GEOG 481 Syllabus

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2024 Syllabus

GEOG 481: Topographic Mapping with Lidar

This syllabus is divided into several sections. You can read it sequentially by scrolling down the length of the document. That said, it is essential that you read the entire document as well as the material covered in the Orientation. Together, these serve the role of our course "contract."

Instructors

    Summer (May - July)

    Karl Heidemann

    Adjunct Instructor
    Department of Geography
    Penn State University

    NOTE: I will read and respond to e-mail and discussion forums once per day at a very minimum. I encourage interactions between all of us in the course. Graduate seminars are an opportunity to learn from each other as well as from the instructor!

    Course Overview

    GEOG 481: TOPOGRAPHIC MAPPING WITH LIDAR - An introduction to the capabilities of lidar sensors and platforms, data processing systems, and derived digital data products. Students in this course will master the basic skills needed to leverage commercial lidar data sources and information products in a broad range of applications, including topographic mapping, flood inundation studies, vegetation analysis, and 3D modeling of urban infrastructure.

    Lidar (Light Detection and Ranging) is an optical remote sensing technology that uses laser pulses to determine the distance between the sensor and a surface or object. In recent years, lidar has emerged as one of the most important sources of data for topographic mapping, vegetation analysis, and 3D modeling of urban infrastructure. Federal, state, and local government agencies are acquiring lidar data and derived products for use in floodplain mapping, transportation planning, and design, resource and environmental management, law enforcement, and emergency response. Much of this data is freely available to the public, and new uses for the data are emerging at a rapid pace. A thorough understanding of lidar technology and its application in GIS is part of the essential body of knowledge for today’s geospatial professional.

    Students who register for the course for credit will complete one orientation lesson and seven content lessons with corresponding quizzes, hands-on assignments, and online discussions. An individual final project is designed and executed by the student in an application area of their choice. Throughout the course, students confront realistic problem scenarios that incorporate such skills and concepts as the definition of data needs, metadata content standards, data formats and types, analysis methods, and spatial accuracy requirements. Those who successfully complete the course will be able to define lidar project specifications in the context of an end-user GIS application.

    Prerequisites: 480 (or equivalent professional experience). It is expected that students are conversant in fundamental concepts of GIS and have hands-on experience with ArcGIS Pro. The following bullets are examples of knowledge and skills you should have before starting this course.

    • explain the concept of map scale
    • explain the concept of a map projection
    • describe the difference between a vector and a raster data set
    • explain the difference between an Esri SHP file and a feature class
    • explain the difference between a 2D and 3D SHP file or feature class
    • manage GIS data files in the Esri interface
    • access data management, data conversion, and data analysis tools in the Esri interface
    • add a vector data layer to a project file
    • add a raster data layer to a project file
    • create a new SHP file or feature class
    • edit a SHP file or feature class using the Editor toolbar
    • change symbols for a SHP file or feature dataset using Symbology Properties
    • view and edit the attribute table for a SHP file, feature class, or raster layer
     

    What will be expected of you?

    This course will require a minimum of 12 - 15 hours of student activity per week.

    Each lesson consists of reading assignments online and in the course textbook. Mandatory reading quizzes in each lesson test your comprehension of this material. Lab instructions for each lesson are provided in PDF form for you to download and print for reference as you proceed through the hands-on exercises with data and software. Lab work is submitted in the form of a Canvas quiz. You are encouraged to ask questions and post comments at any time in the Canvas discussion forums.

    You should get in the habit of checking course e-mail and discussion forums in Canvas on a daily basis. That's where students and the instructor share comments, pose questions, and suggest answers. With only occasional exceptions, the instructor will check e-mail and forums six days per week and will respond to your questions and concerns within 24 hours.

    For a more detailed look at what will be covered in each lesson, please refer to the course content that is part of this syllabus (see "Course Content"). Due dates for assignments and activities will be posted in the Calendar in Canvas.

    Course Objectives

    GEOG 481 cultivates students’ knowledge of the capabilities and limitations of lidar instruments and processing systems. The course also introduces fundamental concepts of accuracy assessment and appropriate use of lidar-derived data products. It helps students master the basic skills needed to leverage these data sources and information products in the context of application domains, such as topographic mapping, floodplain mapping, forestry, urban and regional planning, transportation systems design, and emergency response.

