Session 5
Forestry and Change Detection
CORSE 2000
June 26-29, 2000
University of Southern Mississippi
Gulf Park Conference Center
Daniel L. Civco
LERIS / NRME
University of Connecticut
Storrs CT 06269
dcivco@canr.uconn.edu
June 2000 Volume 98 Number 6
•Remote Sensing and Forestry: Collaborative
Implementation for a New Century of Forest
Information Solutions
•Foresters' Roles in Remote Sensing
•From Pixels to Decisions: Digital Remote
Sensing Technologies for Public Land
Managers
Remote Sensing Data Sources and Techniques
•Aerial Photography in the Next Decade
•Digital Imaging Basics for Natural Resource Managers
•Videography for Foresters
•The Earth Observing System and Forest Management
•Intermediate Multispectral Satellite Sensors
•Selecting and Interpreting High-Resolution Images
•Forest Information from Synthetic Aperture Radar
•Lidar Remote Sensing for Forestry
•Using Hyperspectral Data to Assess Forest Structure
•Map Data in Support of Forest Management
•Image and Spatial Analysis Software Tools
•Field Applications for Statistical Data and Techniques
•Integrating Data and Information for Effective Forest
Management
http://www.safnet.org/pubs/jof/index.html
•Remote Sensing and Forestry:
Collaborative Implementation for a New
Century of Forest Information Solutions
•Kathleen Bergen, John Colwell, & Frank Sapio
“ ... new forest management
paradigms and rapid
technological advances together
create an organizational and
technological challenge, as well
as a great opportunity for
advancing forestry.”
http://www.safnet.org/pubs/jof/index.html
•From Pixels to Decisions: Digital Remote
Sensing Technologies for Public Land
Managers
•Henry Lachowski, Paul Maud, and Norm Roller
“… forest managers need
information about the geospatial
infrastructure, including the
location, amount, and condition of
the forest’s natural and cultural
resources.”
http://www.safnet.org/pubs/jof/index.html
Deforestation is the
permanent destruction of
forests and woodlands.
The increasing population
requires greater food
production - deforestation
occurs as the forests are
converted for agricultural
and urban uses. In the
past three decades one
fifth of all tropical forests
were lost. Currently, 12
million hectares of forests
are cleared annually. Most
deforestation occurs in the
moist forests and open
woodlands of the tropics.
Deforestation
http://ps.ucdavis.edu/classes/ire001/env/deforest.htm
http://www.wri.org/forests/index.html
Deforestation in the Tropics
Landsat Image
Overview Map
Degree of Deforestation
http://www.dpi.inpe.br/Amazonia/pg13.html
Fragmentation
• Habitat Fragmentation, Modification or Loss Sources
of habitat fragmentation include:
– Agriculture: Conversion of prairie and forest areas to
intensive agriculture eliminates nesting cover.
– Forestry: Harvesting and regeneration modify the
forest landscape and alter the structural and plant
species diversity.
– Urbanization: Urban sprawl to accommodate a growing
human population progressively consumes natural areas.
– Linear development: Roads, pipelines and hydro rights-of-way
open up previously difficult-to-access territory to human use.
– Climate change: When growing conditions are altered, habitat
availability is affected, especially for species at the edge of
their range
http://www.cws-scf.ec.gc.ca/canbird/pif/habitat.htm
The Northeast Landscape
In the beginning, there was forest...
The Northeast Landscape
After near total conversion to farmland,
much forest has returned...
The Northeast Landscape
Now, farm and forest are being converted to
developed land, particularly subdivisions.
The Northeast Landscape
Is urban sprawl, deforestation, and habitat
fragmentation the future of the Northeast?
The Power to Visualize
wa*ter*shed n.
1. An area of
land draining to a
common outlet.
ZZZZZ...
The Power to Visualize
wa*ter*shed n. 1. An
area of land draining to
a common outlet.
HMMM...
The Power to Visualize
AWESOME !
AWESOME !
AWESOME !
The Power to Confuse
What the…?!
? ? ?
? ?
Picasso
What is a Watershed?
A Watershed is an area
of land that drains to a
single outlet.
3-D to drive home the point
3D Visualizations
ADAR
TM
DEM
Make the Obvious Even More Obvious
Thematic Mapper Band 6, Thermal, Resampled to 30 Meter Resolution
By enhancing visualization ...
3-D Surface of Temperature Differences
Warmer
Cooler
What are heat sinks?
What will reduce thermal gains?
Forest
Fragmentation
Roads are built.
Forest
Fragmentation
Developed areas
follow.
Forest
Fragmentation
Patches of
contiguous forest
become smaller.
Forest
Fragmentation
Forest resources
are fragmented.
