Characterizing, measuring and visualizing forest resources An inadequate treatment by an unqualified...

Characterizing, measuring and

visualizing forest resourcesAn inadequate treatment by an unqualified

presenter.

Things in this talk

• Remote Sensing 001

• Ways We’re Measuring Forests at UConn

• Quick Note on Visualization

Geospatial Technologies

• Geographic Information Systems (GIS)

• Remote Sensing (RS)

• Global Positioning Systems (GPS) • Internet

Remote sensing is the art and science of detecting, identifying, classifying, and analyzing the earth’s surface using special sensors onboard airplanes

and satellites.

And since we’re talking forest

rather than trees…

Landscape Features Reflect Light Differently

Band

Value

Band

Value

Examples of RS Data Imagery

Land Cover

Elevation

RS Imagery

• General reference/Base mapping

• Visual background to other data

• Digitize new data• Update existing data

What is land cover?

RS image Land cover map

39% forest

21% developed

16% wetla

nd

Land Cover vs Land Use

• Land Cover: Literally, what is covering the land (forest, wetland, pavement)

• Land Use: What is planned, practiced or permitted on a given area (commercial, residential, dedicated open space)

Things in this talk

• Remote Sensing 001

• Ways We’re Measuring Forests at UConn

• Quick Note on Visualization

Analysis & Characterization

Forest cover maps Forest block maps Forest fragmentation

analysis Distance from a road

analysis Buffer analysis

2002 Land cover

Forest 56%

Water3%

Wetland4%Other

2%Developed

19%

Turf/Grass4%

Grasses/Ag12%

Coniferous Forest

Deciduous Forest

Forested Wetland

Water

Non-forest

2002 Land cover: forest only(and

water)

Town of Coventry: 67% forested

2002 Forest Cover: by town

Tolland County: 68% forested

2002 Forest Cover: by county

Willimantic Regional Basin: 73% forested

2002 Forest Cover: by watershed

Forest Cover: Advantages

• Easy to understand• Total cover relates to

watershed research, possible watershed plan goals

• Can easily fit into “Basic NEMO” educational approach

Analysis & Characterization

Forest cover maps Forest block maps Forest fragmentation

analysis Distance from a road

analysis Buffer analysis

Forest Block Analysis

• Isolate forest cover• Remove any polygons smaller than

the size of interest• Block size is key for birds and

others– Considerable evidence that powerline corridors

and roads reduce the quality of habitat for many species of forest birds in the surrounding habitat

– Powerlines appear to be a conduit that brings predators and cowbirds deep into the forest interior

Forest Blocks – by Town

Town of Coventry

Forest Blocks – by County

Tolland County

Forest Blocks – by Watershed

Willimantic Regional Basin

Forest Block: Advantages

• Easy to generate once you have cover data

• Relates well to specific habitat concerns

• Allows the important distinction between amount of forest and amount of usable forest for wildlife

Analysis & Characterization

Forest cover maps Forest block maps Forest fragmentation

analysis Distance from a road

analysis Buffer analysis

• Original method developed by Riitters et al. (2000) of the USDA/USFS to assess global forest fragmentation from 1 km land cover data.

• Adapted by CLEAR for use on Landsat-derived land cover information (30-meter spatial resolution).

UConn CLEAR FF Analysis

Pixel-by-pixel analysis

A moving analysis window (9x9 is shown) is used to look at each center pixel in relation to all the surrounding pixels.

Forest Pixel Non-Forest Pixel

• Core Forest - all surrounding grid cells are forest.

• Perforated Forest - the interior edge of a forest tract such as would occur around a small clearing or house lot.

• Edge Forest - grid cell is on the exterior edge of a forest tract such as would occur along a large agricultural field or urban area.

• Transitional Forest - about half of the surrounding grid cells are forest.

• Patch Forest - less than 40% of surrounding grid cells are forest.

Forest Classes

• Core Forest - all surrounding grid cells are forest.

• Perforated Forest - the interior edge of a forest tract such as would occur around a small clearing or house lot.

• Edge Forest - grid cell is on the exterior edge of a forest tract such as would occur along a large agricultural field or urban area.

