene display, the geographic data processing, the three-dimensional analysis and so on functions.

Comprehensive application of surveying and mapping geographic information technology in cultural relic protection division of Shaanxi province

NAN Junxiang, LIANG Shuang, LI Haiquan, LI Jizhen, ZHENG Zhicheng

2021, 0(11):  145-150.  doi:10.13474/j.cnki.11-2246.2021.357

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In recent years, with the state's high attention to cultural heritage and the rapid expansion of cities, cultural relics protection and management planning can not be connected with urban planning, which is not conducive to the development of cultural relics protection and management. Based on the project of cultural relic protection division in Shaanxi province, the protection area of Yanchang Temple Pagoda in Tongchuan city is selected as the experimental area. Combined with modern surveying and mapping geographic information technology such as UAV aerial survey, three-dimensional laser scanning and three-dimensional geographic information system, this paper discusses the application of integrated modern geographic information technology in the accurate delimitation of cultural relics "two lines" Use and advantage. Through the research and demonstration of this paper, it provides a new idea for improving the authority of cultural relics protection planning and improving the level of cultural relics management. Its technical methods and means can be popularized and applied in similar projects.

Construction of new high freshness electronic map platform based on cloud computing

CHEN Xiaoyu, ZHANG Lu, CHEN Huixian, FU Yu, SUN Yonglie

2021, 0(11):  151-154.  doi:10.13474/j.cnki.11-2246.2021.358

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In the new era of rapid development of electronic technology, electronic map can provide various LBS services for users of car navigation, mobile phones, PAD, and the Internet.Aiming at the problems of low update frequency, slow processing speed, and poor current status of existing electronic map production platforms,this article uses new technologies such as big data mining, cloud computing and artificial intelligence, through automatic recognition and automatic editing capabilities to research the online rapid update technology of electronic maps and the integrated process from collection, editing to production. A new high-fresh electronic map platform based on cloud computing is built, the platform accomplishes the online incremental update of electronic map road information and points of interest, and greatly improves the production capacity, accuracy and efficiency of electronic maps.

Research on the co-construction model of collaborative education and practice base in engineering universities under the background of new engineering

YAN Yueguan, LIU Jibo, GUO Junting, LI Jun, GUO Wei

2021, 0(11):  155-160.  doi:10.13474/j.cnki.11-2246.2021.359

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The new engineering initiative puts forward new requirements for the training of compound applied talents in engineering universities in our country, the construction of practice base and internships can effectively cultivate engineering students' ability to adapt to future social development. This article closely follows the background of the new engineering discipline and combined with the mining characteristics of author's university, it deeply analyzes the main problems and opportunities in the construction of the new engineering of surveying and mapping engineering. Through continuous deepening of university-enterprise and university-university cooperation, multiple measures have been taken to establish university-enterprise, a collaborative education model and a practical base cooperation platform with complementary advantages and shared results between university and university or university and enterprise have been established, and this paper analyzes the joint construction measures and operational effects of author's university's surveying and mapping engineering practice base, and builds up a good basis for improving the quality of student training and cultivating applied engineering talents who are suitable for future social development.

Application of automatic measurement system for pipe jacking used in curve designed axis tunnel

JIANG Liutao, WANG Huiqing, HU Qian

2021, 0(11):  161-164,168.  doi:10.13474/j.cnki.11-2246.2021.360

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In the long distance or curve pipe jacking project, timely and accurate measurement of the position and posture of the front pipe jacking machine is a key technical means to ensure the pipe jacking according to the design axis. Whether it is compared with the position and attitude measurement of the linear pipe jacking machine or compared with the shield machine, the measurement of the position and posture of the long distance and curve jacking pipe is more difficult. This paper has carried out a special research on this problem, and developed a set of curve pipe jacking automatic measurement system. It introduces the system in detail, expounds the design principle and work flow of the system, and analyzes the application data results to optimize the system accuracy.

Application of TerrainMapper airborne LiDAR in smart 3D GIS project of new energy base

SHANG Haixing, HUANG Wenyu, XIE Qian, LIU Yang, PEI Wenyue

2021, 0(11):  165-168.  doi:10.13474/j.cnki.11-2246.2021.361

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Based on Leica terrainmapper airborne lidar system, the laser point cloud and image data of new energy base are obtained, and large area DLG, DEM, DOM and other high-precision achievements are rapidly produced and visualized 3D scene is built. The 3D aided design system of new energy base is developed, which provides an efficient and high-precision BIM+ GIS system solution for smart 3D GIS project of new energy base.