Applied Geomatics最新文献_第6页

Monitoring groundwater quality using principal component analysis 利用主成分分析监测地下水质量

IF 2.3

Applied Geomatics Pub Date : 2024-02-15 DOI: 10.1007/s12518-024-00552-z

Manaswinee Patnaik, Chhabirani Tudu, Dilip Kumar Bagal

{"title":"Monitoring groundwater quality using principal component analysis","authors":"Manaswinee Patnaik, Chhabirani Tudu, Dilip Kumar Bagal","doi":"10.1007/s12518-024-00552-z","DOIUrl":"10.1007/s12518-024-00552-z","url":null,"abstract":"<div><p>For areas without perennial surface water sources, groundwater might be considered the second-largest source of drinking water after surface water. However, groundwater is highly prone to contamination as the groundwater reservoir is formed by the movement of surface water into the subsoil; in its due course of motion, it may dissolve any probable contaminants such as agrochemicals, landfill leachates, the oil spill from underground pipelines, and sewer waste and further convey the contaminated water to join some groundwater aquifers from where the water is again pumped out for human consumption. Therefore, prior to its potable applicability, the quality of groundwater should be evaluated for the presence of alkalinity, hardness, and undesirable and heavy minerals. The Central Ground Water Board (CGWB), Bhubaneswar, collects data on 61 stations in the Kalahandi District for 15 physiochemical parameters, including pH, bicarbonate, hardness, sulphate, Cl<sup>−</sup>, total dissolved solids, Mg<sup>++</sup>, K<sup>+</sup>, Na<sup>+</sup>, total alkalinity, nitrate, fluoride, carbonate, electrical conductivity, and calcium, to assess the quality of the groundwater. The goals were to pinpoint the major elements influencing water quality and comprehend the groundwater quality measures’ regional distribution. Data from the Central Groundwater Board (CGWB) were collected as part of our research, and PCA was used to identify the major impacting elements. To further minimize the dataset’s multidimensionality, a principal component analysis is used. Together, the first three major components explain 76.64% of the overall variability. The first two principal factors themselves explain about 56.9% of the total variance. The three principal factors indicate salinity, hardness, and relative alkalinity and acidity, respectively, in the groundwater.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139775541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Monitoring groundwater quality using principal component analysis 利用主成分分析监测地下水质量

IF 2.7

Applied Geomatics Pub Date : 2024-02-15 DOI: 10.1007/s12518-024-00552-z

Manaswinee Patnaik, Chhabirani Tudu, Dilip Kumar Bagal

引用次数: 0

Mobile mapping system for historic built heritage and GIS integration: a challenging case study 历史建筑遗产和 GIS 集成的移动制图系统：一项具有挑战性的案例研究

IF 2.3

Applied Geomatics Pub Date : 2024-02-15 DOI: 10.1007/s12518-024-00555-w

Daniele Treccani, Andrea Adami, Valerio Brunelli, Luigi Fregonese

{"title":"Mobile mapping system for historic built heritage and GIS integration: a challenging case study","authors":"Daniele Treccani, Andrea Adami, Valerio Brunelli, Luigi Fregonese","doi":"10.1007/s12518-024-00555-w","DOIUrl":"10.1007/s12518-024-00555-w","url":null,"abstract":"<div><p>To manage the historic built heritage, it is of fundamental importance to fully understand the urban area under study, so that all its characteristics and critical issues related to historical conformation, stratification, and transformations can be better understood and described. Geometric surveying allows a deeper investigation of these characteristics through analytical investigation in support of urban planning theories as well. To date, geomatics provides various tools and techniques to meet the above-mentioned needs, and mobile mapping system (MMS) is a technology that can survey large areas in a short time, with good results in terms of density, accuracy, and coverage of the data. In this context, the article aims to verify whether this approach can also be useful in the complex and stratified reality of the historic urban context. The case analyzed—the historical center of Sabbioneta—presents some criticalities found in many urban centers of historical layout. Examples are narrow streets inserted in an urban context with multi-story buildings and consequent difficulty in receiving the GNSS signal and difficulty in following general MMS survey guidelines (trajectories with closed loops, wide radius curves). The analysis presented, relating to a survey carried out with Leica Pegasus:Two instrumentation, in addition to describing the strategies used to properly develop the survey, aims to analyze the resulting datum by discussing its possibilities for use in urban modeling, for cartographic or three-dimensional information modeling purposes. Particular attention is paid to assessing whether the quality of the data (accuracy, density) is suitable for the urban scale. Finally, an analysis of the data obtained from MMS was made with the geographic-topographic database (DBGT), in a GIS (Geographic Information System) environment, to check the possibilities of use and integration between the two models.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12518-024-00555-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139776767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance evaluation of state-of-the-art multimodal remote sensing image matching methods in the presence of noise 存在噪声时最先进的多模态遥感图像匹配方法的性能评估