“Let me see this fragmentation”
Multiresolution Comparison
Impervious
10
80
1
1
30
130
meterADAR
meter
meter
meter
meter
10
80
meter
1 meter
meter
meter
DOQ
SPOT
ADAR
MSS
overlay
TM
TMDOQ
SPOT
w/
w/
MSS
w/
7
w/
4band
impervious
band
from
impervious
impervious
panchromatic
impervious
multispectral
panchromatic
multispectral
multispectral
planimetric
overlay
overlay
overlay
overlay
data
Steamboat Willie
In 1928, Disney made history with the release of first talkie
animation film Steamboat Willie featuring Mickey Mouse.
.. and haven’t we come a long way since?
Mt Fuji volcano flyby created completely from ASTER data
http://terra.nasa.gov/Gallery/
Remote Sensing in Action:
The ASTER Sensor Aboard Terra
http://terra.nasa.gov/Gallery/
Remote Sensing in Action:
The MODIS Sensor Aboard Terra
http://terra.nasa.gov/Gallery/
Global Normalized Difference
Vegetation Index (NDVI)
http://terra.nasa.gov/Gallery/
Global Normalized Difference
Vegetation Index (NDVI)
http://terra.nasa.gov/Gallery/
Mount St. Helens
April 1980
May1980
June 1980
http://edcwww.cr.usgs.gov/earthshots/slow/MtStHelens/MtStHelens
Mount St. Helens
1973
1983
1988
1992
1996
Landsat MSS
http://edcwww.cr.usgs.gov/earthshots/slow/MtStHelens/MtStHelens
EarthShots
http://edcwww.cr.usgs.gov/earthshots/slow/tableofcontents
Rondonia, Brazil: 1975-1992
1975
1986
1992
http://edcwww.cr.usgs.gov/earthshots/slow/Rondonia/Rondonia
Fires in Wyperfeld National Park,
Victoria, Southeast Australia
1975
1985
1999
http://edcwww.cr.usgs.gov/earthshots/slow/Wyperfeld/Wyperfeld
Fires in Wyperfeld National Park
1979 to 1997
http://edcwww.cr.usgs.gov/earthshots/slow/Wyperfeld/Wyperfeld
Clearcutting Near Olympic
National Park, WA
http://svs.gsfc.nasa.gov/imagewall/LandSat/olympic.html
Clearcutting Near Olympic
National Park, WA
1986
1987
1988
1991
http://svs.gsfc.nasa.gov/imagewall/LandSat/olympic.html
Clearcutting Near Olympic
National Park, WA
http://svs.gsfc.nasa.gov/imagewall/LandSat/olympic.html
Clearcutting Near Olympic
National Park, WA
1984
to
1995
http://svs.gsfc.nasa.gov/imagewall/LandSat/olympic.html
Deforestation near Santa Cruz,
Bolivia from 1984 to 1998
150 miles
200 miles
http://svs.gsfc.nasa.gov/imagewall/LandSat/santa_cruz.html
Urban Growth in the DC Area:
1973-1996
http://svs.gsfc.nasa.gov/imagewall/LandSat/dc_growth.html
Urban
Growth
Histories
BaltimoreWashington
Corridor
http://www.ncgia.ucsb.edu/projects/gig/
Urban
Growth
History
Marlborough
Subdivision
Growth
resac.uconn.edu
Urban Growth
Projections
San Francisco Bay Area
Eastern Pennsylvania
http://www.essc.psu.edu/~dajr/chester/animation/
Even WE cause
fragmentation
Click photo
File / Open Movie /
Uconn from Towers.mov
Resize Windows
Pan Right-Left
http://www.sp.uconn.edu/~wwwucimt/pano/images/towers.mov
NAUTILUS Research Objectives
Better land cover
Sprawl metrics
Forest fragmentation
metrics
Better impervious
cover
Landsat ETM+ Data
30 meter
multispectral
15 meter
panchromatic
60 meter
thermal
High Resolution Airborne & Satellite Data
ADAR 5500 and IKONOS
IKONOS coverage
ADAR coverage
IKONOS
Acquired through the
NASA Scientific Data
Purchase Program
ADAR 5500
Other Satellite Data
ASTER
MODIS
Earth Observer 1
Hyperion
ALI
SPOT
Basic Land Cover Characterization and Change
Objectives
• To identify and quantify general land cover change over
a 25 year period
• Perform classifications using traditional classification
techniques
Basic Land Cover Characterization and Change
Procedures, Salmon River Watershed
Identify best signatures
from 1973MSS & 1985TM,
Perform Maximum
Likelihood Classifier
MSS & TM
ISODATA clustering
into 200 clusters
(for each date)
1973
1976
1978
1981
1983
1985
1988
1993
1995
HECTARES
Urb/Bare Ag/Grass Forest
2484
3516
31298
2479
3917
30594
2612
3060
32173
3674
3024
30667
2407
3851
30890
3927
4151
29116
5292
3673
28152
5024
2483
29573
5110
4072
28059
Calculate category areas
Label clusters
into 7 classes
Adjust classifications to remove
unlikely changes due to
classification error
(i.e. urban to forest)
Land Cover
(7 classes)
Basic Land Cover Characterization and Change
Data, Salmon River Watershed
April 24, 1973
resampled MSS
May 5, 1976
resampled MSS
