Modeling Urban Land Use Change: Integrating Remote Sensing with Socioeconomic Data - Computational Approaches for Urban Environments - page 288

Grid based CA Batty and Xie

( 1994 ) and Tang
( 2011 )

Model the spatial
structure of urban
land use over time

Landscape maps,
environmental factors in
neighborhood

The spatial factor and
ecological aspects are
easily to be incorporated

Face challenge in
incorporating human
decision making

LUCAS Berry et al. ( 1996 ) Simulate the

landscape change
with
socioeconomic
information and
its environmental
impacts

Socioeconomic variables,
such as transportation
network, ownership,
population density, etc.

Flexible and interactive
computing environment

The patch size is no
sense due to the
pixel-based method

LT M Pijanowski et al.

( 1997 , 2014 )

Analyze the land
use change and
predict land use
pattern

Landscape maps, social,
political, and
environmental factors

Can be applied to multiple
scales using a moving
scalable window metric

Suppose all the
variables constant

CLUE De Kong et al.

( 1999 )

Predict future land
use

Biophysical drivers and
human drivers

Covers a wide variety of
biophysical and human
factors and ranges multiple
spatiotemporal scales

No social or political
factors

Grid/vector Agent based Liebrand et al.

( 1998 )

Represent a wide
variety of entities
and its activities

A simulated environment,
entities under human
decision making

Flexibility and successful
in replicating human
decision

Difficult to develop
and control