• Transitional Forest - about half of the surrounding grid cells are forest.

• Patch Forest - less than 40% of surrounding grid cells are forest.

Forest Classes

• Core Forest - all surrounding grid cells are forest.

• Perforated Forest - the interior edge of a forest tract such as would occur around a small clearing or house lot.

• Edge Forest - grid cell is on the exterior edge of a forest tract such as would occur along a large agricultural field or urban area.

• Transitional Forest - about half of the surrounding grid cells are forest.

• Patch Forest - less than 40% of surrounding grid cells are forest.

Forest Classes

• Core Forest - all surrounding grid cells are forest.

• Perforated Forest - the interior edge of a forest tract such as would occur around a small clearing or house lot.

• Edge Forest - grid cell is on the exterior edge of a forest tract such as would occur along a large agricultural field or urban area.

• Transitional Forest - about half of the surrounding grid cells are forest.

• Patch Forest - less than 40% of surrounding grid cells are forest.

Forest Classes

• Core Forest - all surrounding grid cells are forest.

• Perforated Forest - the interior edge of a forest tract such as would occur around a small clearing or house lot.

• Edge Forest - grid cell is on the exterior edge of a forest tract such as would occur along a large agricultural field or urban area.

• Transitional Forest - about half of the surrounding grid cells are forest.

• Patch Forest - less than 40% of surrounding grid cells are forest.

Forest Classes

Forested area: 1,886,426 acres = 59.3% of CT

2002

Forest Cover Map

Core Forest: 576,764 acres = 18.1% of CT

( 9x9 analysis window )

Forest Fragmentation Map

2002

Forest Blocks – by Town

Developed 2672

Non-forest 5098

Water 546

Core/Interior Forest

3461

Perforated Forest

4876

Edge Forest 5724

Transitional Forest

1780

Patch Forest 548

Forest Blocks – by County

Developed 32439

Non-forest 47377

Water 6065

Core/Interior Forest

57771

Perforated Forest

50610

Edge Forest 53491

Transitional Forest

14505

Patch Forest 5490

Forest Blocks – by Watershed

Developed 16372

Non-forest 20325

Water 3209

Core/Interior Forest

30216

Perforated Forest

29549

Edge Forest 31042

Transitional Forest

7780

Patch Forest 2325

Forest Frag: Advantages

• Provide data about quality as well as quantity of forest

• Can be run at different scales/grid sizes depending on concerns

• Tells you something about pattern of the forested landscape and its suitability for habitat

Forest Cover

• all based on the same input data (land cover)

• best use(s) for each???

Forest Cover Forest BlocksForest Fragmentation

The Forest Frag Wizard!

There are many other Forest Fragmentation

tools out there

Analysis & Characterization

Forest cover maps Forest block maps Forest fragmentation

analysis Distance from a road

analysis Buffer analysis

100 feet

5400 feet

Distance of Forest From Roads

A nationwide study by Foreman (2000)

estimates that 22% of total land area is affected

ecologically by roads (within 100m of roads).

Analysis & Characterization

Forest cover maps Forest block maps Forest fragmentation

analysis Distance from a road

analysis Buffer analysis

Land Cover Within Buffers

Land Cover Within Buffers

100 ft 200 ft 300 ft

What we measured

“Natural Vegetation”

Developed

Turf & Grass

Other Grasses & Ag.

Deciduous Forest

Coniferous Forest

Water

Forest Wetland

Non-forested Wetland

Tidal Wetland

Barren

Utility Right-of-way

25 Basins with greatest Natural Vegetation loss

(percent) 1985-2002

Combined Indicators of

Stream Health

Stream Health

% Impervious Watershed

% Natural Veg. 100 ft riparian buffer

Excellent <= 6% >= 65%

Good <=10% >=60%

Fair 10-25% 40-60%

Poor >25% <40%

After Goetz et al., 2003

Vis

uali

zat

ion

Stupid PPT & Photoshop Tricks

Stupid PPT & Photoshop Tricks

Economic modeling

Web Tools

Build Out AnalysisArcGIS and Scenario360

Potential New Homes

Google EarthResidential buildout

analysis

Are you insinuating that my talk wasn’t all it was supposed to be??!