The use of GIS for monitoring and predicting urban growth in East and West St Paul, Winnipeg, Manitoba, Canada

Abstract

Most urban growth in Canada occurs in the urban-rural fringe. The increasing dispersal of the Canadian urban population is due to centrifugal forces pulling urbanites past the suburbs into the surrounding exurban communities. Most Canadian urban centres are located on prime agricultural land. Exurban sprawl devours an inordinate amount of the better agricultural land. The growth around the city of Winnipeg is a case in point. Within Winnipeg's urban field are the rural municipalities of East and West St Paul. The objective of this study is to investigate the impact of urban growth on the agricultural land of these RMs as well as the rate of urban growth in both Municipalities based on database analysis using aerial photographs taken in 1960 and 1989 and Geographic Information System (GIS). East St Paul was found to have a higher rate of urbanization (from 10.14% to 43.75%) between 1960 and 1989 than West St Paul (from 7.36% to 23.57%). The growth prediction using Markov probability chain analysis showed that East St Paul will henceforth experience a reduced rate of increase than West St Paul. The rate of urbanization for both RMs is found to be comparable with areas surrounding other major cities such as Toronto. The largest increases in urban land use categories occurred in and around the existing exurban settlements. It was found that most urbanization take place on the most fertile soil.

Spatiotemporal Analysis of Land Use/Cover Patterns and Their Relationship with Land Surface Temperature in Nanjing, China

“…Markov model is a stochastic model that can trace the changing process from one state to another. The future state is only influenced by the current state, and each state should keep the same time step [41]. Markov model can be applied to reflect the change of LULC process [25,42]: (1) all the LULC types can change from each other under the historical influence; (2) LULC change is a complicated process which is influenced by several parameters and cannot be described by simple functions; and (3) the transformation of LULC is stable during the time period.…”

Evaluating Land Use and Land Cover Change in the Gaborone Dam Catchment, Botswana, from 1984–2015 Using GIS and Remote Sensing

“…Thus, LULC change studies are carried out using Remote Sensing (RS) and Geographic Information System (GIS) technologies. These technologies have been widely accepted and have a long history of supporting map development and monitoring for different purposes [64]. Recent advances in these technologies and methods have enabled researchers to model and predict LULC change effectively using satellite data which can be used to acquire data for inaccessible regions [63].…”

Scenarios Simulation of Spatio-Temporal Land Use Changes for Exploring Sustainable Management Strategies

“…Predicting land use changes can assist in determining the extent of degradation and enabling the managers to control changes in the proper directions [16][17][18]. From a planning and management perspective, it is of great significance to have an explicit understanding of predicted land use change as well as the underlying drivers [19][20][21].…”