IF 2.3

Applied Geomatics Pub Date : 2024-02-14 DOI: 10.1007/s12518-024-00553-y

Negar Jovhari, Amin Sedaghat, Nazila Mohammadi, Nima Farhadi, Alireza Bahrami Mahtaj

{"title":"Performance evaluation of state-of-the-art multimodal remote sensing image matching methods in the presence of noise","authors":"Negar Jovhari, Amin Sedaghat, Nazila Mohammadi, Nima Farhadi, Alireza Bahrami Mahtaj","doi":"10.1007/s12518-024-00553-y","DOIUrl":"10.1007/s12518-024-00553-y","url":null,"abstract":"<div><p>To date, various image registration approaches have been conducted to deal with distortions between multimodal image pairs. However, significant existing noise as an unavoidable issue deteriorates many conventional and advanced methods. The critical key is to choose a highly robust local feature detection and description method as the principle for many matching frameworks. However, few studies have concentrated on dealing with the noise issue. For this purpose, this paper evaluates the most well-known and state-of-the-art feature descriptors against artificial sequential noise levels. The employed methods consist of various handcrafted learning-based descriptors. It is further indicated that in addition to the designed structural feature map, multiple criteria, such as spatial arrangement, and the magnitude of the support area, play roles in achieving successful matching, especially in the presence of dramatic noise and complex distortion between multimodal images. Moreover, to filter out the noisy features, the employed local feature detectors are integrated with the uniform competency algorithm. Experimental results demonstrate the overall superiority (20.0% on average) of the MKD (multiple-kernel descriptor) due to advanced designed integrated kernels and polar arrangements.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139777066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance evaluation of state-of-the-art multimodal remote sensing image matching methods in the presence of noise 存在噪声时最先进的多模态遥感图像匹配方法的性能评估

IF 2.7

Applied Geomatics Pub Date : 2024-02-14 DOI: 10.1007/s12518-024-00553-y

N. Jovhari, A. Sedaghat, Nazila Mohammadi, Nima Farhadi, Alireza Bahrami Mahtaj

引用次数: 0

Geometrical evaluation of the UTFPR-DV building area using images of an unmanned aerial vehicle (UAV) with non-metric camera 利用配备非测量摄像机的无人飞行器（UAV）的图像对UTPR-DV 建筑区进行几何评估

IF 2.3

Applied Geomatics Pub Date : 2024-02-10 DOI: 10.1007/s12518-024-00551-0

Raoni Wainer Duarte Bosquilia, Gabriela Oliveira Silva, Maria Madalena Santos da Silva

{"title":"Geometrical evaluation of the UTFPR-DV building area using images of an unmanned aerial vehicle (UAV) with non-metric camera","authors":"Raoni Wainer Duarte Bosquilia, Gabriela Oliveira Silva, Maria Madalena Santos da Silva","doi":"10.1007/s12518-024-00551-0","DOIUrl":"10.1007/s12518-024-00551-0","url":null,"abstract":"<div><p>Nowadays, with the increase in the use of unmanned aerial vehicles (UAVs), small-area aerial photography has become a viable alternative to traditional data surveys, such as topography or satellite imagery analysis, mainly due to its high spatial and temporal resolution. Thus, the objective of this work was to evaluate and compare the survey of the built area of the UTFPR – Dois Vizinhos Campus, Brazil, conducted in the field using total station, with an orthomosaic obtained from a UAV using non-metric camera, with both methods using georeferenced control points in the ground. The analyses showed that there was a high correlation between the areas obtained by these methodologies, with an acceptable error for many purposes, as shown by the Pearson correlation coefficient of 0.9991 and the relative error of 2.23432%, proving to be an effective tool for such surveys. Thus, this work concluded that it is possible to survey the built area from a UAV orthomosaic using a non-metric camera, which required less equipment and allowed to obtain the data in a shorter time when compared to a classical topography survey on the field.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139786280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Geometrical evaluation of the UTFPR-DV building area using images of an unmanned aerial vehicle (UAV) with non-metric camera 利用配备非测量摄像机的无人飞行器（UAV）的图像对UTPR-DV 建筑区进行几何评估

IF 2.7

Applied Geomatics Pub Date : 2024-02-10 DOI: 10.1007/s12518-024-00551-0

R. W. Bosquilia, Gabriela Oliveira Silva, Maria Madalena Santos da Silva

引用次数: 0

Machine learning-enabled soil classification for precision agriculture: a study on spectral analysis and soil property determination 面向精准农业的机器学习土壤分类：光谱分析和土壤特性测定研究

