A Preview of Recent Land Cover Mapping for Connecticut James D. Hurd Jason Parent, Anna Chabaeva and Daniel Civco Center for Land use Education And Research

A Preview of Recent A Preview of Recent Land Cover Mapping for Land Cover Mapping for

ConnecticutConnecticut

James D. HurdJames D. HurdJason Parent, Anna Chabaeva and Daniel CivcoJason Parent, Anna Chabaeva and Daniel Civco

CCenter for enter for LLand use and use EEducation ducation AAnd nd RResearch esearch (CLEAR)(CLEAR)

Department of Natural Resources Management & Department of Natural Resources Management & EngineeringEngineering

The University of ConnecticutThe University of Connecticut

U-4087, Room 308, 1376 Storrs RoadU-4087, Room 308, 1376 Storrs Road

Storrs, CT 06269-4087Storrs, CT 06269-4087







The Center for Landuse The Center for Landuse Education And Research Education And Research

(CLEAR)(CLEAR)

clear.uconn.edu

Established April, 2002


(CLEAR)(CLEAR)

clear.uconn.edu

Established April, 2002

CLEAR conducts remote sensing research, develops analysis tools and training programs, delivers outreach educational programs.


(CLEAR)(CLEAR)

To provide information, education and assistance to land use decision makers, in support of balancing growth and natural

resource protection.

clear.uconn.edu

NEMOLERIS

GVIForestr

y

National NEMO

Network

GTP

Connecticut’s Changing Connecticut’s Changing LandscapeLandscape

What is Connecticut’s Changing Landscape (CCL)?

- An ongoing project that tracks land cover changes in Connecticut’s landscape over time.

- Uses Landsat Satellite imagery to derive a consistent set of land cover maps.

- Currently nearing completion of a 2006 update.

- With the update, will consist of 5 dates of land cover (1985, 1990, 1995, 2002, 2006) consisting of 12 land cover categories.

- Also includes products derived from land cover: forest fragmentation, urban growth, impervious surfaces.


Land Cover and Land Cover Change

Urban Growth

ImperviousSurfaces

ForestFragmentation

clear.uconn.educlear.uconn.edu/ccl.htm

Land Cover andLand Cover andLand Cover ChangeLand Cover Change

Why Land Cover?Why Land Cover?

- Land Cover is the basis for understanding our - Land Cover is the basis for understanding our landscape.landscape.

What is where?What is where?

- - Multiple dates of land cover are necessary to Multiple dates of land cover are necessary to understand the nature of landscape change.understand the nature of landscape change.

What did it change to?What did it change to?

- Many landscape models require land cover - Many landscape models require land cover information.information.

You can measure & analyze this

This is a picture

33% 33% developeddeveloped

33% 33% developeddeveloped

46% 46% forestforest46% 46% forestforest

5% 5% waterwater5% 5%

waterwater

Image to MapImage to MapLandsat

Satellite ImageLand Cover

Map

Landsat 100 footspatial resolution

NAIP 3 footspatial resolution

Image ComparisonImage Comparison

Both images collected late summer 2006

Connecticut’s Changing Connecticut’s Changing LandscapeLandscape1985

1995

1990

2002


2006 Land Cover

DevelopedDeveloped

Turf & GrassTurf & Grass

Other GrassesOther Grasses

AgricultureAgriculture

Deciduous ForestDeciduous Forest

Coniferous ForestConiferous Forest

WaterWater

Forest WetlandForest Wetland

Non-forested Non-forested WetlandWetland

Tidal WetlandTidal Wetland

BarrenBarren

Utility Right-of-wayUtility Right-of-way

DevelopedDeveloped






WaterWater




BarrenBarren


Connecticut’s Changing Connecticut’s Changing LandscapeLandscape 1985 Land Cover

DevelopedDeveloped






WaterWater




BarrenBarren



DevelopedDeveloped






WaterWater




BarrenBarren



DevelopedDeveloped






WaterWater




BarrenBarren



DevelopedDeveloped






WaterWater




BarrenBarren



Increase In DevelopmentIncrease In Development

Developed 1985-1990Developed 1985-1990

Turf & Grass 1985-Turf & Grass 1985-19901990







1985 to 2006

DevelopedDeveloped


WaterWater

UndevelopedUndeveloped

No Change

Change to Developed

Change In AgricultureChange In Agriculture1985 to 2006

Agriculture to Agriculture to Developed/Turf & Developed/Turf & GrassGrass

Agriculture to Other Agriculture to Other GrassesGrasses

New AgricultureNew Agriculture

DevelopedDeveloped



WaterWater


Change in Agriculture

No Change

Agriculture and Forest LossAgriculture and Forest Loss1985 to 2006

Lost AgricultureLost Agriculture

Lost ForestLost Forest

Other Non-developed Other Non-developed ChangeChange

DevelopedDeveloped

WaterWater


Change Classes

No Change Classes

1985 Area

1990 Area

1995 Area

2002 Area

2006 Area

1985-2006 Change

(sq. miles)

