Spatial Analyst Identifying the Best Paths with Cost Distance Analysis. Kevin M. Johnston Elizabeth Graham

Transcription

1 Spatial Analyst Identifying the Best Paths with Cost Distance Analysis Kevin M. Johnston Elizabeth Graham

2 Cost distance analysis - Outline What is cost distance analysis Creating a cost surface Cost Analysis 1 - Cost Connectivity Demo Cost Analysis 2 - Two step process Cost Distance and Cost Path Demo Source characteristics and Network Analyst Demo Adding complexity and corridor analysis

3 What is cost distance analysis One of the most common applications in Spatial Analyst Euclidean distance as the crow flies Cost distance as the phenomenon moves across the landscape Euclidean is how far while cost analysis is a total amount Cost can be: - Preference - Energy expended - Time - Dollars - Risk

4 Problems addressed by cost distance analysis Constructing a road to a proposed shopping center Conserving wildlife corridors between habitat patches Supplying and reinforcing military troops in a deployment Providing movement paths for fire fighters between posts Locating a pipeline to connect energy fields to a refinery Siting electrical lines

5 Why do patches need to be connected? Fragmentation Metapopulation - Logging Roads - Supply routes for military locations - Fire fighting routes

6 Cost distance analysis - Outline What is cost distance analysis Creating a cost surface Cost Analysis 1 - Cost Connectivity Demo Cost Analysis 2 - Two step process Cost Distance and Cost Path Demo Source characteristics and Network Analyst Demo Adding complexity and corridor analysis

7 The problem Have series of locations - Habitat patches - Firefighting headquarters - Military installations Suitability model using Locate Regions tool or known locations Need to connect them the most effective way possible Cost distance analysis

8 Need a cost surface for movement Create a surface identifying the cost to move through each cell location Similar to creating a suitability model Cost per map unit to move through the cell The lower the cost the better Diagonal movement accounted for

9 How to create cost surface Define the problem (which includes creating submodels) Identify and derive the criteria Transform values to a common scale Weight the criteria relative to one another and combine Analyze the results

10 How to create cost surface Define the problem (which includes creating submodels) Identify and derive the criteria Transform values to a common scale Weight the criteria relative to one another and combine. Analyze the results

11 The input to cost distance analysis Define the problem (which includes creating submodels) Identify and derive the criteria Transform values to a common scale Weight the criteria relative to one another and combine. Analyze the results

12 Cost analysis 1 Cost Connectivity Input regions Input cost Create a network of paths - Output optimum paths - Optional neighboring paths

13 Cost Connectivity Optimum network Cost allocation identifies regions to connect Cost path connects neighbors - Base on cost not Euclidean distance Convert to graph theory - Nodes the regions - Edges the paths - Weights accumulative cost Maps back to paths A B C

14 Cost Connectivity Optimum network

15 Demo Creating the optimum network Creating a cost surface Cost Connectivity

16 Cost distance analysis - Outline What is cost distance analysis Creating a cost surface Cost Analysis 1 - Cost Connectivity Demo Cost Analysis 2 - Two step process Cost Distance and Cost Path Demo Source characteristics and Network Analyst Demo Adding complexity and corridor analysis

17 Two step process for performing cost distance analysis Cost Distance tool - Input - Sources starting point - Cost surface cost per map unit for travel - Output - Cost distance total accumulative least-cost for each cell to reach a source - Back link direction to move from each cell to reach a source - Cost allocation for each cell, which is the leastcost source Cost Path tool - Input - Destination ending point - Cost distance and Back link output rasters from Cost Distance tool - Output - Least-cost paths the least-cost paths

18 Use cases for two-step process Know the specific start and end locations Have two locations to connect Add a path to the Cost Connectivity network Connect location to several other locations

19 Step 1: How to perform the cost distance analysis The Cost Distance tool Sources Cost surface Output distance raster for each cell, the lowest total accumulative cost to reach a source

20 Step 1: How to perform the cost distance analysis The Cost Distance tool (continued) Back link Cost allocation

21 Step 2: How to create the least-cost path The Cost Path tool Destination and the cost distance and back link output from the Cost Distance tool Creates the least cost path from the destination to the sources - Best single path - Each zone - Each cell

22 Demo Creating the least-cost path Cost Distance Cost Path

23 Cost distance analysis - Outline What is cost distance analysis Creating a cost surface Cost Analysis 1 - Cost Connectivity Demo Cost Analysis 2 - Two step process Cost Distance and Cost Path Demo Source characteristics and Network Analyst Demo Adding complexity and corridor analysis

24 How cost distance analysis works accum_cost = a1 + (cost2 + cost3)/2 Where a1 The accumulative cost from cell 1 to cell 2 cost2 The cost of travel for cell 2 cost3 The cost of travel for cell 3 accum_cost The accumulative cost to move into cell 3 from cell 1

25 Source characteristics Multiplier - Different modes of travel from each source - an ATV versus walking - Different magnitudes at each source number of firefighters at each headquarter Start cost - Time it takes to prepare before leaving the source a1 = starting_cost + (((cost1 + cost2) / 2) * cost_multiplier) Resistance rate - A hiker getting tired Capacity - Identify potential locations for refueling stations for military tanks accum_cost = (a1 * (1 + resistance_rate)) + ((((cost2 * HF(2)) + (cost3 * HF(3)))/2) * Surface_distance(23) * VF(23) * cost_multiplier)

