Geospatial Techniques for Engineers

Overview

Syllabus

Courses

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  13 hours 27 minutes

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  The "Geospatial Information Technology Essentials" course offers a multi-disciplinary approach, integrating key aspects of both Geospatial and Information Technology. Organized into seven comprehensive modules, it provides a thorough learning experience. Module One introduces the fundamentals of Geographic Information Systems (GIS), covering its applications, hardware requirements, data models, and attribute data types. Module Two delves deeper into GIS concepts, focusing on mapping essentials, data conversion techniques, and georeferencing. In Module Three, learners explore GIS database management, including basics of databases, RDBMS, SQL, and advanced geodatabase management. Module Four covers spatial analysis using GIS, with practical demonstrations of techniques like catchment area delineation, overlay analysis, and viewshed analysis. Module Five provides insights into geospatial IT, including enterprise GIS, web and mobile GIS technologies, and practical case studies. In Module Six, system integrations and decision support are discussed, with a focus on command and control center case studies, decision support systems, and open-source GIS projects. Module Seven introduces future trends in geospatial technologies, highlighting advancements in survey and mapping technologies, spatial analytics, and geointelligence. Join us on this journey into Geospatial Information Technology and equip yourself with the essential skills and knowledge to excel in this dynamic field! Target Learners: • Undergraduate students of Civil Engineering • Post-Graduate Students in Geoinformatics/ Remote Sensing/ Geospatial Engineering. • Practicing Engineers involved in geospatial applications in construction. • Faculties in Civil, Geospatial and Environmental Studies. • Professionals in GIS and Remote Sensing fields • Engineers and project managers involved in spatial data analysis Prerequisites: • Basic understanding of GIS principles and spatial data • Familiarity with computer operations and software usage • Software: ArcGIS
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  14 hours 59 minutes

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  The "Geospatial Technology for Construction" course adopts a multi-disciplinary approach, integrating key aspects of Geospatial and Construction Engineering. The content is structured into seven modules for a comprehensive learning experience. In Module One, learners will understand geospatial thinking, its daily applications, and the importance of spatial thinking. This includes differentiating information types and communicating spatial information effectively. Module Two explores the necessity of Geospatial Technology in the construction industry, covering its role in tender processes, design, execution, and lifecycle management. Module Three delves into geospatial surveying and mapping, introducing components, basics of surveying, and advanced solutions through practical use cases. Module Four covers digital level, electronic total station, and GNSS technologies, demonstrating their use and providing an overview of GNSS components and field procedures. Module Five introduces advanced spatial sensing and imaging technologies, including scanning, remote sensing, and sensor applications. Module Six provides in-depth knowledge of photogrammetry and LiDAR, with practical demonstrations of equipment and data processing. Module Seven explores engineering solutions in geospatial contexts, introducing CORS, scan-to-model techniques, and construction site optimization using UAVs. Visualization in construction projects is also emphasized. We look forward to you joining us on this journey into Geospatial Technology for Construction, equipping you with essential skills and knowledge for this dynamic field! Target Learners: • Undergraduate students of Civil Engineering • Post-Graduate Students in Geoinformatics/ Remote Sensing/ Geospatial Engineering. • Practicing Engineers involved in geospatial applications in construction. • Faculties in Civil and Geospatial Engineering. • Industry professionals working in construction, surveying, and geospatial technology companies. • Project managers and consultants in construction and infrastructure development sectors. Prerequisites: • Basic knowledge of Civil Engineering principles • Familiarity with Surveying and Mapping • Understanding of Construction Practices • Software: ArcGIS, AutoCAD, Trimble Business Center, SCENE Software
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  18 hours 49 minutes

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  The "Mastering Geospatial Analysis with QGIS" course employs a multi-disciplinary approach, covering essential aspects of geospatial analysis and QGIS software through nine structured modules. Module One introduces learners to QGIS, encompassing installation, QGIS 3.0 basics, and interface exploration including toolbars, panels, and plugins. Module Two focuses on practical geospatial data handling within QGIS, covering shapefiles, vector and raster data styling, and attribute management using calculators and selection tools. Module Three explores cartographic techniques such as coordinate systems, projections, and map creation including choropleth and graduated symbol maps. Additionally, it includes data integration tools like basemaps, GPS data handling, and measurement tools. Module Four delves into georeferencing and digitization methods for toposheets and online sources like Open Street Maps and Google Earth. Advanced spatial analysis techniques like buffer and overlay analysis are detailed in Module Six, while Modules Seven to Nine cover satellite data handling, terrain analysis, and advanced mapping and application development using QGIS and tools like Qfield and BIM integration. Join us in mastering QGIS for geospatial analysis and applications development, preparing to excel in this dynamic field. Target Learners: • Undergraduate students of Civil Engineering • Post-Graduate Students in Geoinformatics/ Remote Sensing/ Geospatial Engineering. • Practicing Engineers involved in geospatial applications in construction. • Faculties in Civil, Geospatial and Environmental Studies. • Professionals in GIS and Remote Sensing fields • Engineers and project managers involved in spatial data analysis Prerequisites: • Basic understanding of GIS principles and spatial data • Familiarity with computer operations and software usage • Software: QGIS

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