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GEOG 0094 - Geospatial Analysis

http://catalog.sierracollege.edu/course-outlines/geog-0094/

Catalog Description DESCRIPTION IS HERE: Prerequisite: Completion with grade of "C" or better or concurrent enrollment in GEOG 90 or 91B Hours: 54 lecture Description: Geospatial analysis reveals patterns, relationships, and trends that solve real-world challenges. With GIS tools, students create surface contours, derive slopes, calculate flow direction, draw watersheds, determine line of sight and identify hotspots. GIS modeling and extensions are used. (CSU) Units 3 Lecture-Discussion 54 Laboratory By Arrangement Contact Hours 54 Outside of Class Hours Course Student Learning Outcomes Recall how to transform coordinate grid systems, projections and datum to align all displayed GIS layers. Assess appropriate approaches to spatial modeling on a case-by-case basis. Perform classifications, clusters, and weighted overlays in conjugation with statistical analysis. Create surfaces using Spatial Analyst or 3D Analyst. Rank attributes with color intensity using raster modeling. Course Content Outline I. Getting started with GIS analysis 1. Applications / Who and What doing 2. Framing the question / Stating the problem 3. Breaking down the problem into pieces / diagramming / modeling concepts 4. Input data needed (e.g., elevation, land use, existing schools, etc.) 5. Raster versus Vector data models 6. Building a sample model II. Spatial modeling and GIS analysis 1. Review coordinate systems, map projections, datums 2. Database design considerations / how raster stored in file geodatabase 3. Review basic location, overlay & proximity analysis 4. Appropriate tools (spatial analysis, 3D analysis, etc.) 5. Common geoprocessing tools in for extension (density, distance, etc.) III. Analyzing raster data 1. Uses (background or analysis operations) 2. DEM, cell values & size 3. Integrate raster and vector analysis 4. Raster conversion 5. Automated workflows using models 6. Types of raster analysis 7. Extraction (clip, extract by circle, polygon, etc.) 8. Filtering or generalization (region group, nibble, shrink) 9. Water-based analysis (flow, advection-dispersion) 10. Statistical analysis IV. Creating Surfaces 1. Sources of surface data 2. Creating surfaces (3D Analyst, TINs) 3. Interpolation methods (Nat. Neighbor, Spline) 4. The importance of sample points 5. Calculating density V. Planning and building a raster suitability model 1. Examples of suitability maps / rankings / methods 2. Binary and weighted suitability modeling concepts 3. Planning a scale of suitability 4. Reclassifying raster layers VI. Exploring data patterns and relationships using spatial statistics 1. Directional distribution (a.k.a. standard deviational ellipses) 2. potential applications (crime patterns, groundwater contamination, etc.) 3. Build a Hot Spot Model 4. Potential applications (disease outbreak concentration, peak intensities) Course Objectives Course Objectives 1. Construct comprehensive framework or model to address stated problems. 2. Transform coordinate, projections and datums for display purposes. 3. Assess different approaches to spatial modeling. 4. Evaluate type of raster analysis to achieve stated objectives or anticipated results; 5. Generate basic water-based analysis results, such as flow direction. 6. Perform classifications, clusters, weighted overlays in conjunction with statistical analysis. 7. Create surfaces, using extensions such as 3D analyst; DEM creation and use. 8. Build a raster suitability model using ranking method with color intensification schemes; and integrate with other geo-spatial analysis. 9. Using spatial statistics, such as tracking criminal activity, transform into a hot spot model and map. May use 2D or 3D to represent patterns. Methods of Evaluation Projects Skill Demonstrations Reading Assignments 1. Read the introductory chapter, to investigate different applications of spatial modeling to answer specific questions, such as mapping the distributional trend for a set of crimes that might identify a relationship to particular physical features (a string of bars or restaurants, a particular boulevard, and so on) and be prepared to discuss in class. 2. Read the "A Guide to GIS Analysis," to determine the most effective means to map density (dot map, raster surfaces, density by polygon) by comparing other similar applications and be prepared to discuss in class. Writing, Problem Solving or Performance 1. Exploratory data analysis (EDA) Looking at spatial statistics, explore data that reveal geographic patterns. Specifically use tools such as a histogram to identify outliers and manipulate class divisions to flesh out objectives such as high & low data values, hot spot analysis, detect the unexpected, locate mean center, calculate deviational ellipses, etc. 2. Create Topographic Surfaces Using a Digital Elevation Model (DEM) and related GIS data layers, manipulate ESRI Spatial Analyst extension to derive contours, slopes, aspect, and prominent ridgelines to ascertain high risk or hazardous fire areas useful to determine home insurance rates. Other (Term projects, research papers, portfolios, etc.) 1. Final analysis project to include in mapping portfolio. Methods of Instruction Lecture/Discussion Distance Learning Other materials and-or supplies required of students that contribute to the cost of the course.