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Spatial and Physical Models Related to Processes across the Landscape Miles Logsdon [email protected] OR How will GIS and RS help in Salmon Modeling OR Why is Miles Talking about Fish?

OR How will GIS and RS help in Salmon Modeling OR Why is Miles Talking about Fish?

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Spatial and Physical Models Related to Processes across the Landscape Miles Logsdon [email protected]. OR How will GIS and RS help in Salmon Modeling OR Why is Miles Talking about Fish?. “Our” agenda. What is GIS ? - PowerPoint PPT Presentation

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Page 1: OR How will GIS and RS help in Salmon Modeling OR Why is Miles Talking about Fish?

Spatial and Physical Models Related to

Processes across the LandscapeMiles Logsdon

[email protected]

ORHow will GIS and RS help in Salmon Modeling

ORWhy is Miles Talking about Fish?

Page 2: OR How will GIS and RS help in Salmon Modeling OR Why is Miles Talking about Fish?

“Our” agendaWhat is GIS?What is the difference between a Spatial model and a Spatial Explicit ModelWhat is a theoretical basis for the application of GIS and spatial data analysis in modeling?What model “methods” or “tools” directly apply to Landscape processes?

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QuestionsFor Miles:

How can these central landscape features be described and linked to a fish-habitat model? - with a lot of workWhat are the 2 (or 3 or 4) biggest sources of uncertainty in making predictions about how Spatial Data Analysis affects salmon - meWhat 2 (or 3 or 4) alternative scenarios of current or future conditions would you suggest should be explored to make our model predictions about the effects of habitat change on salmon more robust to uncertainties? – full funding of my research.

See final slide for more complete responses

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My agenda

Show you pretty picturesTalk about “stuff” I enjoyJustify Spatial analysis as a field of study

Spatial InformationTechnologies

GIS - GPS – Remote Sensing

http://boto.ocean.washington.edu/oc_gis_rs

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Spatial Information TechnologiesGeographic Information Systems – GISGlobal Positioning System – GPSRemote Sensing and Image Processing - RS

Technologies to help answer:What is “here”? … give a position What is “next” to “this”? … given some descriptionWhere are all of the “???” … detecting or findingWhat is the spatial pattern of “???”When “X” occurs here, does “Y” also occur?

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GIS Geographic Information System

GIS - A system of hardware, software, data, people, organizations and institutional arrangements for collecting, storing, analyzing, and disseminating information about areas of the earth. (Dueker and Kjerne 1989, pp. 7-8)

GIS - The organized activity by which people •Measure aspects of geographic phenomena and processes; •Represent these measurements, usually in a computer database;•Operate upon these representations; and •Transform these representations. (Adapted from Chrisman, 1997)

A KEY POINT: Geo-referenced Data

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RS: Remote SensingRemote Sensing is a technology for sampling radiation and force fields to acquire and interpret geospatial data to develop information about features, objects, and classes on Earth's land surface, oceans, and atmosphere (and, where applicable, on the exterior's of other bodies in the solar system). Remote Sensing is detecting and measuring of electromagnetic energy (usually photons) emanating from distant objects made of various materials, so that we can identify and categorize these object by class or type, substance, and spatial distribution.

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Suggested ReadingChrisman, Nicholas, 1997, “Exploring Geographic Information Systems”, John Wiley & Sons,

Burrough, P. A., 1986, “Principles of Geographical Information Systems for Land Resources Assessment”, Monographs on Soil and Resources Servey #12, Oxford Science Publications

Miller, Roberta Balstad, 1996, "Information Technology for Public Policy", in GIS and Environmental Modeling: Progress and Research Issues, editors, Michael F. Goodchild, Louis T. Steyaert, Bradley O. Parks, Carol Johnston, David Maidment, Michael Crane, and Sandi Glendinning, GIS World Books.

Goodchild, Michael F., "The Spatial Data Infrastructure of Environmental Modeling", in GIS and Environmental Modeling: (see above).

Faber, G. Brenda, William W. Wallace, Raymond M. P. Miller, "Collaborative Modeling for Environmental Decision Making", proceedings of the GIS'96 Tenth Annual Symposium on Geographic Information Systems, Vancouver, B.C., March 1996.

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The larger context

(Chrisman, 1997)

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INT

EG

RA

TIO

N

IntegratedSystemModel

SystemModels

Process Models

DataModels

PRISMPRISM

MM5MM5 DHSVMDHSVM POMPOM CRYSTALCRYSTAL UrbanSimUrbanSim

……. …….. Soil Texture Geology Elevation Stream Network TemperatureRainfall

……. ….. Population Land Cover Water usage Stream Flow Salinityland ownership

Slope SatiabilitySlope Satiability

Population GrowthPopulation Growth

Land Cover ChangeLand Cover Change

Water Supply & DemandWater Supply & Demand

EvapotranporationEvapotranporation

.ETC.ETC

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INT

EG

RA

TIO

N

DataModels

Process Models

SystemModels

IntegratedSystemModel

PRISM

DataModels

Process Models

SystemModels

IntegratedSystemModel

PRISM

DataModels

Process Models

SystemModels

IntegratedSystemModel

PRISM

elevation

wind

landcover

elevation

wind

landcover

elevation

wind

landcover

TIME – Understanding?

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Biophysical Data Layers

Energy BalanceSoils

Temperature

Precipitation

Vegetation

Land Use

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Concept of Spatial Objects

POINTS

LINES

AREA

0 00

00 0 0

01

POINT

1

0

1

11

0 0

00

0

5 5 3

3311 2

LINE

AREA

Raster Data Encoding

Vector Data Encoding

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VECTOR Data Model

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Vector - TopologyObject Spatial Descriptive

1

2 3

45

15

1211

10

123

x1,y1x2,y2x3,y3

123

12

12

12

12

VAR1 VAR2

VAR1 VAR2

VAR1 VAR2

Fnode Tnode x1y1, x2y2

1 2 xxyy, xxyy2 3 xxyy,xxyy

10, 11, 12, 1510, …….

