Geoscience Reference
In-Depth Information
Chapter 12
Modeling Urban Land Use Change: Integrating
Remote Sensing with Socioeconomic Data
Junmei Tang
Abstract
Rapid urban development has stimulated the progress in predicting and
evaluating urban landscape evolution. As a result of rapid socioeconomic devel-
opment, the land use pattern of Houston, TX, has undergone significant changes
over the past 30 years. It is essential to simulate urbanization processes in Houston
to examine where and to what extent landscape change has occurred and further
to understand how and why the change can occur. This research developed two
cellular automata (CA) models based on the same remote sensing data source: one
was based on the classification from Landsat images and another one incorporated
the socioeconomic data with the same classification results. The predicted results
from these two models suggested that the incorporation of socioeconomic data
improved the accuracy in human-intervened landscapes, such as residential and
industrial/commercial area. More socioeconomic data and finer data sources were
needed to improve the CA model to predict the heterogeneous pattern within urban
areas.
Keywords
Urban land use change CA model Socioeconomic data Remote
sensing
12.1
Introduction
Rapid urbanization in the past 50 years, triggered by the population growth and
migration from rural to urban and suburban areas, presents one of the greatest
challenges in environmental, economic, social, political, and cultural research
(Antrop
2004
;Tangetal.
2012
; Tayyebi et al.
2012
). The total urban population is
82 % with an estimated 1.2 % annual increasing rate from 2010 to 2015 in the United
States (US Census
2011
). The motivation to model urban landscape dynamics arises
from the process of examining where and to what extent landscape change has
occurred, and furthermore, the need to understand how and why the changes can
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