Analysis of GPS Technology in Surveying and Mapping Engineering Technology

With the rapid advancement of digital and information technology,global positioning system(GPS)technology has seen increasing utilization in surveying and mapping engineering,extending its application across land,ocean,and various other domains.By analyzing the technical means of GPS in surveying and mapping engineering,understanding the characteristics and key technologies in different application environments,and exploring the application process and key technical means,accurate control can be effectively realized.Based on this,this paper mainly analyzes the specific application of GPS technology in surveying and mapping engineering technology for reference.

Exploring deep learning for landslide mapping:A comprehensive review

A detailed and accurate inventory map of landslides is crucial for quantitative hazard assessment and land planning.Traditional methods relying on change detection and object-oriented approaches have been criticized for their dependence on expert knowledge and subjective factors.Recent advancements in highresolution satellite imagery,coupled with the rapid development of artificial intelligence,particularly datadriven deep learning algorithms(DL)such as convolutional neural networks(CNN),have provided rich feature indicators for landslide mapping,overcoming previous limitations.In this review paper,77representative DL-based landslide detection methods applied in various environments over the past seven years were examined.This study analyzed the structures of different DL networks,discussed five main application scenarios,and assessed both the advancements and limitations of DL in geological hazard analysis.The results indicated that the increasing number of articles per year reflects growing interest in landslide mapping by artificial intelligence,with U-Net-based structures gaining prominence due to their flexibility in feature extraction and generalization.Finally,we explored the hindrances of DL in landslide hazard research based on the above research content.Challenges such as black-box operations and sample dependence persist,warranting further theoretical research and future application of DL in landslide detection.

Automated machine learning for rainfall-induced landslide hazard mapping in Luhe County of Guangdong Province,China

Landslide hazard mapping is essential for regional landslide hazard management.The main objective of this study is to construct a rainfall-induced landslide hazard map of Luhe County,China based on an automated machine learning framework(AutoGluon).A total of 2241 landslides were identified from satellite images before and after the rainfall event,and 10 impact factors including elevation,slope,aspect,normalized difference vegetation index(NDVI),topographic wetness index(TWI),lithology,land cover,distance to roads,distance to rivers,and rainfall were selected as indicators.The WeightedEnsemble model,which is an ensemble of 13 basic machine learning models weighted together,was used to output the landslide hazard assessment results.The results indicate that landslides mainly occurred in the central part of the study area,especially in Hetian and Shanghu.Totally 102.44 s were spent to train all the models,and the ensemble model WeightedEnsemble has an Area Under the Curve(AUC)value of92.36%in the test set.In addition,14.95%of the study area was determined to be at very high hazard,with a landslide density of 12.02 per square kilometer.This study serves as a significant reference for the prevention and mitigation of geological hazards and land use planning in Luhe County.

Exploration and Application of Ubiquitous Mapping in Engineering Practice Courses in the Intelligence Age

In the current era of digital surveying and mapping to intelligent surveying and mapping,ubiquitous surveying and mapping has brought many opportunities and challenges to college engineering course teaching.With the development of ubiquitous surveying and mapping,college engineering practice courses urgently need to respond to ubiquitous surveying and mapping.The research aims to integrate the development of ubiquitous surveying and mapping into the teaching of engineering practice courses in colleges,including promoting Android,Brower/Server(B/S),and Client/Server(C/S)to build a platform for practice courses.This also incorporates real development cases in measurement data processing such as gravity field refinement.In this way,the teaching level of engineering practice courses in colleges can be improved,and new ideas can be put forward for cultivating surveying and mapping talents in the new era in colleges.Finally,it can also provide new ideas for the organization of surveying and mapping practice courses under the background of the pandemic.

