Standard Course Outline

STANDARD COURSE OUTLINE

College of Liberal Arts

Department of Geography

I. General Information A. Course Number: 141 B. Title: Introduction to Physical Geography Laboratory C. Units: 1 D. Prerequisites or corequisites: Geography 140 or Geology 102 and a course that fulfills the A.1 GE requirement. Prior or concurrent enrollment in a course that fulfills the B.2 requirement is strongly recommended. E. Course Classification: 1 unit at C15 F. Responsible Faculty: C.M. Rodrigue, S. Dallman, P. Laris, C. Lee, S. Wechsler, C. Holmgren G. Terms Offered: every semester H. Prepared by: Christine M. Rodrigue I. Date of Submission/Revision: Fall 2007

II. Catalogue Description Laboratory and field study of the physical environment, emphasizing application of such geospatial techniques as GPS, remote sensing, cartography, GIS, and geostatistics. Course fee may be required (3 hours laboratory and field activity).

III. Expected Outcomes: Upon successful completion of the course, the student will be able to: A. understand Earth-Sun relationships as they affect incoming solar radiation at various latitudes and seasonality B. understand the electromagnetic spectrum and the distribution of solar energy and Earth- emitted energy across that spectrum C. become familiar with a variety of remote sensing images and the sensors that produced them in terms of spatial, spectral, radiometric, and temporal resolution D. be able to interpret remotely sensed images of natural and human-altered landscapes E. be able to collect field data in a GPS unit and transfer the data into a GIS for mapping and analysis F. understand the elements of effective map communication of physical features and processes G. be able to produce maps of the physical environment from field-collected data H. be able to produce maps of the physical environment in a GIS, using either field or archival data I. be able to interpret maps of the physical environment and infer processes from spatial patterns J. be able to characterize data with basic descriptive statistics K. be able to characterize relationships among variables using basic inferential statistics L. be able to model physical features or processes using linear equations M. be able to interpolate missing values from a spatial field of known values (Kriging) N. be aware of the importance of scale in the interpretation of physical environments O. be able to write up and illustrate lab and field results logically and succinctly IV. Text: Departmental lab archive

V. Course Outline: Techniques to Be Applied (1-2 weeks on Physical Environmental Patterns and each of at least 8 of these) Processes to Be Analyzed with Geospatial Techniques (1-2 weeks on > 8 of these topics) o Remote sensing data: sensors, o Earth in space resolutions, and interpretation o Electromagnetic spectrum, solar radiation o Map interpretation (e.g., constructing and Earth radiation elevation profiles from contour maps) o Weather and climate processes and o Field mapping and data collection patterns o Global Positioning Systems (GPS) o Climate and environmental change and field data collection o Vegetation systems as indicators of climate o Geographic Information Systems and influences on slope and hydrological (GIS) and digital mapping processes o Describing data with statistics: o Water, soil, and air quality central tendency, variation o Earth materials o Relationships between environmental o Tectonic processes (e.g. folding, faulting, variables earthquake magnitude and epicenter) o Modelling physical systems and o Gradational processes (e.g., mass wasting, interpolation fluvial, glacial, coastal, wind processes) o Microscopy o Frequency and magnitude relationships o Safe use of lab equipment and (e.g., for floods, earthquakes, droughts) chemicals

VI. Methods of Presentation: A. Laboratory demonstrations and activities B. Field demonstrations and activities

VII. Methods of Evaluation: A. Field exercises and reports (required) B. Laboratory exercises and reports (required) C. Exams (optional) D. Oral or poster presentations (optional) VIII. Outcomes and Assessments: Expected Learning Outcomes Representative Assessments