October 31, 1978
resampled MSS
March 4, 1981
resampled MSS
April 18, 1983
resampled MSS
May 4, 1988 TM
May 8, 1995 TM
April 26, 1985 TM
April 25, 1993 TM
Basic Land Cover Characterization and Change
Results to Date, Salmon River Watershed
April 24, 1973
resampled MSS
May 5, 1976 MSS
October 31, 1978 MSS
March 4, 1981 MSS
April 18, 1983 MSS
May 4, 1988 TM
May 8, 1995 TM
April 26, 1985 TM
April 25, 1993 TM
Forest Fragmentation and Urban Sprawl
Objectives
• To develop a practical method for assessing forest
fragmentation and urban sprawl
• Use ArcView GIS and extensions exclusively
Forest Fragmentation and Urban Sprawl
Procedures
ISODATA clustering
into 100 clusters
Label clusters
into 7 classes
(ArcView Image Analyst)
Spring & Summer
TM Images
Total Class Area
(ha)
Class
1985
1995
URBAN 1,495
2,578
FOREST 30,565 29,751
GRASS 3,909
3,713
Number of
Patches (n)
1985
1995
812
1,856
2,524
2,785
3,823
3,463
Derive Spatial
Statistics
Mean Patch Size
(ha)
1985
1995
2.42
1.68
11.97
10.52
0.99
1.05
(ArcView Spatial Analyst)
Land Cover
(7 classes)
Forest Fragmentation and Urban Sprawl
Data, Salmon River Watershed
Landsat TM
August 28, 1995
Landsat TM
August 9, 1985
Landsat TM
May 8, 1995
Landsat TM
April 26, 1985
Forest Fragmentation and Urban Sprawl
Results to Date, Salmon River Watershed
1985 Land Cover
1995 Land Cover
Detail Areas of Change
1985
1995 Land Cover
1995
1985 Land Cover
Forest Fragmentation and Urban Sprawl
Results to Date, Salmon River Watershed
Urban Land Gains: 1985 to 1995 (Hectares)
42.9
7.7
Water
353.4
Forest
Wetland
Grassland
36.4
892.4
Barren
Total urban land gain 1,333 ha
- Change to Urban Land
- Other Change
- No Change
Forest Fragmentation and Urban Sprawl
Results to Date, Salmon River Watershed
Forest Land Losses: 1985 to 1995 (Hectares)
63.9 68.7
345.5
Water
Wetland
853.0
Urban
Grassland
Barren
892.4
Total forest land loss 2,223 ha
- Change from Forest Land
- Other Change
- No Change
Forest Fragmentation and Urban Sprawl
Results to Date, Salmon River Watershed
Grassland Losses: 1985 to 1995 (Hectares)
47.7
2.8
Water
Forest
353.4
Wetland
Urban
5.9
801.5
Barren
Total grassland loss 1,211 ha
- Change from Grassland
- Other Change
- No Change
Forest Fragmentation and Urban Sprawl
Results to Date, Salmon River Watershed
Total Class Area
(ha)
Class
1985
1995
URBAN 1,495
2,578
FOREST 30,565 29,751
GRASS 3,909
3,713
Number of
Patches (n)
1985
1995
812
1,856
2,524
2,785
3,823
3,463
Mean Patch Size
(ha)
1985
1995
2.42
1.68
11.97
10.52
0.99
1.05
Forest Fragmentation and Urban Sprawl
Results to Date, Salmon River Watershed
GRASSLAND
1985, 10.1 % of the total area
1995, 9.6 % of the total area
FOREST
1985, 79.2 % of the total area
1995, 77.1 % of the total area
URBAN
1985, 3.9 % of the total area
1995, 6.7 % of the total area
Image Visualization Research
Temporal Image Sequencing
Objectives
• To create a visual demonstration of actual change
occurring in the landscape through the use of
animations
Image Visualization Research
Temporal Image Sequencing
Procedures, Histogram Matching
1995 TM
Linear Transforms
1995 TM
Non-linear
transform
Histogrammatched
1985 TM
ER Mapper Algorithm
Original
1985 TM
Image Visualization Research
Temporal Image Sequencing
Procedures, Interpolation and Movie Creation
1990 TM
.GIF Movie Creator
1991 Interpolated
TM
Formula Editor
[((1990 * 4) + (1995 * 1))/5] = 1991
1995 TM
.AVI Format
Movie
Image Visualization Research
Temporal Image Sequencing
Data, springtime Landsat imagery
April 24, 1973
resampled MSS
May 5, 1976
resampled MSS
April 18, 1983
resampled MSS
April 26, 1985 TM
May 4, 1988 TM
May 8, 1995 TM
Image Visualization Research
Temporal Image Sequencing
Data, summertime Landsat imagery
August 9, 1985 TM
August 30, 1990 TM
August 28, 1995 TM
August 31, 1999 TM
Image Visualization Research
Temporal Image Sequencing
Springtime 1973-1995 Animation
Image Visualization Research
Temporal Image Sequencing
Summertime 1985-1999 Animation
Intertnet Sources of Forestrelated Information
http://www.wri.org/gfw/
http://www.fanweb.org/index.shtml/
http://www.forestwatch.sr.unh.edu/
Where Can You Find Additional
Educational Resources on
Remote Sensing?
