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Spatial Analysis for Resource Management

Spatial Analysis for Resource Management. RESM 575 Spring 2011 Lecture 1. Today. Lecture 2 to 3:30 Break 3:45 to 5pm lab in 2013 Ag Sci Bldg. Overview of today’s topics. What is spatial analysis? What is advanced spatial analysis? Lab today Geoprocesing Model builder.

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Spatial Analysis for Resource Management

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  1. Spatial Analysis for Resource Management RESM 575 Spring 2011 Lecture 1

  2. Today • Lecture 2 to 3:30 • Break • 3:45 to 5pm lab in 2013 Ag Sci Bldg

  3. Overview of today’s topics • What is spatial analysis? • What is advanced spatial analysis? • Lab today • Geoprocesing • Model builder

  4. Introduction to Spatial Analysis

  5. Spatial Analysis • Generically speaking, it is discovering information about spatial data based on its locational relationship to other spatial data

  6. Personnel Hardware Software Spatial Data Analysis Entry Storage Manipulation Presentation

  7. Spatial data • To do spatial analysis, the objects to study must be represented on a map to conduct the spatial relationship • We then build data for both the locations and the attributes • GIS programs then organize the spatial objects

  8. What spatial objects or features are we talking about? • Ways to represent spatial features digitally: • Vector data model • Raster data model

  9. X,Y X,Y X,Y X,Y How are spatial objects stored? • Vector formats (points, lines, polygons) • Discrete representations of reality • Raster formats • Use square cells to model reality Rows Reality(A highway) Columns X,Y

  10. Points(Fire hydrants) Lines (Streets) Polygons (Parcels, Zoning) Representing features in vector data • Real-world entities are abstracted into three basic shapes

  11. Point features • one dimensional • only represent positions, x and y • have no other meaningful measurement • can’t get area or length as a calculation

  12. Line features • one dimensional • represent both position and direction • length is a significant measurement of line features

  13. Polygon features • two dimensional • area features • represent both position and area

  14. Representing features in the raster data model • Square cells store values to represent reality • Images • Aerial photos • Scanned photos or maps • Satellite imagery • Grids • Values represent some measured quantity or classification (elevation, precipitation, land cover)

  15. Raster datasets - GRIDs Common GRID format datasets: • Land use/land cover • Elevation (DEM) • Slope • Aspect • Shaded relief • Precipitation • Temperature

  16. Raster cells or pixels • a cell or pixel is a two dimensional square • the smallest nondivisible element of an image • an object which represents an element of a regularly spaced surface

  17. Basic elements of spatial information • Spatial information requires location, attribute data, and topology • First, the exact location of every spatial feature must be available • Second, attribute data provides the information • Third, topology is the relationship between map features, you must know the topological characteristics and spatial relationships

  18. Key points • Spatial data is the foundation for spatial analysis • Analysis of the data requires that objects be geographically referenced or mappable • Spatial features are points, lines, polygons, and grids with location, attribute info, and topology

  19. Performing spatial analysis • Started by “quantitative geographers” in the mid 80s • GIS software to do spatial analysis has evolved slowly • Other fields besides geography have pushed the development

  20. Basic spatial analysis functions • Available in leading software now • Vector based • Raster based

  21. ArcGIS Select by location

  22. Spatial analysis • Geoprocessing

  23. Spatial analysis with raster data

  24. Spatial analysis with raster data

  25. Spatial analysis with raster data

  26. Move toward more spatial analysis • Other disciplines have forced it with questions • Part of the wider move to a digital world • Computers are more capable • More digital data (remote sensing media) • Ability of GIS software to create data rapidly

  27. Advanced Spatial Analysis

  28. Advanced spatial analysis • More rigorous explanations or models of spatial distributions • Analysis of locational patterns • Forecasting space-time dynamics

  29. Advanced spatial analysis • Longley and Batty (1994): Advanced spatial analysis embraces a whole cluster of techniques and models which apply formal, usually quantitative, structures to systems in which the prime variables of interest vary significantly across space. Yahoo, this is what we will do in this class!!!!