    Students who excel in this course are able to:

    • summarize the basic operational characteristics of lidar instruments and platforms used for topographic mapping and geospatial applications;
    • describe the basic principles of calibrating, georeferencing, and processing of lidar data;
    • describe quantitative and qualitative methods used in industry standards for quality assurance and accuracy assessment of lidar-derived data products;
    • critically assess the strengths and weaknesses of various lidar platforms and instruments for a broad range of application scenarios;
    • apply acquired knowledge and critical thinking skills to solve a real-world problem with appropriate lidar data processing and analysis methods.

    Required Course Materials

    There is one required textbook for this course.

    Renslow, Michael, ed. 2012. Airborne Topographic Lidar Manual. Bethesda, MD. American Society for Photogrammetry and Remote Sensing. ISBN 1-57083-097-5.

    The required textbook for this course, Manual of Airborne Topographic Lidar, can be purchased from Amazon(link is external) in Hardcover (prime eligible) and Kindle Edition.

    ASPRS members receive a discount when purchasing directly from the ASPR Bookstore(link is external). Add the book to your cart, navigate to the cart page, then enter your ASPRS login credentials to see the discounted pricing.

    Assistance 

    Penn State honors and values the socioeconomic diversity of our students. If you require assistance with the costs of textbooks for this course, please contact your academic advisor. For additional needs, related to socioeconomic status, please visit Project Cahir(link is external) or visit the Office of Student Care and Advocacy(link is external) at 220 Boucke Building or call 814-863-2020.

    Supplemental References (No Purchase Necessary)

    Additional readings may be provided electronically through the course management system and Penn State library services. These readings may include but are not limited to, the following sources. These are also useful references for final project development.

    Campbell, J.B. 2007. Introduction to Remote Sensing. 4th edition. The Guilford Press. ISBN 978-1606230749.

    Congalton, R. and K. Green. 2009. Assessing the Accuracy of Remotely Sensed Data. 2nd edition. CRC Press. ISBN 978-1-4200-5512-2.

    Jensen, J.R. 2007. Remote Sensing of the Environment: An Earth Resource Perspective. 2nd edition. Prentice Hall. ISBN 978-0131889507.

    Maune, D. F., ed. 2007. Digital Elevation Model Technologies and Applications: The DEM Users Manual. 2nd edition. Bethesda, MD. American Society for Photogrammetry and Remote Sensing. ISBN 1-57083-082-7.

    McGlone, J. C., ed. 2004. Manual of Photogrammetry. 5th edition. Bethesda, Md.: American Society for Photogrammetry and Remote Sensing. ISBN 1-57083-071-1.

    Shan, J. and C. Toth, ed. 2008. Topographic Laser Ranging and Scanning, Principles and Processing. Boca Raton, FL. Taylor & Francis Group. ISBN 9781420051421.

    Wolf, P., B. Dewitt, B. Wilkerson. 2014. Elements of Photogrammetry, 4th edition. Boston. McGraw-Hill. ISBN 978-0071761123.

    Earth Imaging Journal(link is external).

    Photogrammetric Engineering and Remote Sensing(link is external), American Society for Photogrammetry and Remote Sensing.

    Technical Requirements

    The minimum technical requirements for the MGIS program apply to this course. They can be found on the Online Geospatial Education Technology and Communication Requirements(link is external) page.

    Mac users will need either Parallels, Bootcamp, or VMWare to run ArcGIS and other software required for the remote sensing courses. Please refer to instructions provided by Esri(link is external) when installing ArcGIS on an Apple computer.

    The following bullets apply to all courses in the remote sensing curriculum:

    • This is a very computer-intensive course. The minimum technical requirements linked above really are the minimum. If you do not have a computer that meets these and the following specifications, you will have trouble completing the course.
    • You must have a reliable, robust high-speed Internet connection on a daily basis. The course requires you to watch streaming video as well as download files that may be as large as 6 GB. It is not possible to e-mail or send course materials on DVD. You cannot download entire lessons once a week to work offline.
    • Mobile computing platforms are not suitable for this course.
    • You will need an administrator-level password for your computer to be able to install the software required for this course. In addition, if you plan to use a computer that belongs to your place of work (is not your personal property), be aware that if you run into difficulties, the administrators of this course will not be able to help you. 
    • The course software is very memory intensive. RAM has a significant impact on performance and speed. While the program technical specs call for at least 4 GB of RAM, 8-16 GB are recommended when working with the large data files typically encountered in remote sensing work.
    • Your computer should have at least 150 GB of free disk space for course-related materials and data.
    • An external hard drive or flash drive can be used for supplemental backup storage. Be sure to back up your coursework frequently, regardless of what type of disk storage you use. A USB flash (or "thumb") drive is not suitable for your working storage, as these devices are quite slow.
    • An SSD (solid-state) hard drive will support faster processing than an HDD drive. If you are buying a hard drive or computer specifically for this course, check this specification. SSD may be slightly more expensive, but better performance will save you a lot of time overall when doing the lab activities. External USB drives are typically slower than internally installed ones.
    • A second monitor is not required, but if you have one available, you will find it very helpful.