CONGRATULATIONS ON THE JOURNAL CHANGED THE NAME OF《SURVEYING AND MAPPING》AS《ENGINEERING OF SURVEYING AND MAPPING》

The journal has been changed the name of《Surveytng And Mapping》,as《Engineering of Sur-veying And Mapping》from this issue.The jounal is a quarterly publication for surveying and map-ping science and technology sponsored by Harbin Institute of Engineering(former Harbin Instituteof Surveyting and Mapping).The purpose of the journal is to present national and international newtheoris,techniques and methods,to exchange achievements and experience about the scientific re-search,teaching,technique reform and production management,to report national and internation-al development,seminar and technique lessons,and introduce famous scholars and books in survey-ing and mapping circles.The journal has enjoyed the support and favorable comment of nationalreaders of surveying and mapping circles.

Monthly composites from Sentinel-1 and Sentinel-2 images for regional major crop mapping with Google Earth Engine

Rapid and accurate access to large-scale,high-resolution crop-type distribution maps is important for agricultural management and sustainable agricultural development.Due to the limitations of remote sensing image quality and data processing capabilities,large-scale crop classification is still challenging.This study aimed to map the distribution of crops in Heilongjiang Province using Google Earth Engine(GEE)and Sentinel-1 and Sentinel-2 images.We obtained Sentinel-1 and Sentinel-2 images from all the covered study areas in the critical period for crop growth in 2018(May to September),combined monthly composite images of reflectance bands,vegetation indices and polarization bands as input features,and then performed crop classification using a Random Forest(RF)classifier.The results show that the Sentinel-1 and Sentinel-2 monthly composite images combined with the RF classifier can accurately generate the crop distribution map of the study area,and the overall accuracy(OA)reached 89.75%.Through experiments,we also found that the classification performance using time-series images is significantly better than that using single-period images.Compared with the use of traditional bands only(i.e.,the visible and near-infrared bands),the addition of shortwave infrared bands can improve the accuracy of crop classification most significantly,followed by the addition of red-edge bands.Adding common vegetation indices and Sentinel-1 data to the crop classification improved the overall classification accuracy and the OA by 0.2 and 0.6%,respectively,compared to using only the Sentinel-2 reflectance bands.The analysis of timeliness revealed that when the July image is available,the increase in the accuracy of crop classification is the highest.When the Sentinel-1 and Sentinel-2 images for May,June,and July are available,an OA greater than 80%can be achieved.The results of this study are applicable to large-scale,high-resolution crop classification and provide key technologies for remote sensing-based crop classification in small-scale agricultural areas.

Morphological MRI and T2 mapping of cartilage repair tissue after mosaicplasty with tissue-engineered cartilage in a pig model

The aim of this study was to evaluate the efficacy of mosaicplasty with tissue-engineered cartilage for the treatment of osteochondral defects in a pig model with advanced MR technique. Eight adolescent miniature pigs were used. The right knee underwent mosaicplasty with tissue-engineered cartilage for treatment of focal osteochondral defects, while the left knee was repaired via single mosaicplasty as controls. At 6, 12, 18 and 26 weeks after surgery, repair tissue was evaluated by magnetic resonance imaging （MRI） with the cartilage repair tissue （MOCART） scoring system and T2 mapping. Then, the results of MRI for 26 weeks were compared with findings of macroscopic and histologic studies. The MOCART scores showed that the repaired tissue of the tissue-engineered cartilage group was statistically better than that of controls （P 〈 0.001）. A significant correlation was found between macroscopic and MOCART scores （P 〈 0.001）. Comparable mean T2 values were found between adjacent cartilage and repair tissue in the experimental group （P 〉 0.05）. For zonal T2 value evaluation, there were no significant zonal T2 differences for repair tissue in controls （P 〉 0.05）. For the experimental group, zonal T2 variation was found in repair tissue （P 〈 0.05）. MRI, macroscopy and histology showed better repair results and bony incorporation in mosaicplasty with the tissue-engi- neered cartilage group than those of the single mosaicplasty group. Mosaicplasty with the tissue-engineered cartilage is a promising approach to repair osteochodndral defects. Morphological MRI and T2 mapping provide a non-invasive method for monitoring the maturation and integration of cartilage repair tissue in vivo.

