Distributed Land-Cover Change Simulation
Statement of interest submitted to the
Land Use Modeling Workshop at the
USGS EROS Data Center, Sioux Falls,
SD, June 5-6, 1997.
Statement of Interest:
Computer simulations are used in landscape ecology to simulate the effects
of human land-use decisions on the environment. Such decisions are
influenced by both ecological
and socioeconomic factors which can be represented by
spatially explicit multidisciplinary data. With support from the
U.S. Man and the Biosphere (MAB) program,
we have developed (through a collaboration with several ecologists, economists,
sociologists, and foresty personnel) the
Land-Use Change Analysis System (or
LUCAS) for the
study of land-use effects on landscape structure in such areas as
the Little Tennessee River Basin in western North Carolina and the
Olympic Peninsula of Washington state. These effects include
land-cover change and species habitat suitability. Using a
geographic information system (GIS) to store, display and
analyze map layers derived from remotely sensed images, census and
ownership maps, topological maps, and output from econometric models,
a parallel/distributed version of LUCAS (pLUCAS) was developed for
simulations on a network of workstations. Targeting distributed computational
environments reflects the resources available to most land-use
planners, forestry personnel, and wildlife managers. We have recently
conducted a formal performance evaluation of two pLUCAS distributed models on
an ATM-based network of 12 SUN Ultra-2 workstations. Speed improvement
factors as high as 8 (relative to serial runs
on a single SUN Ultra-2 workstation) have been obtained using
the PVM or MPI message-passing environments.
As part of the
Integrated Modeling Project (IMP) of
Southern Global Change Program, we are responsible for the
development of the (second) IMP module which facilitates the
horizontal integration of
forest responses to environmental stresses and disturbances
through the use of micro-scale cellular automata. This module
is being developed from the LUCAS modeling system prototype.
Stochastic attributes used by LUCAS will incorporate the
frequency distributions of output results generated by the IMP's Linked
Dynamic Model. Overall focus of the Integrated Modeling Project (IMP) is to
integrate forest health and productivity assessments of southern and
southeastern forests by taking into account changing climate,
air quality, and land use changes.
In order for LUCAS to aggregate site
index and forest growth types (height vs age) attributes to forest
stands across the southern region, response surfaces must be
developed from selected outputs of the codes comprising the
Linked Dynamic Model. Using 5-dimensional interpolation based
on the Modified Shepard's Method developed by Robert Renka
(Univ. of North Texas) we are building a portable object-oriented
(C++) software package that will produce interpolated values for the
of any model output (e.g, site index or the height of
of dominant trees at age 25) based on the following
independent variables (or conditions):
- standard deviation,
- minimum value,
- maximum value, and
- distribution type (normal, lognormal, uniform, etc.)
The hypervolumes or response surface data produced from the
proposed activity will be constructed using the
(network Common Data Form) which is a popular machine-independent
format for representing GIS and other scientific data. These
hypervolumes will be used to integrate the influence of environmental
factors on the forest conditions modeled by the codes in the IMP's
Linked Dynamic Module. These hypervolumes may also be of
great use by other researchers (outside of the IMP project) in the
study of forest growth and production in the southeastern US.
- atmospheric carbon dioxide,
- ozone exposure,
- nitrogen deposition,
- temperature, and
In addition to the development of the 5-dimensional hypervolumes
for the IMP driving variables, we will be porting
the current MPI-based pLUCAS prototype to a newly acquired IMP SP/2
(total of 40 processors). Cycles on this machine will be available
for future pLUCAS-based simulations associated with Module II
of the IMP project.
Our research in computational ecology
has been supported by the Southeastern Appalachian
Man and the Biosphere (SAMAB) Program under U.S. State Department
Grant No. 1753-000574 and University of Washington Subcontract
No. 392654, by the National Science Foundation under grants
NSF-ASC-94-11394 and NSF-CDA-95-29459, and the USDA Forest
Service under Contract Nos. 29-1286-96 and SRS-CA-96-067.
M. W. Berry, R. O. Flamm, B. C. Hazen, and R. L. MacIntyre.
Lucas: A System for Modeling Land-Use Change.
IEEE Computational Science and Engineering, 3(1):24-35, June 1996.
B. C. Hazen.
A Distributed Implementation of the Land-Use Change Analysis System
(LUCAS) Using PVM.
Master's thesis, University of Tennessee, Knoxville, August 1995.
B. C. Hazen and M. W. Berry.
The Simulation of Land-Cover Change Using a Distributed Computing
Environment. Simulation Practice and Theory, 1997. In Press.
R. J. Renka.
Multivariate Interpolation of Large Sets of Scattered Data.
ACM Trans. on Math. Soft. 14(2):139-148, June 1988.
Tue May 13 20:58:03 EDT 1997