    We recommend using Mozilla Firefox as your browser. Problems encountered within Canvas are almost always related to the choice of browser, so before you contact Canvas Technical Support, make sure you have tried using Firefox. Please use the links below to test some of your basic browser settings:

    1. Adobe Acrobat(link is external)
    2. Cookies(link is external)
    3. Frames(link is external)
    4. Java(link is external) [This may take a minute to load.]
    5. JavaScript(link is external)

    Required Software

    NOTE: You need administrative rights on your computer in order to properly install the course software.

    All software listed below is provided at no cost to the enrolled student, but a specific process must be followed to obtain these licenses. Instructions for downloading and installing the software are given in the lab activity for Lesson 0. You will be given ample time to obtain, install, and test the software before using it in a hands-on course activity.

    1. ArcGIS, Esri
      All students in the Online Geospatial Program receive a student license of ArcGIS valid for one year. Licenses will be issued during the first week of class for those students who do not already have one. Students with existing licenses may be asked to upgrade to a newer service pack or version. Instructions for downloading, installing, and updating the ArcGIS software are provided in Lesson 0 - Orientation.
    2. QCoherent, LP360
    3. 7-Zip
      7-Zip can be downloaded for free(link is external).
    4. Screen Capture Utility
      Students are free to use any screen capture software of their choosing. Examples are Snagit(link is external) (paid), Jing(link is external) (free), CaptureWizPro(link is external) (paid), or the Windows Snipping Tool. The software should allow capturing selected portions and single windows on the desktop.

    Supplemental Software Tutorials

    Registered students have access to the Esri Virtual Campus courses free-of-charge. These courses are available for students who wish to review or enhance their ArcGIS skills in preparation for or during the course. Several Virtual Campus courses will be assigned as part of the weekly lab activities; the instructor will provide access codes. Visit the Penn State Esri Virtual Campus Subscription(link is external) page to request access codes for any other Virtual Campus courses that are of interest.

    Free tutorials for other commercial software used in this course are available directly from vendor websites.

    Note!

    If you're interested in productivity software, which can be very helpful and is available at no cost to you as a Penn State student, visit Information Technology's Microsoft Office 365 page(link is external) and the Available Student Software page(link is external). 

    Assignments and Grading

    Students earn grades that reflect the extent to which they achieve the learning objectives listed above. Opportunities to demonstrate learning include:

    • 7 online quizzes (17% of grade)
    • 8 hands-on laboratory activities (45% of grade)
    • 6 discussion/survey activities (4% of grade)
    • 6 final project building activities (31% of grade)

    The final grading scale, based on 445 point total, is shown below.

    Grading Scale
    A 93% and above 413 points and above
    A- 90% - 92.9% 400 - 412 points
    B+ 87% - 89.9% 387 - 399 points
    B 83% - 86.9% 369 - 386 points
    B- 80% - 82.9% 356 - 368 points
    C+ 77% - 79.9% 342 - 355 points
    C 70% - 76.9% 311 - 341 points
    D 60.0 - 69.9% 267 - 310 points
    F 59.9% and below 266 points and below

    Class participation will be considered in grading for those whose final course grade is close to the next letter grade. To view your progress throughout the semester, click on Grades in Canvas. In order to qualify for use of any extra credit points in the calculation of the final grade, the student must submit ALL lesson quizzes, hands-on activities, discussions, and final project deliverables. Exceptions to the extra credit policy may be granted by the instructor on a case-by-case basis in special circumstances.

    Assignments are due on the dates published in the Canvas calendar and syllabus. Acceptance of assignments after the due date is at the discretion of the instructor; late penalties may be applied. Extensions and waiver of late penalties can be requested in writing, but must be received by the instructor before the assignment due date.

    To view your grades during the semester you need to do the following:

    GEOG 481 Course Schedule

    Print IconPrintable Schedule

    Below you will find a summary of the learning activities for this course. The session-specific calendar is available in Canvas.

