The document discusses calculating the average combined scale factor and convergence angle for state plane coordinate systems. It describes accessing a tool on the NGS website to input latitude and longitude values for project corners to determine the grid scale factor and gamma angle. The average combined scale factor is calculated by multiplying the elevation factor by the average grid scale factor. The convergence angle is also averaged from the four corners to allow converting between grid and geodetic bearings.
Well Directional Survey Processing in FMESafe Software
Directional surveys for wells are typically received with data points represented as angles (inclination, azimuth) and depths. This data needs to be converted to Cartesian coordinates for mapping or 3D visualization. This presentation demonstrates the use of FME to replicate the formula from the "Minimum-Curvature Method" to convert well surveys for mapping purposes.
Well Directional Survey Processing in FMESafe Software
Directional surveys for wells are typically received with data points represented as angles (inclination, azimuth) and depths. This data needs to be converted to Cartesian coordinates for mapping or 3D visualization. This presentation demonstrates the use of FME to replicate the formula from the "Minimum-Curvature Method" to convert well surveys for mapping purposes.
Determination of Sa and Design category and Combinations following BNBC 2020 Seismic Procedure. This app I made by using Python Programming to lessen the time consuming effort. Hope fully this will be a great help to the user as well as improving my skill to next level.
This presentation focuses on Creation of image to image georeferencing in Arcgis of a particular area
A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data.
Raster data is commonly obtained by scanning maps or collecting aerial photographs and satellite images. Scanned map datasets don't normally contain spatial reference information (either embedded in the file or as a separate file). With aerial photography and satellite imagery, sometimes the location information delivered with them is inadequate, and the data does not align properly with other data one has. Thus, to use some raster datasets in conjunction with other spatial data, we need to align or georeference them to a map coordinate system. A map coordinate system is defined using a map projection (a method by which the curved surface of the earth is portrayed on a flat surface). Georeferencing a raster data defines its location using map coordinates and assigns the coordinate system of the data frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with other geographic data.
Generally, we georeference raster data using existing spatial data (target data)—such as georeferenced rasters or a vector feature class—that resides in the desired map coordinate system. The process involves identifying a series of ground control points—known x,y coordinates—that link locations on the raster dataset with locations in the spatially referenced data (target data). Control points are locations that can be accurately identified on the raster dataset and in real-world coordinates. Many different types of features can be used as identifiable locations, such as road or stream intersections, the mouth of a stream, rock outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows. The control points are used to build a polynomial transformation that will shift the raster dataset from its existing location to the spatially correct location. The connection between one control point on the raster dataset (the from point) and the corresponding control point on the aligned target data (the to point) is a link.
Finally, the georeferenced raster file can be exported for further usage.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Spatial analysis & interpolation in ARC GISKU Leuven
In ArcGIS, a data model describes the thematic layers used in the applications (for example, hamburger stands, roads, and counties); their spatial representation (for example, point, line, or polygon); their attributes; their integrity rules and relationships (for example, counties must nest within states).
Determination of Sa and Design category and Combinations following BNBC 2020 Seismic Procedure. This app I made by using Python Programming to lessen the time consuming effort. Hope fully this will be a great help to the user as well as improving my skill to next level.
This presentation focuses on Creation of image to image georeferencing in Arcgis of a particular area
A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data.
Raster data is commonly obtained by scanning maps or collecting aerial photographs and satellite images. Scanned map datasets don't normally contain spatial reference information (either embedded in the file or as a separate file). With aerial photography and satellite imagery, sometimes the location information delivered with them is inadequate, and the data does not align properly with other data one has. Thus, to use some raster datasets in conjunction with other spatial data, we need to align or georeference them to a map coordinate system. A map coordinate system is defined using a map projection (a method by which the curved surface of the earth is portrayed on a flat surface). Georeferencing a raster data defines its location using map coordinates and assigns the coordinate system of the data frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with other geographic data.