(sq. miles)

(sq. miles)

(sq. miles)

(sq. miles)

(sq. miles) (%)

Developed 812.09 875.23 897.59 933.11 949.24 137.15 16.89

Turf & Grass 276.68 280.49 289.16 296.59 310.44 33.76 12.20

Other Grass 45.23 69.25 86.12 103.97 109.15 63.92 141.33

Agriculture 465.91 436.75 424.45 412.86 409.18 -56.73 -12.18

Deciduous Forest 2,470.08 2,409.53 2,373.37 2,327.54 2,298.20 -171.88 -6.96

Coniferous Forest

460.71 455.23 451.52 446.37 442.13 -18.58 -4.03

Water 174.33 171.89 167.36 159.87 158.22 -16.11 -9.24

Non-forest Wetland

11.61 18.17 20.07 23.49 25.62 14.00 120.61

Forested Wetland

186.00 179.09 175.68 174.23 171.43 -14.57 -7.83

Tidal Wetland 23.13 23.51 23.58 23.88 23.43 0.31 1.33

Barren 33.93 40.81 51.03 58.17 62.99 29.05 85.61

Utility ROWs 15.35 15.10 15.13 14.98 15.04 -0.31 -2.01


0

500

1,000

1,500

2,000

2,500

3,000

3,500

19851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007200820092010

YEAR

SQ

MIL

ES


Tracking ChangeTracking Change

R2 = 0.9722

R2 = - 0.9821

R2 = - 0.8956

FOREST = deciduous, coniferous, forested wetlandDEVELOPED = developed, turf & grassAGRICULTURE = agriculture

Forest FragmentationForest FragmentationAnalysisAnalysis

Forest FragmentationForest FragmentationForest FragmentationForest FragmentationOld Method: Image ConvolutionNew Method: Morphological Image Processing

= SE1 = SE2

erosion operator, dilation operator(shrink forest) (expand forest)

= calculate Pf and Pff

Core Forest – All pixels in SE1 are forest.

Analysis applied to the center forest pixel

Patch Forest – Forest pixels that are isolated from core forest pixels (uses SE2 with repeated dilations).

Forest FragmentationForest FragmentationForest FragmentationForest Fragmentation

Edge Forest – forest pixels on the edge of large non-forested features (uses SE1 on non-forest pixelswith repeated dilations).

Perforated Forest – forest pixels surrounding smallnon-forested features (remaining unlabeledforest pixels).

1985

1990

1995

2002

2006

Connecticut Forest Connecticut Forest FragmentationFragmentation

Connecticut Forest Connecticut Forest FragmentationFragmentation

1985 Area

1990 Area

1995 Area

2002 Area

2006 Area

1985-2006 Change

(sq. miles)

(sq. miles)

(sq. miles)

(sq. miles)

(sq. miles)

(sq. miles) (%)

Patch Forest 74.04 73.66 74.66 75.58 76.70 2.66 3.59

Perforated Forest

105.19 113.90 125.54 136.68 144.71 39.52 37.57

Edge Forest 683.23 689.16 694.68 704.87 712.02 28.78 4.21

Core Forest 2,267.93 2,167.28 2,105.87 2,031.11 1,975.02 -292.92 -12.92

Urban GrowthUrban GrowthAnalysisAnalysis

Urban Growth MetricsUrban Growth MetricsDerivationDerivation

Manifestation metrics based Manifestation metrics based on the “urbanness” of the on the “urbanness” of the neighboring areaneighboring area

Urbanness = % of pixels in Urbanness = % of pixels in neighborhood that are built-neighborhood that are built-upup

The neighborhood is a 1 kmThe neighborhood is a 1 km22 circle centered on each pixelcircle centered on each pixel 252 pixels = 0.2 km2

Urbanness = 0.2 / 1 = 20%

Urban Growth MetricsUrban Growth MetricsDefinitionsDefinitions

Built-up(developed pixels)

> 50% urban30 to 50%

urban < 30% urban

Largest contiguo

us group of

pixels

All other

groups

Linear semi-

contiguous groups approx.

