Extending ArcView’s Spatial Analysis Capabilities

Extending ArcView’s Spatial Analysis Capabilities Phil HurvitzCollege of Forest ResourcesUniversity of Washington April 7, 2003

Overview • Historical context of ESRI GIS spatial analysis tools • Limitations of ArcInfo/AML • Advantages of ArcView/Avenue • Introducing 4 ArcView/Avenue based extensions for spatial analysis • Conclusion

Historical context of ESRI GIS spatial analysis tools • ArcInfo 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 • ArcView (version 1.0, 1993?) • ArcGIS (version 8.0, 1999?)

ArcInfo interface ArcViewinterface ArcGIS interface Historical context of ESRI GIS spatial analysis tools

Limitations of ArcInfo/AML • ArcInfo 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

Limitations of ArcInfo/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

Limitations of ArcInfo/AML (continued) • – Because ArcInfo has no GUI, associating scripts with buttons or menus requires ArcTools programming • – ArcTools provides an API for creating GUIs • The ArcTools API is very difficult to code • ArcTools still runs on an AML back-end, which is slow

Advantages of ArcView/Avenue • ArcView provides a new API: Avenue programming language with several major advantages (and a few drawbacks) • – ArcView 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

Advantages of ArcView/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

Introducing 4 ArcView/Avenue based extensions for spatial analysis • LineSlope Analyst • LMS Analyst • FocalPatch Analyst • WBC Analyst

205 ft 200 ft 30 ft LineSlope Analyst • Stream or road gradient is an important metric in hydrology & forest engineering • Gradient is easily calculated on a segment-by-segment or line-by-line basis slope % = rise / run * 100% (205 – 200) / 30 * 100% = 16.7%

LineSlope Analyst • Although gradient is easily calculated on a segment-by-segment or stream-by-stream basis, it takes programming to calculate gradient for an entire stream data set.

LineSlope Analyst • LineSlope Analyst Extension adds a single button to calculate gradient for any linear feature

LineSlope Analyst

LMS Analyst • The Landscape Management System (LMS) is an integrated forest growth model, visualization, and analysis application • Incorporates GIS data in several modules • EnVision or SVS visualization module • Tree list expansion factors (rely on stand area) • Growth models (require stand-level topographic characteristics)

LMS Analyst • Stand topographic metrics are needed for growth models • Mean elevation per stand • Mean slope per stand • Mean aspect per stand • USGS or LiDAR based DEMs can be used to calculate these metrics

LMS Analyst

LMS Analyst: Mean Elevation • Mean elevation is a simple calculation

LMS Analyst: Mean Slope • Mean slope is a simple calculation

359º 1º 180 º LMS Analyst: Mean Aspect • Mean aspect is nota simple calculation • 359º = nearly due north • 1º = nearly due north • ( 359º + 1º ) / 2 = 180º • Nearly due south! • Must convert values to radian measures and use a more complicated calculation • Algebraic & trigonometric functions are available in ArcView

custom calculation LMS Analyst: Mean Aspect • Mean aspect is not is a simple calculation

LMS Analyst: Multiple nested buffers • Forests & Fish rules require multiple nested riparian buffers • ArcView includes a simple buffer method • Single buffers • Nested buffers, but only at equal-width • Nested buffers required by F&F are not equal-width • LMS Analyst MultiBuffer creates multiple nested buffers at users’ definition

LMS Analyst: Multiple nested buffers

FocalPatch 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?

(image from Fragstats manual) Fragstats • Patch metrics

(image from Fragstats manual) Fragstats • Class metrics

(image from Fragstats manual) Fragstats • Landscape metrics

Focal Functions in GIS • Processing occurs on a central cell in conjunction with the values associated in its neighborhood • “Moving window” • “Kernel”

FocalPatch 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

FocalPatch Analyst • Extracts circular region from land cover grid at user-defined radius

Rempel’s batch script Rempel’sinterface FocalPatch Analyst • Calculates landscape metrics

FocalPatch Analyst • Calculateslandscape metrics • Values represent the landscape metrics for the circular focal region around the central cell

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?

utilization distribution (UD) limit processing to UD Patch Metrics and Utilization Distributions

utilization distribution contrast-weighted edge surface Patch Metrics and Utilization Distributions

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)

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

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

WBC Analyst • Tallies land uses within user-specified distance of households • Finds closest of each land use type, by Euclidean and network distance

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

WBC Analyst • Tallies land uses within neighborhood clusters • Determines Euclidean and network distances to each household’s closest neighborhood cluster

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

Extending ArcView’s Spatial Analysis Capabilities