Generally, we georeference raster data using existing spatial data (target data)—such as georeferenced rasters or a vector feature class—that resides in the desired map coordinate system. The process involves identifying a series of ground control points—known x,y coordinates—that link locations on the raster dataset with locations in the spatially referenced data (target data). Control points are locations that can be accurately identified on the raster dataset and in real-world coordinates. Many different types of features can be used as identifiable locations, such as road or stream intersections, the mouth of a stream, rock outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows. The control points are used to build a polynomial transformation that will shift the raster dataset from its existing location to the spatially correct location. The connection between one control point on the raster dataset (the from point) and the corresponding control point on the aligned target data (the to point) is a link.
Finally, the georeferenced raster file can be exported for further usage.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Spatial analysis & interpolation in ARC GISKU Leuven
In ArcGIS, a data model describes the thematic layers used in the applications (for example, hamburger stands, roads, and counties); their spatial representation (for example, point, line, or polygon); their attributes; their integrity rules and relationships (for example, counties must nest within states).
2018 GIS in Government: Pits and False Hills and Spikes, Oh My Fixing Blunder...GIS in the Rockies
The U.S. Geological Survey (USGS) National Geospatial Technical Operations Center (NGTOC) maintains the USGS Seamless 1/3 Arc-Second (approximately 10-meter resolution) Digital Elevation Model (DEM). This national dataset provides foundational elevation information for earth science studies and mapping applications over the conterminous United States, Hawaii, Puerto Rico, other territorial islands, and parts of Alaska. Through the 3D Elevation Program, the Seamless DEM is continually updated with new lidar and interferometric synthetic aperture radar (ifSAR) collections (IfSAR in Alaska only). Although eventually all of the 1/3 Arc-Second Seamless DEM will be derived from lidar or ifSAR, currently portions of the dataset, especially in the western United States, are still sourced from legacy data created from digitized 1:24,000 scale topographic map contour lines. This legacy data contains some blunders resulting from errors in data capture, processing, or in the original source map sheet. The purpose of this presentation will be to discuss the types of blunders that are present in a small fraction of our legacy data, how those blunders came to be, and what steps USGS is taking to fix these issues to better support our customers.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
The Pennsylvania State University Department of Civi.docxssusera34210
The Pennsylvania State University
Department of Civil Engineering
CE 321: Highway Engineering
Dr. Venky Shankar, Professor
Jung Yeol Hong, TA.
Preliminary Rural Collector Design,
Connecting SR 20 and SR3
Spring 2015
Section [#]
[Your Name Here]
Due Date: April 24, 2015
1. Introduction
Introduction and Project objectives
1. Alignments analysis
· Analysis of geographical information, topography/surface
· Criteria used in design (horizontal alignment, vertical alignment, cross section, etc.)
· Horizontal and vertical alignment characteristics, impacts displayed by the footprint (effects on forest, roads, waterways, etc.)
· Compare all alignment attributes: length, earthwork volumes, foot print area, environmental impacts, and houses displaced
· Show the 5 separate costs and total cost for each alignment and discuss cost effects
1. Earthwork
1. Safety
1. Pavement
1. Right of Way Acquisition
1. Habitat
1. Total cost for each alignment
Refer to the table
Design Analysis Summary
· Discuss the qualitative performance measures (traffic operation, safety, environment)
Which alternative is predicted safer? Why?
Is delay going to be an issue on either or both alternatives?
Do these performance measures weigh on the final decision?
1. Conclusion
As a result of the comparison, recommend the “best” alternative and describe the reasons
Note:
· Must use the Contour map and Existing Features from ANGEL in this semester (Spring 2015) –CAD drawing, and use this word file for the summary report
· Use bold print section titles
· Report must be written in third person (Do not use I)
· Include page numbers (not necessary for appendices and drawings)
· Refer to all tables or figures that are discussed in the text. There should not be a Table or Figure that is included that is not discussed and called out in the text.