… how about the Internet?
ASPRS Remote Sensing
Core Curriculum
http://research.umbc.edu/~tbenja1/index.html
NASA On-Line
Remote
Sensing Tutorial
http://rst.gsfc.nasa.gov/
Canada Center for Remote
Sensing Fundamentals
http://www.ccrs.nrcan.gc.ca/ccrs/eduref/tutorial/indexe.html
Where Can You Find Digital
Remote Sensing Image Data
For Forest Characterization ?
… how about the Internet?
North American Landscape
Characterization (NALC)
1973
1980
1990
Landsat MSS Triplicates
http://edcdaac.usgs.gov/pathfinder/pathpage.html#nalc
North American Landscape
Characterization (NALC)
1990
DEM
Landsat MSS and DEM
http://edcdaac.usgs.gov/pathfinder/pathpage.html#nalc
TerraServer
http://www.terraserver.com/
Global Land Information System
Landsat TM August 20, 1998
http://edcwww.cr.usgs.gov/webglis
March
http://landsat7.usgs.gov/order.html
http://edcimswww.cr.usgs.gov/pub/imswelcome/
7, 2000 ETM+
Other Sites for Data
http://images.jsc.nasa.gov/iams/html/
http://terra.nasa.gov/
http://svs.gsfc.nasa.
gov/imagewall.html
… or Visit NASA’s RESAC at UConn
http://resac.uconn.edu
… where you’ll find ...
.. and ...
http://resac.uconn.edu
Research & Education
Watersheds
Presumpscot
SuAsCo
Salmon
Stonybrook
A range of land
covers and issues
Salmon River
Watershed, CT
• Focused watershed for NAUTILUS research
• CES program and research already
existing in watershed
• Rapid Urbanization
• State highway connects with major
Hartford market
• 5 out of 7 watershed towns are listed as
the fastest growing towns in the State
• Key component of the lower Connecticut
River Watershed
140 Sq. Miles
Stony Brook Millstone
Watershed, NJ
• Has a strong Watershed
Association in existence
• Between New York City and
Philadelphia
• Increased development pressures
• Loss of agriculture land to
urban sprawl
265 Sq. Miles
SuAsCo
Watershed, MA
Sudbury
Assabet
Concord
Watershed
• Has a strong Watershed
Coalition in existence
• Between the Boston metropolitan
region and Worcester
• Rapid development
• New residential development
replacing forests
• All river segments are Class B
waters
377 Sq. Miles
Presumpscot
Watershed, ME
• Existing NEMO Program
• Focus is on the lower portion
of Presumpscot River
• Most urban and rapidly
developing region in the State
• Significant water quality
problems in the lower portion
• Adjacent Harraseeket River coastal
watershed, which contains Freeport,
is included in NAUTILUS Project
200 Sq. Miles
Alternative/Emerging Classification Approaches
Knowledge Based Expert Systems, Procedures
Decision Tree
Source Data
and Derivatives
Final Classifications
Alternative/Emerging Classification Approaches
Neural Networks, Procedures
Input Layers
Output Layer
Neural Network Training
May 8, 1995 TM
Back-propagation
Neural Network
Classification
Principal Components
Neural Network Based Land Cover Change
Proof of Concept Study
Backpropagation
neural network
Forest to nonforest land cover
change
…. In tomorrow’s breakout
session we’ll look at ...
Land Cover Mapping and
Change Detection Using
ArcView
Session 5
Forestry and Change Detection
CORSE 2000
June 26-29, 2000
University of Southern Mississippi
Gulf Park Conference Center
Daniel L. Civco
LERIS / NRME
University of Connecticut
Storrs CT 06269
dcivco@canr.uconn.edu