Mapping winter rapeseed in South China using Sentinel-2 data based on a novel separability index

Large-scale crop mapping using remote sensing data is of great significance for agricultural production, food security and the sustainable development of human societies. Winter rapeseed is an important oil crop in China that is mainly distributed in the Yangtze River Valley. Traditional winter rapeseed mapping practices are insufficient since they only use the spectral characteristics during the critical phenological period of winter rapeseed, which are usually limited to a small region and cannot meet the needs of large-scale applications. In this study, a novel phenology-based winter rapeseed index(PWRI) was proposed to map winter rapeseed in the Yangtze River Valley. PWRI expands the date window for distinguishing winter rapeseed and winter wheat, and it has good separability throughout the flowering period of winter rapeseed. PWRI also improves the separability of winter rapeseed and winter wheat, which traditionally have been two easily confused winter crops. A PWRI-based method was applied to the Middle Reaches of the Yangtze River Valley to map winter rapeseed on the Google Earth Engine platform. Time series composited Sentinel-2 data were used to map winter rapeseed with 10 m resolution. The mapping achieved a good result with overall accuracy and kappa coefficients exceeding 92% and 0.85, respectively. The PWRI-based method provides a new solution for high spatial resolution winter rapeseed mapping at a large scale.

Engineering Geological Map of the Sakha(Yakutia) Republic

The Engineering Geological Map of the Sakha（Yakutia） Republic covers about 3 million kilometers which is one-fifth of the territory of Russia.The map displays ground and geocryological conditions and active faults.Seismic intensity,schemes of zoning by factors of engineering geological conditions,and the general scheme of engineering geological zoning of the Sakha（Yakutia） Republic or the SR（Y）,are shown on the inset maps.The map is required to provide information for planning,construction and exploitation of engineering structures in the SR（Y）.A distinguishing feature of the map is the indication of almost blanket distribution of the frozen ground class.Types of the frozen ground class are separated by lithology,while ground varieties are separated by temperature.Fresh and ultra-fresh suprapermafrost water is predominant within the territory.The compiled map indicates parts of the Arctic-Asian and Baikalo-Stanovoi planetary seismic belts that make engineering geological conditions more complicated.

基于ArcGIS Engine的乡镇区域洪灾应急路径规划和制图系统设计与实现

近年来,极端天气引起的洪涝灾害频繁发生,给人民生命财产安全造成巨大威胁。乡镇区域由于基础设施不够完善、应急救援信息化建设相对薄弱,是人员、经济损失最为严重的区域。针对上述问题,基于ArcGIS Engine设计并开发了乡镇区域洪灾应急路径规划和制图系统,通过设计灾区信息查询、道路更新、救援路径规划、应急地图制图和灾情统计等功能,优化救援路径规划方案,提高应急地图制图效率,为乡镇区域洪灾应急救援提供支持和服务。

Evaluation of Environmental Sound Pressure Level,Drawing of Noise-Isosonic Map Using Surfer V.19,and Prioritization of Engineering Noise Control Methods Using the Analytic Hierarchy Process(AHP):A Field Study in CGS Stations

Noise pollution is one of the most significant harmful physical factors in the industrial and occupational environments.Due to the high costs of exposure to excessive noise;continuous sound evaluation,propose and implement noise control plans in occupational environments is necessary.Thus,the present study aimed to review environmental sound measurements,drawing of noise maps,and prioritizing the engineering noise control methods using the Analytic Hierarchy Process(AHP).This study was a descriptive-analytical study that aimed to assess occupational noises and present a control plan in the City Gas Stations(CGSs)of Kerman,Iran in 2021.The present study was done in two phases.In the first phase,six CGSs were investigated to measure and evaluate the noise.In addition,the noise map of a CGS was drawn using the Surfer software.Finally,the AHP was used in the second phase of the research to prioritize the control measures.In this phase,four criteria and ten alternatives were identified.According to first phase results,the sound pressure level(SPL)of the stations varied from 76 to 98 dBA.Besides,the majority of the studied stations had a sound level higher than 85 dBA(danger zone).The second phase of the study showed that out of the four evaluated criteria,the executability criterion had the highest impact and the cost criterion had the lowest impact on the selection of control measures with a weight of 0.587 and 0.052,respectively.Based on the results of prioritization of the alternatives,using a silenced regulator(weight of 0.223)and increasing the thickness of the tube(weight of 0.023)had the highest and lowest priorities among the alternatives,respectively.The use of engineering noise control methods such as using silenced regulators was the best way to control the noises of CGSs.Additionally;it is noteworthy that AHP is a practical method for prioritizing alternatives to achieve the most accurate decision-making.The results of AHP can be of great help to health and safety experts and managers in choosing the sound engineering control measures more precisely.