· Minimum 3 pages text
· Please bind report (Cover, text, Appendix A, B, C, and 7 CAD drawings)
Appendix A
(Horizontal Curve Reports)
The horizontal curve report generation function in Civil 3D does not work in this version. Instead of generating a report like you do for the Vertical Curves, copy the information from the “grid view” under “Edit Alignment Geometry.”
· Select the alignment you want to generate a report for
· Right click and select “Edit Alignment Geometry”
· Click the “Alignment Grid View” icon as shown below
· Right click in any cell and select “Copy All”
· Paste table to a new Excel file
· You can delete the following columns
· Start Point
· End Point
· Center Point
· Pass Through Point
· Direction at Through Point1
· Direction at Through Point2
· Attainment Method
· Curve Group Index
· Curve Group Sub-Entity Index
· Pi Point
· Use the remaining table as your Horizontal Curve Report
· Do this for East and West, make sure they are labeled and include them in this appendix
Appendix B
(Vertical Curve Reports)
To generate Vertical Curve Reports:
· G ...
The Ultimate GIS Dictionary: Your Complete Guide to GIS
GIS is more than just “maps and data”. Instead, it’s multi-disciplinary.
It impacts various sectors and uses different skill sets.
That’s why we’ve put together this list of GIS definitions to give you 20/20 vision.
From A to Z, sharpen your GIS knowledge with these GIS dictionary definitions and meanings.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Spcs01a
1. Surv 222 - Geodesy/State Plane STATE PLANE COORINATES Computing Project Average Combined Scale Factor and Convergence angle (Gamma)
2. Purpose To reduce ground measurements to project grid values by reducing to the ellipsoid and then scaling to the grid equivalent (two-step procedure) To calculate the value of convergence (Gamma angle) to allow determination of true north from grid north observations Surv 222 - Geodesy/State Plane
3. Features Calculations are made on NGS site using Geodetic Tool Kit, State Plane Conversion Routine Go to NGS site at: http://www.ngs.noaa.gov/ Select Geodetic Tool Kit (See slide) from left-hand side of menu Select ‘State Plane Coordinates’ (See Slide) Input the values for Latitude & Longitude for the four corners of perimeter rectangle encompassing project site Either select zone or let software determine zone Hit submit and program will process the data providing grid scale factor and convergence (gamma angle) for position Surv 222 - Geodesy/State Plane
8. Surv222 - Geodesy/State Plane Reduction of Ground Surveyed Distance to the Ellipsoid Derived by averaging the elevations throughout the survey area. This is an approximate value and should have 50% of area above and 50% below mean elevation, or alternatively on the perimeter if that is where you will be surveying, such as the perimeter of a section. Start by averaging the elevations at the top left, middle and right corners of mapping area; then middle left, middle of map and middle right; ending with lower left, lower middle and lower right.
9. Surv 222 - Geodesy/State Plane Determination of Elevation Factor Calculate the elevation factor using the formula (Ra/Ra+H+N) Where: H (average orthometric height above the geoid); N (geoid separation); Ra=20,902,000’ (Mean radius of the Earth) From Ghilani & Wolf Elementary Surveying, Section 20.8.1 Grid Reduction of distances. Since Geoid separation is around -20 meters (65’) in Washington, this component can be dismissed as insignificant in this calculation. Simplified, this means for local surveys, such as section line retracements that the ratio is simply 20,902,000/Mean elevation of site (20,902,000+average ortho height)
10. Determination of Elevation Factor From Ghilani & Wolf Elementary Surveying, 12th Edition Section 20.8.1 Surv 222 - Geodesy/State Plane
11. Combined Average Scale Factor Final step of calculation Multiply elevation factor x average grid factor Example 0.9999427 x 0.999921 = .9998637(CSF) Average the convergence angle at each of the 4 corners of the survey project area to use for converting grid bearing to geodetic bearings. The sign of the convergence angle is always from Grid azimuth to geodetic Azimuth. Example: Grid Azim.= N 01°48’15”W-01°56’53”(convergence) =N 00°08’38” E (Geodetic Azimuth) Surv 222 - Geodesy/State Plane