Extending Arc Views Spatial Analysis Capabilities Phil Hurvitz
Extending Arc. View’s Spatial Analysis Capabilities Phil Hurvitz College of Forest Resources University of Washington April 7, 2003
Extending Arc. View’s Spatial Analysis Capabilities Overview • Historical context of ESRI GIS spatial analysis tools • Limitations of Arc. Info/AML • Advantages of Arc. View/Avenue • Introducing 4 Arc. View/Avenue based extensions for spatial analysis • Conclusion © Phil Hurvitz 2
Extending Arc. View’s Spatial Analysis Capabilities Overview • Historical context of ESRI GIS spatial analysis tools • Limitations of Arc. Info/AML • Advantages of Arc. View/Avenue • Introducing 4 Arc. View/Avenue based extensions for spatial analysis • Conclusion © Phil Hurvitz 3
Extending Arc. View’s Spatial Analysis Capabilities Historical context of ESRI GIS spatial analysis tools • Arc. Info has dominated the GIS market for years (20+ years) • New software tools have become available more recently • More functionality in a more user-friendly environment • Arc. View (version 1. 0, 1993? ) • Arc. GIS (version 8. 0, 1999? ) © Phil Hurvitz 4
Extending Arc. View’s Spatial Analysis Capabilities Historical context of ESRI GIS spatial analysis tools Arc. Info interface Arc. View interface Arc. GIS interface © Phil Hurvitz 5
Extending Arc. View’s Spatial Analysis Capabilities Overview • Historical context of ESRI GIS spatial analysis tools • Limitations of Arc. Info/AML • Advantages of Arc. View/Avenue • Introducing 4 Arc. View/Avenue based extensions for spatial analysis • Conclusion © Phil Hurvitz 6
Extending Arc. View’s Spatial Analysis Capabilities Limitations of Arc. Info/AML • Arc. Info is a very robust environment for spatial analysis • AML (Arc Macro Language) provides a programming environment for automating functionality • AML is a procedural language-based (macro) API for development of applications • + As users become better at the command line, their programming/command skills will increase • – If users do not start programming, their programming/procedure skills will never increase beyond a very basic level • – Procedural languages are not compiled, so their programs run slowly © Phil Hurvitz 7
Extending Arc. View’s Spatial Analysis Capabilities Limitations of Arc. Info/AML (continued) • – AML is “clunky” • Basic dialogs do not exist • File saving, file writing, feature/record selections, graphical symbol definition • File locations are difficult to handle • Hard-coded pathnames are easier to program • Hard-coded pathnames reduce flexibility • – AMLs are completely file-based • AMLs exist as separate files that must be managed • Files can get corrupted, incorrectly altered, or lost without proper management • Inter-application macros must refer to specific AML files/pathnames © Phil Hurvitz 8
Extending Arc. View’s Spatial Analysis Capabilities Limitations of Arc. Info/AML (continued) • – Because Arc. Info has no GUI, associating scripts with buttons or menus requires Arc. Tools programming • – Arc. Tools provides an API for creating GUIs • The Arc. Tools API is very difficult to code • Arc. Tools still runs on an AML back-end, which is slow © Phil Hurvitz 9
Extending Arc. View’s Spatial Analysis Capabilities Overview • Historical context of ESRI GIS spatial analysis tools • Limitations of Arc. Info/AML • Advantages of Arc. View/Avenue • Introducing 4 Arc. View/Avenue based extensions for spatial analysis • Conclusion © Phil Hurvitz 10
Extending Arc. View’s Spatial Analysis Capabilities Advantages of Arc. View/Avenue • Arc. View provides a new API: Avenue programming language with several major advantages (and a few drawbacks) • – Arc. View runs in native mode with no command line • API needs to be learned as an entire new environment • + Avenue is compiled code rather than procedural • Runs much faster © Phil Hurvitz 11
Extending Arc. View’s Spatial Analysis Capabilities Advantages of Arc. View/Avenue, continued • + Scripts can be easily associated with menus, buttons, and tools in the GUI • + Not file-based • Scripts are typically created & stored in projects rather than as stand-alone files • Scripts can be packaged in “Extensions, ” which provide complete application functionality as simple add-ins • Extension is a single OS file containing all necessary scripts & GUI controls © Phil Hurvitz 12
Extending Arc. View’s Spatial Analysis Capabilities Overview • Historical context of ESRI GIS spatial analysis tools • Limitations of Arc. Info/AML • Advantages of Arc. View/Avenue • Introducing 4 Arc. View/Avenue based extensions for spatial analysis • Conclusion © Phil Hurvitz 13
Extending Arc. View’s Spatial Analysis Capabilities Introducing 4 Arc. View/Avenue based extensions for spatial analysis • • © Phil Hurvitz Line. Slope Analyst LMS Analyst Focal. Patch Analyst WBC Analyst 14
