nr 422 data types ii jim graham spring 2010. simple data types point (2d or 3d) –coordinates with...

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NR 422 Data Types II Jim Graham Spring 2010

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NR 422Data Types II

Jim Graham

Spring 2010

Simple Data Types• Point (2d or 3d)

– Coordinates with attributes

• Polyline (2d or 3d)– Points collected by line segments– 2 lines max per point

• Polygon (2d)– Closed polylines

• Rasters (2d, 3d elevations)– Points in a grid (one attribute or lookup)

• Triangulated Irregular Networks (2d or 3d)– 3 lines max per point

Triangulated Irregular Networks

• TINs

• A “mesh” of triangles

VerticesNodes

Edges, Line Segments, LinksArcs

TINs – Complex but Flexible

IDRISI

3d Graphic Solids are TINs!

• DEMs: 2 triangles per pixel

Topography: Atoll

Water Resource Management

Improving Environmental Site Management Through the Use of Internet ResourcesAuthors: Gary Whitton, Clayton Cranor, Michael Lilly, David Nyman

Applications

• Water resource management

• Water dynamics (tsunamis)

• Erosion

• Earthquakes

• “Volume” modeling in oceans

• Species relationships

• Decease transmission

Describing 3d Structures

• Contours: – Constant elevations– Variable horizontal resolution

• Rasters: Constant resolution– Variable elevations– Constant horizontal resolution

• TINs: – Variable elevations– Variable horizontal resolution

More Complex Data Types

• Features – Collections of points, polylines, polygons

• Networks– Related polylines and/or TINs

• Raster Mosaics– Overlapping rasters

• Spatial Databases/Datasets– All types and relationships

Complex Features

• Polyline– Rivers & Streams: Connected networks of

“reaches”– Attributes include: quantity of flow

• Polygons– Groups of islands: Hawaii– “Holes”:

• Lakes on surfaces• Islands on lakes

Networks

• Spatial, relationships, or both

• Basically large, complex polylines

• Or relationships

• Trophic relationships

• Bilogical Network Analyais– Gene flow

• Related to “Graph Theory”

Networks

• Streams and rivers– Water supply– Flood prediction– National Hydrology Network

• Transportation (mature):– Freeways, highways, and roads– Ships– Planes

• Disease vectors (developing)

• Natural Resource Management (new)

Problems

• Shortest path

• Network flow (traffic, water)

• Transport Problem: Optimal movement of goods

Shortest Path Problem

• What is the shortest path from 6 to 2?

• What is the shortest path to visit all nodes starting at 1?

Network Analysis

• Vertex: Sum of inputs and outputs = 0

• Edge: Has maximum capacity

• Source: Inputs to network

• Sink: Outputs from the network

Spread of Content in a Network

• Conserved:– Water– Soil– Nitrogen

• Non-Conserved:– Infectious deceases– Food (trophic levels)

Global Water Cycle

West Nile Virus

• US with crow migrations

Link Analysis

• Seeks relationships between lots of nodes in the network

• Banks, search engines, fraud, spamming

• Epidemiology

Trophic Relationships

• Network Analysis of the St. Marks Wildlife Refuge Seagrass Ecosystem.

http://core.ecu.edu/BIOL/luczkovichj/stmarks/stmarks.htm

Networks of Habitat Trees

• Networks of roosting trees for bats

• Brisbane, Australia

Social Networks

• Social networks of wildlife stakeholders: Insights from waterfowl hunting and furbearer trapping conflicts in New York

Network Analysis in NRM

• Social Movements and Ecosystem Services-the Role of Social Network Structure in Protecting and Managing Urban Green Areas in Stockholm

• Management of Natural Resources at the Community Level: Exploring the Role of Social Capital and Leadership in a Rural Fishing Community

• 'Who's in the Network?' When Stakeholders Influence Data Analysis

• http://www.springerlink.com/content/585x2t15n46739g6/

• stochastic network analysis

• Serfozo, R. 1999. Introduction to Stochastic Networks. Springer: New York.

• Sympatry Inference and Network Analysis in Biogeography