Uncertainty awareness in urban sprawl simulations: Lessons from a small US metropolitan region

被引:34
作者
Batisani, Nnyaladzi [1 ]
Yarnal, Brent [2 ,3 ]
机构
[1] Botswana Coll Agr, Dept Agr Engn & Land Planning, Gaborone, Botswana
[2] Penn State Univ, Ctr Integrated Reg Assessment, University Pk, PA 16802 USA
[3] Penn State Univ, Dept Geog, University Pk, PA 16802 USA
关键词
Land use change modeling; Simulation; CLUE-S; Uncertainty analysis; Sensitivity analysis; LAND-COVER CHANGE; SENSITIVITY-ANALYSIS; FARMLAND CONVERSION; MODEL; VALIDATION; ERROR; GIS; DYNAMICS; HABITAT; MAPS;
D O I
10.1016/j.landusepol.2008.01.013
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Land use change modeling and simulation is a popular tool in land use planning and policy formulation. However, the outputs of land use change simulation are not always accompanied with information on uncertainty. The goal of this paper is to demonstrate the inherent uncertainty in sprawl simulation, which is attributable to error in the input parameters and to limitations in our understanding of land use systems. To reach this goal, the paper determines sprawl simulation accuracy and uncertainty for a small US metropolitan region as produced by the CLUE-S modeling framework. The model simulates sprawl location in the region accurately, but the certainty of sprawl location projections decreases with time. This uncertainty in the simulation suggests that modelers should report uncertainty with their output over all time horizons so that, on the one hand. land use planners and decision makers do not place too much confidence in any single sprawl simulation (which could lead to unwarranted and expensive urban growth management policies) and, on the other hand, do not place too little confidence in sprawl models (which could have severe socioeconomic and environmental consequences). Thus, reporting uncertainty with simulation output provides planners and decision makers with a platform for more informed land use policy. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:178 / 185
页数:8
相关论文
共 83 条
[1]  
ANDERSON RJ, 1976, 964 GEOL SURV PROF U
[2]  
[Anonymous], 1994, SCI JUDGM RISK ASS C
[3]  
[Anonymous], 1976, Applications of Statistics to Industrial Experimentation
[4]  
[Anonymous], 2002, DEFORESTATION LAND U
[5]  
Batty M., 1999, Computers, Environment and Urban Systems, V23, P205, DOI 10.1016/S0198-9715(99)00015-0
[6]   WATER-QUALITY MODELING - A REVIEW OF THE ANALYSIS OF UNCERTAINTY [J].
BECK, MB .
WATER RESOURCES RESEARCH, 1987, 23 (08) :1393-1442
[7]   Measuring uncertainty importance: Investigation and comparison of alternative approaches [J].
Borgonovo, Emanuele .
RISK ANALYSIS, 2006, 26 (05) :1349-1361
[8]  
BOX GEP, 1987, QUAL PROG, P54
[9]  
Burrough P.A., 2000, Principles of Geographic Information Systems
[10]  
CARMICHAEL GR, 1997, ATMOS ENVIRON, V13, P475