100 meters wide

Main core Secondary core

Fringe Ribbon Scatter

All other

groups

Landsat image

Built-up area(impervious surfaces)

Open space (OS)(non-developed pixels)

Urbanized OS(> 50 % built-

up)

Urbanizedarea

Urbanfootprint

Peripheral OS(< 100 m from

built-up)

Urban Growth MetricsUrban Growth MetricsDefinitionsDefinitions

Urban Growth AnalysisUrban Growth Analysis

Urban CoreUrban Core

Urban FringeUrban Fringe

Urban ScatterUrban Scatter

Urbanized Open Urbanized Open SpaceSpace

Interior Urbanized OSInterior Urbanized OS

Peripheral Open Peripheral Open SpaceSpace

Core Open SpaceCore Open Space

WaterWater

Excess SlopeExcess Slope

1985 Urban Landscape

1985

1990

1995

2002

2006

URBAN FOOTPRINT = all built-up pixels (urban core, urban fringe, urban scatter) and urbanized open space pixels (urbanized open space, interior urbanized open space, peripheral open space).


1985

1990

1995

2002

2006

►Development occurring between time Development occurring between time periods Tperiods T11 and T and T22

► Classification based on location relative to Classification based on location relative to the Tthe T11 urban area urban area InfillInfill: new development occurring within the T: new development occurring within the T11

urbanized open spaceurbanized open space ExtensionExtension: new non-infill development : new non-infill development

intersecting the Tintersecting the T11 urban footprint urban footprint LeapfrogLeapfrog: new development not intersecting the : new development not intersecting the

TT11 urban footprint urban footprint



InfillInfill

ExtensionExtension

LeapfrogLeapfrog

1985to

2006

►Infill - development of a small area surrounded by existing developed land.

►Expansion - the spread of development from existing developed areas.

►Outlying - characterized by a change from undeveloped to developed beyond existing developed areas. Isolated – small developed area surrounded by

undeveloped land. Linear Branching – linear development

Clustered Branching – large cluster of developed pixels.



InfillInfill

ExpansionExpansion

IsolatedIsolated

LinearLinear

ClusteredClustered

1985to

2006

Impervious SurfaceImpervious SurfaceEstimationEstimation

Impervious Surfaces Impervious Surfaces EstimationEstimation

Regression analysis model based on the use of:

• Impervious surface coefficients for each land cover category.

• Population density within analysis unit being analyzed.

Impervious Surfaces Impervious Surfaces EstimationEstimation

RMSE=7.72y = 1.2479x - 2.0241

R2 = 0.95180

20

40

60

80

100

0 20 40 60 80 100

Actual %IS

CC

L S

ub

-pix

el %

IS

CCL Sub-pixelAnalysis

RMSE=6.30y = 0.7088x + 5.1551

R2 = 0.93510

20

40

60

80

100

0 20 40 60 80 100

Actual %IS

CC

L IS

AT

%IS

CCL ISAT

RMSE=4.73y = 0.8548x + 2.763

R2 = 0.92910

20

40

60

80

100

0 20 40 60 80 100

Actual %IS

CC

L E

TIS

%IS

CCL ETIS

2006 Impervious Surfaces2006 Impervious Surfaces2000 Census Tracts2000 Census Tracts

0% - 5% IS0% - 5% IS

5% - 10% IS5% - 10% IS

10% - 15% IS10% - 15% IS

15% - 20% IS15% - 20% IS

20% - 25% IS20% - 25% IS

> 25% IS> 25% IS

2006 Impervious Surfaces2006 Impervious SurfacesLocal WatershedsLocal Watersheds

0% - 5% IS0% - 5% IS

5% - 10% IS5% - 10% IS

10% - 15% IS10% - 15% IS

15% - 20% IS15% - 20% IS

20% - 25% IS20% - 25% IS

> 25% IS> 25% IS

In SummaryIn Summary

SummarySummaryThe land cover products allow us to quantify

land cover and land cover change in Connecticut over a 21 year period and allow us to visualize how we are impacting our landscape.

The derived products provide us with various perspectives about the state of Connecticut’s landscape.

Land Cover should be available online in the next month or so with the derived products following soon after.

CLEAR.uconn.eduCLEAR.uconn.edu

A Preview of Recent A Preview of Recent Land Cover Mapping for Land Cover Mapping for

ConnecticutConnecticut













Documents

A Preview of Recent Land Cover Mapping for Connecticut James D. Hurd Jason Parent, Anna Chabaeva and Daniel Civco Center for Land use Education And Research