  30. RESM 575 “cluster of techniques and models” • Suitability modeling • Boolean overlay • Spatial multi-criteria analysis • Preference weighting techniques • Membership functions and fuzzy logic • Compromise programming • Spatial compromise programming and the ArcGIS model builder • Interpolation methods, Kriging, Spatial Autocorrelation • Point pattern analysis, spatial statistics, GEODA • Spatial ecology and landscape pattern analysis methods • Advanced terrain analysis • Water quality modeling from expected mean concentration modeling • Weights of evidence, Bayes theorem, posterior probability modeling • Spatial statistics and applications • Home range analysis for wildlife modeling

  31. Caution • Analysis carried out using apparently benign technology that lurks behind user-friendly GIS interfaces routinely makes heroic assumptions – unknown author • These can distort and even confound the results of spatial analysis

  32. Geoprocessing and Model Builder Lab 1 Lessons 1 and 2 Input Data Derived Data Tool

  33. Lesson Overview • Review key ArcGIS concepts • Perform spatial analysis • Review raster analysis • Model builder

  34. Accessing geoprocessing ArcToolbox Command Line Model Builder ArcObjects/Scripts

  35. Using tools for Geoprocessing • General spatial analysis tools • Dissolve • Add XY coordinates • Proximity tools • Finding nearest features • Buffering • Extract/Overlay tools • Clip • Combining features and attributes Multiple 5 mile buffer zones around Charleston

  36. General Tools: Dissolve • Use: Simplify data based on common attribute value (points or lines) • Data Management > Generalization > Dissolve 343 watersheds (before) With river basin attribute 32 river basins (after) New shapefile

  37. Proximity tools - Nearest feature • Analysis Tools > Proximity > Near • Computes distance from each point (input layer) to point or line features (near layer) • Results saved in attribute table of point input layer (table is edited!) Example:Input layer: Towns Near layer: Landfills Result: distance from each town to nearest landfill

  38. Proximity tools - Point distance • Analysis Tools > Proximity > Point distance • Computes distances between point features in input layer to all points in 2nd layer • Results saved in output table, based on FID Example:Input layer: Towns 2nd layer: Landfills Result: distance from each town to all landfills in table form

  39. Proximity tools - Buffering • A distance tool for points, lines, polygons • Create new polygon representing buffer distance(s) • Allows answering questions based on proximity • Inside or outside buffer polygon? 1 mile buffer around Blackwater River

  40. Additional resources Documentation (PDF files) • Included with ArcGIS installation • Access through help • Contents > Geoprocessing > Geo. Tool reference • ESRI Book: Geoprocessing in ArcGIS (PDF or hardcopy) ESRI Website • www.support.esri.com ESRI Classes • Geoprocessing with ArcGIS Desktop (Virtual Campus class) • Writing Advanced Geoprocessing Scripts with Python (Instructor led course)

  41. Lab 1 – Lesson 1 Geoprocessing • Load data into ArcMap • Simple geoprocessing – dissolve • Proximity tools – buffer • Overlay/extract tools – clip • Overlay/extract tools – intersect • Extra questions • Adding XY centroid • Additional proximity tools • Advanced intersect example • Adding/updating area, length, perimeter attributes

  42. Customizing ArcGIS and the Model Builder Lab 1. Lesson 2.

  43. Lesson 2 overview • Customizing the ArcGIS interface • ArcGIS settings and options • Creating a model • Running a model

  44. Customizing ArcGIS • Why customize the interface? • Personalize software for your needs • Load additional toolbars • Load “hidden” tools not already on toolbars • Group frequently used tools • How to customize the interface • Add toolbars • Add new tools already in ArcGIS • Load new tools from TBX (toolbox) or DLL (compiled code) • Write VBA scripts • Save your customizations

  45. Map Documents and Map Templates • Map Document (MXD) • Map Template (MXT) • MXD saves references to datasets used in layers, including file name • Map document properties include relative path name setting option

  46. Saving your customizations • Interface changes can be saved in three places: • Current map document (save as MXD File) • Map template (save as MXT File) • Normal.mxt (default map template on your computer)

  47. Types of models • Repetitive tasks • Minimize grunt work • Efficiently use frequently accessed tools • Suitability modeling • Find best locations • Process models • Custom models of complex interactions • Show landscape as conditions change (flood, fire etc)

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