基于ArcGIS Engine的使用草原方位图自动化制图系统的设计与实现

利用C#开发语言,结合ArcGIS Engine二次开发技术、开源技术,通过自动化制图技术研究,实现使用草原方位图自动化制图系统的研发。该系统利用ArcGIS Engine的功能模块及数据库等技术,结合项目需求和业务工作实际,对常规地理信息软件相关功能进行二次开发,实现对拟占用草原地块进行地理要素空间分析、属性信息交互及流程化快速制图输出等功能,解决采用常规软件在制图方面对制图人员的技术水平要求较高、工作耗时长、成果输出效率低、错误多和一致性差等难题,为相关领域的类似制图工作提供可参考的技术依据和方案支持。

基于Pro/Engineering的特征映射器的开发

针对特征映射方法的不足，提出了分层、分类实施特征映射的策略。以此为基础，运用Ｐｒｏ／Ｄｅｖｅｌｏｐ为工具，在Ｐｒｏ／Ｅｎｇｉｎｅｅｒｉｎｇ软件平台上开发一个特征映射器，该特征映射器可以实现零件的形状特征、尺寸特征、几何公差特征由设计域向制造域的映射，能够满足ＣＡＤ／ＣＡＰＰ集成的信息需求。

Gold enrichment characteristics and exploration prospects in Zambia: Based on 1∶1000000 geochemical mapping

The 1∶1000000 geochemical mapping of Zambia provides catchment sediment geochemical data for 58elements including Au from 746 sediment samples at 736 sampling sites,corresponding to a sampling density of about one site per 1000 km2.Under strict quality control using field duplicates,certified reference materials,and analytical replicate samples,the Au was determined by Inductively Coupled Plasma Mass Spectrometry(ICP-MS).The detection limit of Au was 0.20×10^(-9).The 95%range(2.5%–97.5%)of Au concentrations was from 0.24×10^(-9) to 1.36×10^(-9),and the median value was 0.40×10^(-9).The most noticeable Au distribution patterns shown on the map are mainly located between Lusaka and Ndola(Lufilian Arc Belt).In addition,several high Au value areas occurred in Mansa,Muyombe,Chipata,and Livingstone.The spatial distribution patterns of Au in tectonic units,drainage basins,and geomorphological landscapes could be related to the Lufilian Arc Belt and Bangweulu Block.The Au concentrations show metallogenic belts between Muyombe and Mbala areas,between Mansa and Ndola areas,and between Lusaka and Kasempa areas.

A Modified SOFM Method for Point Cloud Segmentation in Reverse Engineering

The purpose of reverse engineering is to convert a large point cloud into a CAD model. In reverse engineering, the key issue is segmentation, i.e. studying how to subdivide the point cloud into smaller regions, where each of them can be approximated by a single surface. Segmentation is relatively simple, if regions are bounded by sharp edges and small blends; problems arise when smoothly connected regions need to be separated. In this paper, a modified self-organizing feature map neural network （SOFM） is used to solve segmentation problem. Eight dimensional feature vectors （3-dimensional coordinates, 3-dimensional normal vectors, Gaussian curvature and mean curvature） are taken as input for SOFM. The weighted Euclidean distance measure is used to improve segmentation result. The method not only can deal with regions bounded by sharp edges, but also is very efficient to separating smoothly connected regions. The segmentation method using SOFM is robust to noise, and it operates directly on the point cloud. An examples is given to show the effect of SOFM algorithm.