Extending Arc. View’s Spatial Analysis Capabilities Introducing 4 Arc. View/Avenue based extensions for spatial analysis • • © Phil Hurvitz Line. Slope Analyst LMS Analyst Focal. Patch Analyst WBC Analyst 15
Extending Arc. View’s Spatial Analysis Capabilities Line. Slope Analyst 200 ft 205 ft • Stream or road gradient is an important metric in hydrology & forest engineering • Gradient is easily calculated on a segment-bysegment or line-by-line basis slope % = rise / run * 100% (205 – 200) / 30 * 100% = 16. 7% 30 ft © Phil Hurvitz 16
Extending Arc. View’s Spatial Analysis Capabilities Line. Slope Analyst • Although gradient is easily calculated on a segmentby-segment or stream-by-stream basis, it takes programming to calculate gradient for an entire stream data set. © Phil Hurvitz 17
Extending Arc. View’s Spatial Analysis Capabilities Line. Slope Analyst • Line. Slope Analyst Extension adds a single button to calculate gradient for any linear feature © Phil Hurvitz 18
Extending Arc. View’s Spatial Analysis Capabilities Line. Slope Analyst © Phil Hurvitz 19
Extending Arc. View’s Spatial Analysis Capabilities Introducing 4 Arc. View/Avenue based extensions for spatial analysis • • © Phil Hurvitz Line. Slope Analyst LMS Analyst Focal. Patch Analyst WBC Analyst 20
Extending Arc. View’s Spatial Analysis Capabilities LMS Analyst • The Landscape Management System (LMS) is an integrated forest growth model, visualization, and analysis application • Incorporates GIS data in several modules • En. Vision or SVS visualization module • Tree list expansion factors (rely on stand area) • Growth models (require stand-level topographic characteristics) © Phil Hurvitz 21
Extending Arc. View’s Spatial Analysis Capabilities LMS Analyst • Stand topographic metrics are needed for growth models • • © Phil Hurvitz Mean elevation per stand Mean slope per stand Mean aspect per stand USGS or Li. DAR based DEMs can be used to calculate these metrics 22
Extending Arc. View’s Spatial Analysis Capabilities LMS Analyst © Phil Hurvitz 23
Extending Arc. View’s Spatial Analysis Capabilities LMS Analyst: Mean Elevation • Mean elevation is a simple calculation © Phil Hurvitz 24
Extending Arc. View’s Spatial Analysis Capabilities LMS Analyst: Mean Slope • Mean slope is a simple calculation © Phil Hurvitz 25
Extending Arc. View’s Spatial Analysis Capabilities LMS Analyst: Mean Aspect • Mean aspect is not a simple calculation • 359º = nearly due north • 1º = nearly due north • ( 359º + 1º ) / 2 = 180º • Nearly due south! 359º 1º 180 º • Must convert values to radian measures and use a more complicated calculation • Algebraic & trigonometric functions are available in Arc. View © Phil Hurvitz 26
Extending Arc. View’s Spatial Analysis Capabilities LMS Analyst: Mean Aspect • Mean aspect is not is a simple calculation custom calculation © Phil Hurvitz 27
Extending Arc. View’s Spatial Analysis Capabilities LMS Analyst: Multiple nested buffers • Forests & Fish rules require multiple nested riparian buffers • Arc. View includes a simple buffer method • Single buffers • Nested buffers, but only at equal-width • Nested buffers required by F&F are not equalwidth • LMS Analyst Multi. Buffer creates multiple nested buffers at users’ definition © Phil Hurvitz 28
Extending Arc. View’s Spatial Analysis Capabilities LMS Analyst: Multiple nested buffers © Phil Hurvitz 29
Extending Arc. View’s Spatial Analysis Capabilities Introducing 4 Arc. View/Avenue based extensions for spatial analysis • • © Phil Hurvitz Line. Slope Analyst LMS Analyst Focal. Patch Analyst WBC Analyst 30
Extending Arc. View’s Spatial Analysis Capabilities Focal. Patch Analyst • FRAGSTATS is commonly used to calculate spatial metrics for landscapes, patches, or classes • FRAGSTATS as originally written calculates metrics only for the entire landscape or for entire or specific patches • What are the landscape characteristics in a neighborhood around a specific location? • How do neighborhood landscape characteristics change across large landscapes? © Phil Hurvitz 31
Extending Arc. View’s Spatial Analysis Capabilities Fragstats • Patch metrics © Phil Hurvitz (image from Fragstats manual) 32
Extending Arc. View’s Spatial Analysis Capabilities Fragstats • Class metrics © Phil Hurvitz (image from Fragstats manual) 33
Extending Arc. View’s Spatial Analysis Capabilities Fragstats • Landscape metrics © Phil Hurvitz (image from Fragstats manual) 34
Extending Arc. View’s Spatial Analysis Capabilities Focal Functions in GIS • Processing occurs on a central cell in conjunction with the values associated in its neighborhood • “Moving window” • “Kernel” © Phil Hurvitz 35
Extending Arc. View’s Spatial Analysis Capabilities Focal. Patch Analyst • On a cell-by-cell basis • Creates a point feature at the cell center • Extracts the region in a user-specified radius around the point • Calculates landscape metrics for that circle • Places metrics back into point attribute table • Point data can be interpolated to create different surfaces of each different focal landscape metric © Phil Hurvitz 36