    Course Orientation and Lesson 0
    Date: Refer to Canvas calendar
    OBJECTIVES:

    After completing the Orientation and Lesson 0, you should be able to:

    • navigate the Canvas course management system;
    • express your expectations about how and what you will learn in your online course;
    • articulate how and what instructors expect you to learn in your online course;
    • locate key information about the course, including assignments, due dates, technical information, and where to go for help;
    • locate detailed information about course policies, including academic integrity and accommodations for disabilities;
    • communicate effectively with instructors and fellow students using a variety of online tools
    Readings: Online: GEOG 481 Orientation
    Assignments:
    1. Orientation Survey
    2. Personal Introduction
    3. Lesson 0 Reading Assignment
    4. Software Installation Quiz
    Lesson 1: Lidar Sensors and Data
    Date: Refer to Canvas calendar
    Objectives:

    After completing this lesson, you should be able to:

    • define “lidar” and differentiate from other remote sensing technologies, such as photogrammetry and radar;
    • describe the basic physics of the interaction of laser energy with earth surface features;
    • describe the historical development of lidar sensors;
    • identify key design components of lidar sensors, including linear-mode (single-return, multi-return, waveform), flash-mode, and geiger-mode.
    Readings:

    See Canvas for details
    Assignments:
    1. Lesson 1 Reading Quiz
    2. Lesson 1 Lab Deliverable
    Lesson 2: Lidar Systems and Calibration
    Date: Refer to Canvas calendar
    Objectives:

    After completing this lesson, you should be able to:

    • describe the integration of direct georeferencing technologies (GPS and inertial measurement devices) with lidar sensors and platforms;
    • explain sources of error in lidar data and methods of system calibration;
    • define “remote sensing platform” and distinguish between terrestrial, airborne, and spaceborne types;
    • outline key steps in airborne lidar mission planning for topographic mapping.
    Readings:

    See Canvas for details
    Assignments:
    1. Lesson 2 Reading Quiz
    2. Lesson 2 Lab Deliverable
    Lesson 3: Lidar Data Processing, Part 1
    Date: Refer to Canvas calendar
    Objectives:

    After completing this lesson, you should be able to:

    • describe procedures for removal of lidar signal noise and other sensor-related artifacts;>
    • classify lidar data by return number and layer;
    • apply simple filtering algorithms for first-level classification of land cover types;
    • explain the tradeoffs between efficiency and accuracy when using automated filters to classify lidar data.
    Readings:

    Refer to Canvas for details
    Assignments:
    1. Lesson 3 Reading Quiz
    2. Lesson 3 Lab Deliverable
    Lesson 4: Lidar Data Processing, Part 2
    Date: Refer to Canvas calendar
    Objectives:

    After completing this lesson, you should be able to:

    • perform manual classification of lidar data;
    • explain the concept of hydrologic enforcement in lidar point cloud data;
    • discuss lidargrammetry as a means for extracting features and terrain breaklines;
    • explain the procedure for creating GIS data products, including DEMs, DTMs, DSMs, and TINs
    • compare and contrast the strengths and weaknesses of various terrain products for use in GIS applications.
    Readings:

    Refer to Canvas for details
    Assignments:
    1. Lesson 4 Reading Quiz
    2. Lesson 4 Lab Deliverable
    Lesson 5: Accuracy Assessment and Quality Control
    Date: Refer to Canvas calendar
    Objectives:

    After completing this lesson, you should be able to:

    • identify, compare, and explain prevailing accuracy standards for lidar;
    • describe sources and methods for detecting systematic error in lidar data;
    • perform quantitative accuracy assessment using statistical methods;
    • describe artifacts commonly discovered in qualitative accuracy assessment;
    • assess accuracy of second-generation lidar-derived data products relative to the source point data;
    • evaluate lidar data using USGS Base Specification;
    • create an accuracy statement for a lidar dataset in accordance with ASPRS Positional Accuracy Standards.
    Readings:

    Refer to Canvas for details
    Assignments:
    1. Lesson 5 Reading Quiz
    2. Lesson 5 Lab Deliverable
    Lesson 6: Topographic Mapping
    Date: Refer to Canvas calendar
    Objectives:

    After completing this lesson, you should be able to:

    • perform hydro-flattening of lakes, ponds, streams, and shorelines;
    • explain the differences between hydro-flattening, hydro-conditioning, and hydro-enforcement;
    • explain differences between surface interpolation methods and discuss their impacts on raster surfaces produced from lidar point clouds;
    • explain the content and use of a lidar intensity image in topographic mapping applications;
    • produce derivative base map products from lidar data according to USGS specifications;
    • discuss challenges involved in producing cartographic contours from lidar point clouds and remedies to address these challenges.
    Readings:

    Refer to Canvas for details
    Assignments:
    1. Lesson 6 Reading Quiz
    2. Lesson 6 Lab Deliverable
    Lesson 7: Lidar Applications
    Date: Refer to Canvas calendar
    Objectives:

    After completing this lesson, you should be able to:

    • describe the advantages and disadvantages of various types of lidar sensors (single-return, multiple-return, and waveform) for forestry applications;
    • generate a canopy model of a forested area from lidar data;
    • perform vegetation metric calculations.
    Readings:

    Refer to Canvas for details
    Assignments:
    1. Lesson 7 Reading Quiz
    2. Lesson 7 Lab Deliverable
    Final Project: Leveraging Lidar Data to Confront Contemporary Challenges in Geospatial Analysis
    Date: Refer to the Canvas calendar
    Objectives: This project will challenge students to apply knowledge and skills acquired in the earlier lessons in a realistic problem scenario that requires the acquisition and analysis of lidar data. The project will span the final four to five weeks of the session. Students will work individually to scope a problem, determine the appropriate combination of lidar data and application software needed to support analysis, propose a processing and analysis workflow, and move to a solution. The students will then produce a final report that discusses their understanding of the problem, a detailed discussion of the workflow steps, and the results of their study.
    Readings: Refer to Canvas for details
    Assignments:
    1. Post final project idea
    2. Peer review other students' final project ideas
    3. Post final project proposal
    4. Peer review other students' final project proposals
    5. Submit written final project report
    6. Prepare final project abstract

    Course Policies

    Citation and Reference Style

    The Academic Integrity and Citation Style Guide is here.

    Need general technical assistance?

    If you need assistance with Canvas at any point during the course, please contact the World Campus Help Desk(link is external)

    Need course-specific remote sensing technical assistance?

    If you need technical assistance with course-specific remote sensing, image processing, or GIS software at any point during the course, please contact the instructor.

    Remote Sensing - Internet Connection and Course Data Downloads

    In this course, you are going to be downloading files ranging in size from several hundred megabytes to several gigabytes. Depending on the speed of your internet connection, this may take somewhere between 10-15 minutes to a few hours. Download speeds are normally faster than upload speeds, regardless of the internet technology. In this course, download speed is most important; you will not have to upload any large files.

    Test your internet connection speed at this Speedtest(link is external) website. Most important for this course is that you have a reliable, constant internet connection, even if the speeds are on the slow end. If you have a slow connection, you can download all the lab data files in advance, perhaps while you are at work during the day or during the night when you are sleeping.

    Here are a couple of guidelines for planning:

    • Do not rely on public Wi-Fi (coffee shop, airport, etc.) as a means of downloading lab data. You may be able to do course email and post on the discussion forum, but any other course work needs more robust internet.
    • Most hotel internet is too slow for downloading lab data files.
    • Check your internet service plan to see if you have limits on the amount of data you can download in one billing period. Some service providers will simply shut down when you reach the plan limit for the month. Others may charge hefty overage fees.
    • Check your internet speeds at different times of the day. Some internet services split bandwidth throughout a neighborhood, so data transfer rates may be a lot slower in the evenings when a lot of users are streaming video.

    If you are overseas or traveling during the course, you are definitely going to have to plan ahead. Download all the tutorials and weekly lab data from all lesson folders as soon as possible. Skim through lab instructions and discussion assignments to note any other data downloads - occasionally we will ask you to find data on public websites, such as USGS or a state GIS data clearinghouse, as part of the learning experience in your course.

    Internet problems can be minimized if you plan ahead. If you are traveling, do not expect to make do with sketchy or occasional service. Sometimes travel comes up due to an emergency or unexpected event. If you have downloaded all the course data in advance, it will be a lot easier to stay on track, or at least not fall terribly behind.

    Questions?

    If you have any questions now or at any point during this week, please feel free to post them to the Discussion Forum.

    In EMS, inclusivity is one of our core values. We prioritize fostering a diverse and equitable community where each member knows they belong here and is inspired to succeed. We encourage everyone in our EMS community to be actively engaged in fostering this ideal, and all members of this class should contribute to a respectful, welcoming, and inclusive environment and interact with civility. Our commitment to inclusivity aligns with Penn State’s values and policies.

    To learn more, visit EMS Educational Equity(link is external). Here, you will find information about the EMS ALLWE initiative, the Rainbow EMS Network, Anti-Racism, active ally-ship, bystander intervention, and more. The site also has resources for where to turn if you need assistance and links to University references. Also, contact your EMS department’s Associate Head for DEI for more information about department initiatives.

    Disclaimer

    Please note that the specifics of this Course Syllabus can be changed at any time, and you will be responsible for abiding by any such changes. Changes to the syllabus shall be given to you in written (paper or electronic) form.