1

2 3

1

2

Data Relationships are invariant to translation and rotation

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RASTER Data Model

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Raster TopologyMap Algebra

In a raster GIS, cartographic modelingis also named Map Algebra.

Mathematical combinations of raster layers several types of functions: • Local functions – do not consult the 8 neighbors• Focal functions – function on the “kernel” of neighboring cells• Zonal functions – function on cells that test true in a different layer• Global functions – based upon the distribution of “all” cells

Functions can be applied to one or multiple layers

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Focal Function: Examples

2 0 1 1

2 3 0 4

2 1 1 2

2 3 3 2

2 0 1 1

2 3 0 4

4 2 2 3

1 1 3 2

•Focal Sum (sum all values in a neighborhood)

=

=

•Focal Mean (moving average all values in a neighborhood)

1.8 1.3 1.5 1.5

2.2 2.0 1.8 1.8

2.2 2.0 2.2 2.3

2.0 2.2 2.3 2.5

(3x3)

(3x3)12 13

17 19

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Digital Elevation Model – Raster Data Model

Thanks to David Maidment: http://www.ce.utexas.edu/prof/maidment

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D8 – Determine the Direction of flow

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Assign a value to indicate the direction of flow. Then for each cell determine the number of cell “upstream”

Set a threshold for the minimum value of flow accumulation which defines a stream

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Data Modeling Issues for hydrologyData Modeling Issues for hydrology

Spatial and temporal scaleSpatial and temporal scaleIrrigationIrrigationDiversionsDiversionsImpoundmentImpoundmentUrban water useUrban water useOther urbanization effectsOther urbanization effects

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Temporal Averaging:Temporal Averaging:Example: 1-month rainfallExample: 1-month rainfall

Evaporation and discharge modeled as functions Evaporation and discharge modeled as functions of soil moisture contentof soil moisture contentHow to handle long-interval (1-month) RF?How to handle long-interval (1-month) RF?Constant (drizzle) or One Big EventConstant (drizzle) or One Big EventDrizzle: ET too high, Discharge too lowDrizzle: ET too high, Discharge too lowBig Event: ET too low, Discharge too highBig Event: ET too low, Discharge too high

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Urbanization EffectsUrbanization Effects

Water Use: How much outdoor use?Water Use: How much outdoor use?Waster Water: How disposed?Waster Water: How disposed?Urban HydrologyUrban Hydrology

Reduced infiltrationReduced infiltrationConcentration of waterConcentration of waterReduced ETReduced ET

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Satellite Remote Sensing

June 27, 2001

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Remote Sensingin brief

Thanks to Robin Weeks

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The “PIXEL”

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Ground Truth

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Classified Product

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Urban I (10-30% developed)Urban II (30-60%)Urban III (> 60%)Short GrassTall grassCrop/mixedIrrigated CropMixed WoodlandBog or MarshEvergreen ShrubConiferous IConiferous IIConiferous IIIConiferous IVDeciduous BroadleafNon-forested (Altered-unknown)Non-forested (Altered-shrub)Ice cap / GlacierWater

Prism ‘98 ClassifiedLandcover Snoqualmie Drainage Basin

Evaluating the Impact of Landscape Pattern on Watershed Hydrology

DOES PATTERN MATTER?

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Classified“real”

Random

Patchy Smooth

4 landscapes with different patterns

Same composition

12% more ForestsPatches

12% lessForestsPatches

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Accumulated Sum Difference (1990 – 1991): The Difference in the total amount of water flowing past the mouth of the basin between the “real” landscape (1998 classified) and the “simulated”pattern – Random, Patchy, and Smooth

Random - 1998

Patchy – 1998 more water

Smooth – 1998Less water

A 12% change in the forest composition, impacts the total accumulated flow to a greater degree then does a change in the pattern of the landscape with the same composition.

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1991

1998

Change in Landcover Through an Increase inImpervious Surfaces

Maplewood Creek – an Urban Watershed

LANDCOVER CHANGE

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1008060402000

20

40

60

80

100

120

140

cfs (91)cfs (98)cfs (Hist)

Dis

char

ge (

cfs)

Recurrence interval (years)

Assuming the same rainfall record we experienced between 1989 – 1991, The amount of Discharge at peak flow increased ~67% over historical conditions, and ~11% between 1991 - 1998

Historical

1991

1998

Maplewood Creek, of the Lower Cedar River

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Spatial Data Analysis

The accurate description of data related to a process operating in space, the exploration of patterns and relationships in such data, and the search for explanation of such patterns and relationships

Spatial Analysis vs. Spatial Data Analysis

Spatial Analysis = what is here, and where are all the X’s ???

Spatial Data Analysis = observation data for a process operating in space and methods are used to describe or explain the behavior, and/or relationship with other phenomena.

SUMMARY POINTS

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QuestionsFor Miles:

How can these central landscape features be described and linked to a fish-habitat model? – spatially explicit definition of objects and processes that are consistent with spatially reference data modelsWhat are the 2 (or 3 or 4) biggest sources of uncertainty in making predictions about how Spatial Data Analysis affects salmon – data definition and/or data resolutionWhat 2 (or 3 or 4) alternative scenarios of current or future conditions would you suggest should be explored to make our model predictions about the effects of habitat change on salmon more robust to uncertainties? – Does Pattern Matter? Does a change in configuration of landcover produce a change in function of the landscape for a give process.