A. understand Earth-Sun relationships o Lab applying the inverse square law and trigonometry to understand the solar constant, the trivial effect of orbital eccentricity on seasonality, and the distribution of insolation intensity by latitude and season o Lab on use of the analemma and chronometers to determine latitude and longitude B. understand the electromagnetic o Lab applying Wien's Displacement Law to spectrum the concentration of peak insolation intensity in the visible light spectrum and the concentration of Earth radiated energy in the infrared o Lab using prisms or diffraction gratings to demonstrate the EMS in the visible light range C. become familiar with remote sensing o Lab on feature identification using imagery imagery of different spatial and spectral resolution (e.g., coarse Landsat vs. fine IKONOS; hyperspectral AVIRIS vs. multispectral SPOT) D. be able to interpret remotely sensed o Lab on vegetation classification using images of natural and human-altered multispectral imagery (e.g., Landsat, landscapes IKONOS, SPOT) o Lab on water pollutant tracking using multispectral imagery E. be able to collect field data in a GPS o Field project collecting locations and unit and transfer them into a GIS physical data using Garmin GPS units o Lab on moving GPS points into ArcGIS, constructing a simple map, and performing analysis of the physical data attributes of the field locations F. understand the elements of effective o Lab on map scale, projections, symbology, map communication comformality and equal-area trade-offs, and clutter G. be able to produce manual maps from o Field project on surveying and manual field data mapping of points at which physical data are collected (e.g., relative humidity, temperature, soil pH or compaction, vegetation sampling to assess fire hazard, water sampling) H. be able to produce maps of the o Lab transferring field-collected data points physical environment in a GIS, using and environmental attributes into ArcGIS either field or archival data o Lab downloading a Digital Elevation Model and delineating a watershed Expected Learning Outcomes Representative Assessments

I. be able to interpret maps of the o Lab inferring stratigraphic structure and the physical environment and infer sequence of sedimentary, seismic, and processes from spatial patterns volcanic events from a series of maps J. be able to characterize data with o Lab calculating mean precipitation and basic descriptive statistics standard deviation from weather data for Long Beach o Lab graphing mean precipitation and temperatures by month for a variety of weather stations and classifying them into climate types o Lab characterizing point distributions (e.g., plants, dune fields, karst sinkholes) as clustered, random, or uniform using nearest neighbor analysis K. be able to characterize relationships o Lab using Chi-square and Yule's Q tests to among among variables statistically evaluate the spatial patterns of two plant or lichen species in a study area (either archival or field data) o Lab using simple linear correlation and regression analysis to describe the association between snowfall and distance from Lake Erie o Lab using simple linear correlation and regression analysis to describe the association between annual precipitation and variability in precipitation L. be able to model physical features or o Lab modelling the association between processes using linear equations stream discharge and velocity using a power curve o Lab modelling the association between specific humidity and air temperature using an exponential curve M. be able to interpolate missing values o Lab creating an isobar map of North from a spatial field of known values America from NOAA/NWS data o Lab creating a contour map from USGS elevation data (paper or digital) N. be aware of the importance of scale o Lab doing Chi-square analysis of the in the interpretation of physical association between dominant species and environments slope angle at different scales (Modifiable Areal Unit Problem) o Lab doing Chi-square analysis of the association between two species at different scales (MAUP) o Lab doing nearest-neighbor analysis of point patterns (e.g., plant locations) at different scales (MAUP)

Expected Learning Outcome Representative Assessments

O. be able to write up and illustrate lab o All labs and field projects include write up of and field results logically results and most require graphs, tables, equations, and/or maps o There are so many lab and field reports that students will get multiple opportunities to improve their writing, quantitative, analytic, and graphic skills o The optional oral or poster presentation will provide opportunity to present and illustrate results in the succinct viewgraph (e.g., PowerPoint) or poster format so common in most sciences

