Comparison of the Comparison of the New Jersey Landscape New Jersey Landscape

Alison BurnettAlison BurnettMark June-WellsMark June-Wells

December 13, 2006December 13, 2006

QuestionsQuestions

How do multi-fractal, random, and a NJ How do multi-fractal, random, and a NJ map relate at the landscape scale?map relate at the landscape scale?

In what landscape characteristics does In what landscape characteristics does the NJ map differ from the two random the NJ map differ from the two random maps?maps?

What can class-level indices tell us What can class-level indices tell us about the spatial distribution of NJ state about the spatial distribution of NJ state patches vs. random patch distribution.patches vs. random patch distribution.

HypothesisHypothesis NJ State map will differ significantly NJ State map will differ significantly

from both random and multi-fractal from both random and multi-fractal random maps for the measured random maps for the measured indices at the class and landscape indices at the class and landscape levels.levels.

ConsiderationsConsiderations

Equal probability inputs for random Equal probability inputs for random map classes…Nature is not random.map classes…Nature is not random.

Shape of NJ State vs. rectangle.Shape of NJ State vs. rectangle.

M&M ProgramsM&M ProgramsRULERULE

RULE:RULE: Generate a series of random maps.Generate a series of random maps. Rows = 274; Columns = 148Rows = 274; Columns = 148 34 classes – probability for each = .02934 classes – probability for each = .029 Nearest Neighbor Rule 1 chosenNearest Neighbor Rule 1 chosen No analysis…output as ASCIINo analysis…output as ASCII Multifractal Map was created using 8 Multifractal Map was created using 8

levels and an h=.5levels and an h=.5

M&M ProgramsM&M ProgramsArcArc

Converted all ascii files or NJ, Converted all ascii files or NJ, Random, and Multifractal maps to Random, and Multifractal maps to grid files for analysis.grid files for analysis. I love ARC!!!!I love ARC!!!!

M&M ProgramsM&M ProgramsFragstatsFragstats

Fragstats:Fragstats: Conducted basic analysis at the class Conducted basic analysis at the class

and landscape levels with a broad and landscape levels with a broad assemblage of indices.assemblage of indices.

Neighbor Rule of 4Neighbor Rule of 4 Parameters were chosen based on Parameters were chosen based on

simplicity and efficacy of design.simplicity and efficacy of design.

Fragstats ParametersFragstats ParametersLandscapeLandscape

Edge DensityEdge Density FRAC meanFRAC mean FRAC standard FRAC standard

deviationdeviation CONTIG meanCONTIG mean CONTIG std. dev.CONTIG std. dev.

PROX meanPROX mean PROX std. dev.PROX std. dev. COHESIONCOHESION

Fragstats Parameters Fragstats Parameters ClassClass

NPNP PDPD TETE PAFRACPAFRAC

PROX weighted meanPROX weighted mean PROX standard PROX standard

deviationdeviation CLUMPYCLUMPY COHESIONCOHESION

M&M ProgramsM&M ProgramsArcViewArcView

ArcView3: Made maps for visual purposes

Results- Landscape MetricsResults- Landscape Metrics

Map Type Edge Density

NJ 4.9

Random 19538.6

Multi-fractal 17821.8

NJ map significantly less than created NJ map significantly less than created mapsmaps

Expected result for NJExpected result for NJ Multi-fractal slightly less than randomMulti-fractal slightly less than random

Results- Landscape MetricsResults- Landscape Metrics

Map TypeFractal Dimension

mean std. dev.

NJ 1.0193 0.0316

Random 1.0626 0.2232

Multi-fractal 1.0745 0.1912

Subsets of geometrical space within which Subsets of geometrical space within which they residethey reside

Random/multi-fractal maps more complexRandom/multi-fractal maps more complex

Results- Landscape MetricsResults- Landscape Metrics

Map TypeContig

mean std. dev.

NJ 0.1221 0.1659

Random 0.0143 0.0445

Multi-fractal 0.0403 0.0778

High=clumped; low=disperseHigh=clumped; low=disperse Expected that NJ by more clumped Expected that NJ by more clumped Random least clumpedRandom least clumped

Results- Landscape MetricsResults- Landscape Metrics

Map TypeProximity

mean std. dev.

NJ 23.835 76.293

Random 0.695 0.209

Multi-fractal 0.991 0.474

Lower= more isolatedLower= more isolated Higher=more connectedHigher=more connected Also expected from NJ mapAlso expected from NJ map

Results- Landscape MetricsResults- Landscape Metrics

Map Type Cohesion

NJ 95.1672

Random 8.1095

Multi-fractal 19.9875

NJ’s classes are very connectedNJ’s classes are very connected Multi-fractals classes still more connected Multi-fractals classes still more connected

than randomthan random

Results- Class MetricsResults- Class MetricsRandom and Multi-fractalRandom and Multi-fractal

GeneralGeneral Random and multi-fractal maps show similar Random and multi-fractal maps show similar

values for each index across all patchesvalues for each index across all patches Random maps, 34 patch types, all the same Random maps, 34 patch types, all the same

probability probability As expected multi-fractal maps show higher As expected multi-fractal maps show higher

clumpiness and cohesion than random mapsclumpiness and cohesion than random maps Random map “total edge” values more Random map “total edge” values more

contiguous throughout class typescontiguous throughout class types ““Patch density” same for both maps, slightly Patch density” same for both maps, slightly

more evenly distributed for randommore evenly distributed for random ““Number of patches” for random map almost Number of patches” for random map almost

all the same; more variation in multi-fractalall the same; more variation in multi-fractal

Results- Class Metrics Results- Class Metrics NJ MapNJ Map

Patch Density significantly lower than Patch Density significantly lower than created mapscreated maps

Greater variation in total edge as Greater variation in total edge as compared to created mapcompared to created map

Proximity mean overall greater, showing Proximity mean overall greater, showing more connectedness of classesmore connectedness of classes

Fractal dimension Fractal dimension NOTNOT significantly significantly different across mapsdifferent across maps

Patch cohesion variable “could be” highly Patch cohesion variable “could be” highly correlated to patch typecorrelated to patch type Moderately developed- 95.426Moderately developed- 95.426 Estuarine marsh- 92.4115Estuarine marsh- 92.4115 Cultivated- 94.5218Cultivated- 94.5218 Golf courses- 7.933Golf courses- 7.933

ConclusionsConclusions

NJ map is significantly different than NJ map is significantly different than both random and multi-fractal maps both random and multi-fractal maps in class and landscape analysisin class and landscape analysis

Further, more rigorous investigation, Further, more rigorous investigation, would require producing a wider would require producing a wider variety of map types and imputing variety of map types and imputing real-life patch probabilities.real-life patch probabilities.

AcknowledgementsAcknowledgements

GIS lab people who let us in on GIS lab people who let us in on SaturdaySaturday

Software companiesSoftware companies FragstatsFragstats RuleRule ArcArc ArcView3ArcView3

Questions?Questions?