Extending Arc. View’s Spatial Analysis Capabilities Focal. Patch Analyst • Extracts circular region from land cover grid at user-defined radius © Phil Hurvitz 37
Extending Arc. View’s Spatial Analysis Capabilities Focal. Patch Analyst • Calculates landscape metrics Rempel’s interface © Phil Hurvitz Rempel’s batch script 38
Extending Arc. View’s Spatial Analysis Capabilities Focal. Patch Analyst • Calculates landscape metrics • Values represent the landscape metrics for the circular focal region around the central cell © Phil Hurvitz 39
Extending Arc. View’s Spatial Analysis Capabilities Patch Metrics and Utilization Distributions • Some animal species respond to large regions of landscapes • Typical animal-landscape relationships are analyzed either by point processes or by land cover types • Is there a relationship between local (focal) landscape metrics and actual animal usage of landscape? • To which landscape characteristics do animals respond? © Phil Hurvitz 40
Extending Arc. View’s Spatial Analysis Capabilities Patch Metrics and Utilization Distributions utilization distribution (UD) limit processing to UD © Phil Hurvitz 41
Extending Arc. View’s Spatial Analysis Capabilities Patch Metrics and Utilization Distributions utilization distribution © Phil Hurvitz contrast-weighted edge surface 42
Extending Arc. View’s Spatial Analysis Capabilities Patch Metrics and Utilization Distributions • Regression techniques are used to determine strength of relationship between utilization and landscape metrics • Multiple regression • Raster regression within GRID • Process described in paper submitted to Ecology (Marzluff et al. , 2003) © Phil Hurvitz 43
Extending Arc. View’s Spatial Analysis Capabilities Introducing 4 Arc. View/Avenue based extensions for spatial analysis • • © Phil Hurvitz Line. Slope Analyst LMS Analyst Focal. Patch Analyst WBC Analyst 44
Extending Arc. View’s Spatial Analysis Capabilities WBC Analyst • Do patterns of urban environmental structure have an effect on exercise? • Are particular urban settings more conducive to exercise? • “Walk Friendly” • “Bike Friendly” • Urban structure must be quantified before answering these questions • GIS provides the tools for quantifying the composition and configuration of urban structure © Phil Hurvitz 45
Extending Arc. View’s Spatial Analysis Capabilities WBC Analyst • Performs tasks that would be either impossible or extremely time-consuming manually • Analysis based on proximity to selected households • Based on Euclidean and network buffers, network connectivity © Phil Hurvitz 46
Extending Arc. View’s Spatial Analysis Capabilities WBC Analyst • Tallies land uses within user-specified distance of households • Finds closest of each land use type, by Euclidean and network distance © Phil Hurvitz 47
Extending Arc. View’s Spatial Analysis Capabilities WBC Analyst • Creates convex hull “neighborhood clusters” of key urban land uses (e. g. , grocery & retail stores) • Clusters are defined by particular land uses and numbers of parcels within a specific proximity © Phil Hurvitz 48
Extending Arc. View’s Spatial Analysis Capabilities WBC Analyst • Tallies land uses within neighborhood clusters • Determines Euclidean and network distances to each household’s closest neighborhood cluster © Phil Hurvitz 49
Extending Arc. View’s Spatial Analysis Capabilities WBC Analyst • Telephone survey has obtained personal exercise habits for 750 households in King Co. • WBC Analyst creates output tables to be used for statistical analysis with telephone survey results • If there is a relationship between urban structure and habits, it will be possible to predict the “walkability” and “bikeability” of neighborhoods based solely on readily available GIS data. • CDC funding for initial project © Phil Hurvitz 50
Extending Arc. View’s Spatial Analysis Capabilities Overview • Historical context of ESRI GIS spatial analysis tools • Limitations of Arc. Info/AML • Advantages of Arc. View/Avenue • Introducing 4 Arc. View/Avenue based extensions for spatial analysis • Conclusion © Phil Hurvitz 51
Extending Arc. View’s Spatial Analysis Capabilities Conclusion • New generation GIS environments coupled with powerful and extensible APIs hold much promise for creating science-based applications • Arc. GIS, with its COM API will allow even greater extensibility, allowing its object model to work with any other COM-compliant application (e. g. MS Office, next generation LMS & En. Vision) • Extensions allow applications to be used widely with little back-end configuration © Phil Hurvitz 52
Extending Arc. View’s Spatial Analysis Capabilities Conclusion • phurvitz@u. washington. edu • http: //gis. washington. edu/phurvitz © Phil Hurvitz 53
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