IX. Bibliography:

A. Course lab manual is drawn from the Department of Geography collection of laboratory exercises B. Physical geography textbooks that are commonly used in GEOG 140: 1. Christopherson, Robert. 2005. Geosystems: An Introduction to Physical Geography, 6th ed. Prentice Hall. 2. de Blij, Harm J.; Muller, Peter O.; and Williams, Richard S. 2003. Physical Geography: The Global Environment. Oxford University Press. 3. Gabler, Robert E.; Petersen, James F.; and Trapasso, Michael L. 2005. Essentials of Physical Geography. Brooks Cole. 4. Holden, Joseph. 2006. Introduction to Physical Geography and the Environment. Prentice Hall. 5. Smithson, Peter; Addison, Ken; and Atkinson, Ken. 2002. Fundamentals of the Physical Environment, 3rd ed. Routledge. 6. Strahler, Alan H. 2005. Physical Geography: Science and Systems of the Human Environment, 3rd ed. Wiley. C. Some journals in which physical geographers publish: 1. Annals of the Association of American Geographers 2. The Professional Geographer 3. Progress in Physical Geography 4. Geografiska Annaler, Series A: Physical Geography 5. Physical Geography 6. EOS: Transactions of the American Geophysical Union 7. Journal of Geophysical Research 8. Earth Interactions 9. Geophysical Research Letters 10. Reviews of Geophysics 11. Global Biogeochemical Cycles 12. Geochemistry, Geophysics, Geosystems 13. Water Resources Research 14. Hydrological Sciences Journal 15. Journal of Hydrology 16. Hydrological Processes 17. Earth Surface Processes and Landforms 18. Geomorphology 19. Bulletin of the Geological Society of America 20. Journal of Arid Environments 21. Journal of Coastal Research 22. Journal of Quaternary Science 23. Catena 24. Bulletin of the American Meteorological Society 25. Journal of Climate 26. Climatic Change 27. International Journal of Climatology 28. Palæogeography, Palæoclimatology, Palæoecology 29. Journal of Hydrometeorology 30. Journal of Biogeography 31. Journal of Ecology 32. Ecology 33. Ecological Monographs 34. Photogrammetric Engineering and Remote Sensing 35. International Journal of Remote Sensing 36. Transactions in GIS 37. Geoinformatica 38. The Photogrammetric Record 39. Science 40. Nature D. Articles and chapters ???????? X. SYLLABUS

GEO 474 - INTRODUCTION TO DIGITAL IMAGE PROCESSING

DEPARTMENT OF GEOGRAPHY - SPRING 2006 DR. CHRISTOPHER LEE - INSTRUCTOR DATE/TIME: MW 2 pm-4:20pm CLASSROOM: LA4-100 (lecture) and LA4-207 (lab) OFFICE: LA4 205 OFFICE HOURS: M& W 9:30-10:15 am AND 5-5:30 PM, Tues 10am-12pm, Th & F by appointment TELEPHONE: 562-985-2358 E-MAIL: [email protected]

COURSE OBJECTIVE GEO 474 is designed to introduce students with a background in remote sensing to the principles and concepts of digital image processing and the extraction of inforamtion from digital airborne and satellite data. Lectures will focus on various enhancement and analysis techniques, specifically, within the visible and near-infrared portions of the electromagnetic spectrum. Current and near future imaging systems will be investigated and specific applications projects and programs involving the techniques discussed will also be presented.

The course will also provide introductions to the integration of derived digital information into Geographic Information Systems (GIS), and the role of Global Position Sytems (GPS) in providing required geometric fidelity. Laboratory exercises will follow two tracks, one that stresses learning the fundamentals of ERDAS and Feature Analyst image processing software and a second that focuses on the application of these software packages to the processing and analysis of selected data sets. Semester projects will allow each individual to choose an image or images of specific interest and apply selected techniques.

TEXTBOOK Digital Image Processing, J. Jensen, 2004, 3rd edition

ATTENDANCE Although your grade will not be lowered for absences, past experience has shown that you will need to attend lectures on a regular basis and devote the required time to labs and projects to do well in this course. If you do not take advantage of regular lab time (and even if you do) you will need to schedule alternate/additional lab time to properly complete labs and semester projects.

GRADING Three lecture examinations = 60% of final grade Laboratory exercises = 30% of final grade Semester Project = 10% of final grade

A = 90% of total points B = 80% of total points C = 65% of total points D = 60% of total points F = less than 60% of total points COURSE CONTENT

Lectures/Readings Introduction The Remote Sensing Process Orbital and Airborne Sensors Structure of Digital Imagery Initial Statistics Extraction Preprocessing Radiometric Normalization Atmospheric Correction Geometric Rectification Examination #1

Classification Schemes Image Classification Unsupervised Supervised Change Detection Examination #2

Selected Applications Vegetation Indexes Band Ratioing Image Enhancement Spatial Filtering Low Pass Filters High Pass Filters Principal Components Analysis Examination #3 (Final Exam)

Laboratory Exercises- Software Viewer Import/Export Map Composer Vector Querying and Editing Polynomial Rectification Classification Advanced Classification Image Interpreter Spatial Modeler (Feature Analyst)

Laboratory Exercises - Sensors and Applications Selected Sensor Powerpoint Presentation Campus GPS Data Collection and Image Rectification Southern California Image Classification Delta Vegetation Index Port Image Rectification Port Feature Extraction