IF 2.3

Applied Geomatics Pub Date : 2024-01-03 DOI: 10.1007/s12518-023-00546-3

Amol D. Vibhute, Karbhari V. Kale, Sandeep V. Gaikwad

{"title":"Machine learning-enabled soil classification for precision agriculture: a study on spectral analysis and soil property determination","authors":"Amol D. Vibhute, Karbhari V. Kale, Sandeep V. Gaikwad","doi":"10.1007/s12518-023-00546-3","DOIUrl":"10.1007/s12518-023-00546-3","url":null,"abstract":"<div><p>Surface soil type classification is essential to enhance food production in precision farming. However, soil classification is time-consuming, laborious, and costly through the traditional methods. Recently, artificial intelligence-based methods, especially machine learning, have played a vigorous role in soil classification and its mapping. However, machine learning still makes exterior soil type classification and its mapping difficult due to various features and spatio-temporal inconsistencies. Therefore, the present study has tried to determine soil properties and sort accordingly using hyperspectral datasets and machine learning methods. We used field spectra generated by ASD Field Spec 4 device and satellite image. The proposed approach has identified three prominent soil types, <i>Regur</i> soil, <i>Lateritic</i> soil, and <i>sand dunes</i> according to soil taxonomy, with more than 95% success rate using satellite hyperspectral image and machine learning models. Thus, the outcome of the present study can be effectively utilized in healthy agricultural practices to increase global food production. In addition, the suggested strategy can be used in precision agriculture and environmental management.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139388644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Inter-comparison and assessment of digital elevation models for hydrological applications in the Upper Mahi River Basin 上马希河流域水文应用数字高程模型的相互比较与评估

IF 2.3

Applied Geomatics Pub Date : 2024-01-03 DOI: 10.1007/s12518-023-00547-2

Dweep Pandya, Vikas Kumar Rana, Tallavajhala Maruthi Venkata Suryanarayana

{"title":"Inter-comparison and assessment of digital elevation models for hydrological applications in the Upper Mahi River Basin","authors":"Dweep Pandya, Vikas Kumar Rana, Tallavajhala Maruthi Venkata Suryanarayana","doi":"10.1007/s12518-023-00547-2","DOIUrl":"10.1007/s12518-023-00547-2","url":null,"abstract":"<div><p>This study evaluates and compares the accuracy and reliability of multiple freely available digital elevation models (DEMs) including Copernicus Global Land Operations (GLO), Advanced Land Observing Satellite (ALOS), Cartosat, Shuttle Radar Topography Mission (SRTM), and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) for hydrological applications in the Mahi River upper basin in Western India. Through watershed delineation, statistical analysis, error quantification, and 2D hydraulic modeling using HEC-RAS, this research assesses the performance of these DEMs with GLO DEM as the reference. GLO DEM is used as the reference because key findings show it most accurately delineates watershed boundaries and stream networks and has the fewest sinks. ALOS also demonstrates strong performance, with 70.47% watershed boundary similarity to GLO. Cartosat shows reasonable accuracy in watershed delineation with a Jaccard Index (<i>JI</i>) of 68.41% while SRTM and ASTER appear less reliable. Statistical analysis reveals ALOS slightly overestimates while other DEMs underestimate elevations compared to GLO for most of the slope classes. Flood modeling shows GLO produces the smoothest inundation, with ALOS second-best. Overall, GLO and ALOS emerge as the most accurate and reliable options followed by Cartosat among freely available datasets for the study area. The research provides insights into DEM performance to inform selection and improve hydrological applications involving terrain data for the study area.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139388251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Extending 3D geometric file formats for geospatial applications 为地理空间应用扩展三维几何文件格式

IF 2.3

Applied Geomatics Pub Date : 2023-12-29 DOI: 10.1007/s12518-023-00543-6

Christoph Praschl, Oliver Krauss

{"title":"Extending 3D geometric file formats for geospatial applications","authors":"Christoph Praschl, Oliver Krauss","doi":"10.1007/s12518-023-00543-6","DOIUrl":"10.1007/s12518-023-00543-6","url":null,"abstract":"<div><p>This study addresses the representation and exchange of geospatial geometric 3D models, which is a common requirement in various applications like outdoor mixed reality, urban planning, and disaster risk management. Over the years, multiple file formats have been developed to cater to diverse needs, offering a wide range of supported features and target areas of application. However, classic exchange formats like the JavaScript Object Notation and the Extensible Markup Language have been predominantly favored as a basis for exchanging geospatial information, leaving out common geometric information exchange formats such as Wavefront’s OBJ, Stanford’s PLY, and OFF. To bridge this gap, our research proposes three novel extensions for the mentioned geometric file formats, with a primary focus on minimizing storage requirements while effectively representing geospatial data and also allowing to store semantic meta-information. The extensions, named GeoOBJ, GeoOFF, and GeoPLY, offer significant reductions in storage needs, ranging from 14 to 823% less compared to standard file formats, while retaining support for an adequate number of semantic features. Through extensive evaluations, we demonstrate the suitability of these proposed extensions for geospatial information representation, showcasing their efficacy in delivering low storage overheads and seamless incorporation of critical semantic features. The findings underscore the potential of GeoOBJ, GeoOFF, and GeoPLY as viable solutions for efficient geospatial data representation, empowering various applications to operate optimally with minimal storage constraints.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12518-023-00543-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139146417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0