26 Source characteristics (cont.) Travel direction (From source and To source) - Bobcat, for security, prefer locations away from roads - Bobcat prefer locations that are easiest to access streams Travel from source a5 = c1 + c2 (1+r) + c3 (1+r) 2 + c4(1+r) 3 + c5(1+r) 4 Where a5 The least accumulative cost for the first five cells ci The cell identifier r The resistance rate Travel to source a5 = c1 (1+r) 4 + c2 (1+r) 3 + c3 (1+r) 2 + c4 (1+r) + c5

27 Cost Connectivity Neighbor paths and Network Analyst

28 Demo Controlling the mover Source Characteristics Network Analyst

29 Cost distance analysis - Outline What is cost distance analysis Creating a cost surface Cost Analysis 1 - Cost Connectivity Demo Cost Analysis 2 - Two step process Cost Distance and Cost Path Demo Source characteristics and Network Analyst Demo Adding complexity and corridor analysis

30 Adding complexity Adding surface distance with the Path Distance tool Actual distance traveled Endure the cost longer because going uphill or downhill Surface raster The Path Distance tool

31 Adding complexity Adding directionality with the Path Distance tool Cost adjustment to overcome going uphill and downhill Vertical factor - Surface raster endure cost longer - Vertical factor the additional cost to over come the slope

32 Adding complexity Adding directionality with the Path Distance tool Horizontal factor - Additional cost to overcome a horizontal factor such as wind Accum_cost_distance = a1 + (((Cost_Surface(b) * Horizontal_factor(b)) + (Cost_surface(c) * Horizontal_factor(c)))/2) * Surface_distance(bc) * Vertical_factor(bc)

33 Creating a cost corridor The Corridor tool Cost distance from source one Cost distance from source two Combine in the corridor tool Extract by Attribute tool to identify acceptable threshold

34 Additional resource Two case studies in the Find locations section of the case studies in the online help Cost distance analysis Case study with 4 lessons with data (ArcGIS desktop and Pro - Lesson 1: Creating a cost surface - Lesson 2: Creating an optimal connectivity network - Lesson 3: Creating a least cost path - Lesson 4: Creating a corridor

35 Additional resource Suitability modeling: Case study and 4 lessons with data - Lesson 1: Exploring and deriving data - Lesson 2: Transforming data onto a common scale - Lesson 3: Weighting and Combining Data - Lesson 4: Locating and connecting regions

36 Demo Directionality Path Distance Case studies and lessons Cost distance analysis Suitability modeling

37 Conclusion Defining the cost units can be difficult Can create the optimum network of paths Cost Connectivity - Compatible with Network Analyst Two step process Cost Distance and Cost Path - When source and destination known Source Characteristics - Difference modes of travel from a source - Starting costs - Dynamic adjustment getting tired Directionality Path Distance Creates the optimum least-cost solution - Assumes memory - Has visited all locations Acknowledgements: The Vermont Center for Geographic Information for the use of their data in this presentation

38 Other Spatial Analyst sessions Spatial Analyst: An Introduction - Tues 10:15 11:30 - Wed 10:15 11:30 Finding the Best Locations Using Suitability Modeling - Tues 1:30 2:45 - Thurs 8:30 9:45 Identifying the Best Paths with Cost Distance - Tues 3:15 4:30 - Wed 1:30 2:45 Suitability Modeling and Cost Distance Analysis Integrated Workflow (Demo Theater) - Wed 4:30 5:15 Python: Raster Analysis - Tues 8:30 9:45 Getting Started With Map Algebra Using the Raster Calculator and Python (Demo Theater) - Thurs 9:30 10:15 9

39 Other Spatial Analyst sessions Modeling Renewable Energy Potential Using ArcGIS (Demo Theater) - Tues 1:30 2:15 Creating Watersheds and Stream Networks - Wed 10:00 10:30 Hydrologic and Hydraulic Modeling - Wed 3:15 4:30 - Thurs 1:30 2:45 GIS Techniques for Floodplain Delineation (Demo Theater) - Tues 12:30 1:15 Creating a Hydrologically Conditioned DEM (Demo Theater) - Tues 10:30 11:15 Creating Surfaces from Various Data Sources - Tues 3:15 4:30 - Thurs 3:15 4:30 Choosing the Best Kriging Model for Your Data (Demo Theater) - Wed 11:30 12:15

40 Other Spatial Analyst sessions Surface Interpolation in ArcGIS (Demo Theater) - Thurs 10:30 11:15 Creating Watersheds and Stream Networks (Demo Theater) - Wed 10:00 10:30 Working with Elevation Services (Demo Theater) - Tues 10:30 11:15 - Wed 9:30 10:15 Building Python Raster Functions (Demo Theater) - Tues 10:30 11:15 Raster Analytics in Image Server: An Introduction - Wed 3:15 4:30 Raster Classification with ArcGIS Desktop (Demo Theater) - Thurs 9:30 10:15 Raster Function Processing (Demo Theater) - Thurs 10:30 11:15

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