Estimation of peak runoff and frequency in an ungauged stream of a forested watershed for flood hazard mapping

Kaynasli District in the western Black Sea region of Turkey has long been vulnerable to frequent flood damage due to the establishment of settlements within and around stream channels without regard to fluctuating peakstreamflow frequencies. The aim of this research was to determine the measures needed to protect the towns and villages from this type of damage. Daily total precipitation data for 1975–2010 were analysed, and rainfall-runoff models developed to estimate the potential yearly maximum discharge from each stream of sub-watersheds dominated by forests and/or agriculture. This was then calculated for different frequencies of the yearly maximum discharge. Flood analysis and mapping was modified via the one-dimensional Hydrologic Engineering CentersRiver Analysis System software to produce potential maximum discharge and geometric data for Kaynasli Creek. As the main creek of the sub-watershed, its crosssection was shown to be insufficient and incapable of containing the maximum discharge at the 100-year frequency presumed for the watershed, and subsequently was seen as having a high level of casualty risk. It was concluded that the one dimensional model could be useful, but 2D models were more suitable for these types of watersheds.

Methodology for Road Defect Detection and Administration Based on Mobile Mapping Data

A detailed inspection of roads requires highly detailed spatial data with sufficient precision to deliver an accurate geometry and to describe road defects visually.This paper presents a novel method for the detection of road defects.The input data for road defect detection included point clouds and orthomosaics gathered by mobile mapping technology.The defects were categorized in three major groups with the following geometric primitives:points,lines and polygons.The method suggests the detection of point objects from matched point clouds,panoramic images and ortho photos.Defects were mapped as point,line or polygon geometries,directly derived from orthomosaics and panoramic images.Besides the geometric position of road defects,all objects were assigned to a variety of attributes:defect type,surface material,center-of-gravity,area,length,corresponding image of the defect and degree of damage.A spatial dataset comprising defect values with a matching data type was created to perform the attribute analysis quickly and correctly.The final product is a spatial vector data set,consisting of points,lines and polygons,which contains attributes with further information and geometry.This paper demonstrates that mobile mapping suits a large-scale feature extraction of road infrastructure defects.By its simplicity and flexibility,the presented methodology allows it to be easily adapted to extract further feature types with their attributes.This makes the proposed approach a vital tool for data extraction settings with multiple mobile mapping data analysts,e.g.,offline crowdsourcing.

谷歌发布针对企业的地图服务Maps Engine Pro

据国外媒体报道，谷歌近日发布了针对企业的专业版地图引擎服务MapsEnginePro，企业可利用此项服务将各类数据（如地址、名称、办公地点、潜在客户等）从Excel工作表中导入谷歌地图中，然后这些数据会以非常直观的方式呈现出来。

基于Omap的信息化公路工程地质调绘

随着平板电脑、智能手机普及及地图查看APP功能的增强,公路工程地质调绘已由携带纸质资料、罗盘、地形图定位的传统工作方式转变为集地形、地质、设计资料于一个平板(手机)地图查看APP内的信息化调绘方式。在信息化调绘过程中收集的基础资料导入及现场记录信息的导出是关键,以Omap APP为例,给出无坐标属性的区域地质资料位图文件制作成自定义地图;具有坐标属性的地形、不良地质、建筑物、勘探布置制作成.kml文件;APP记录数据导出至CAD,GIS软件的过程及方法。经国内外多个高速公路、水电站项目使用,实践证明行之有效。

普通高校测绘工程专业程序设计类课程的教学改革探讨

随着传感器技术的飞速发展,以三维激光扫描为代表的新型批量数据采集装备的出现极大地提高了空间定位数据采集的效率。正确、高效地从采集的各类数据中提取感兴趣的信息成为新时代背景下测绘人员的必备技能。作为培养高级专门人才的摇篮,紧跟行业需求,在课程设置、教学内容与教学方法方面不断进行优化和调整是高等院校教学人员的使命。以“数据结构与测绘程序设计”课程为例,探讨了新时代背景下课程教学改革的具体措施,重点讨论了教学内容的调整与教学方法的变革两个方面,在此基础上,对多媒体课件研制过程中面临的问题及解决措施进行了分析;最后立足于课程教学改革的现有成果,对课程建设与改革的下一步工作进行了展望。