A Prediction of Future Land Use/Land Cover in Amman Area Using GIS-Based Markov Model and Remote Sensing

Hamzah Ali Khawaldah
2016 Journal of Geographic Information System  
The paper aims to analyze land use/land cover (LULC) changes in western part and the populated area of Amman governorate and to identify the process of urbanization and urban expansion within the study area for the period of 1984-2014. It also aims to predict future LULC map for the year 2030 using Markov Model to provide city planners and decision makers with information about the past and current spatial dynamics of LULC change and strictly urban expansion towards successful management and
more » ... ter planning in the future. Images from Landsat 5-TM for the years 1984, 1999 and from Landsat 8-OLI for the year 2014 were used to investigate LULC within the study area during 1984-2014 and the resulted LULC maps in 1999 and 2014 were used to predict future LULC map based on Markov Model. The results indicated that the urban/built up area expanded by 147% during the period from 1984 to 2014 and predicted to expand by 43.9% from 2014 to 2030 based on Markov model predictions. The areas in the western, northwest and southwest parts of Amman as well as the areas of Marka and Uhud, the northeast of the study area, were predicted to witness the major urban expansion in 2030. And these are the areas where city planners and decision makers should take into consideration in future plans of Amman. The urban expansion was mainly attributed to the high population growth rate and large number of immigrants from neighboring countries and other socio-economic changes. Keywords Land Use/Cover Change, Markov Model, GIS, RS, Amman Introduction The entire world is continuously experiencing rapid urbanization [1] that leads to a variety of urban-related en-H. A. Khawaldah 413 vironmental and socio-economic issues. Urbanization, caused by population growth, will lead to inward urban growth (intensification) and outward urban growth (sprawl) [2] . These processes inevitably result in Land Use/ Land Cover (LULC) change which has great impacts on both natural ecosystems and human systems [3] [4]. Therefore, monitoring and detecting urban growth and its resulting LULC change are critical to planners, government agencies, hydrologists, ecologists, and so on. With the development of remote sensing and GIS technologies, reliable change detection results can be obtained. Urban growth mainly comes as a result of population growth and frequent human activities, such as industrialization, migration from rural to urban areas and resettlement [1] [5], leading to LULC changes and landscape pattern alteration at local and regional scale [6]-[10]. Such changes can include losses of agriculture areas, water bodies, forest and other vegetated green spaces and non-vegetated fields [2] [6] [9]-[11], and can result in various urban issues by increasing population density, housing condition, education, employment, public facilities accessibility, infrastructure sufficiency, and quality of life and so on, which are important socioeconomic issues accompanying urban expansion [5] [10] [12] [13]. Amman city, the capital of Jordan, is one of the cities that is experiencing a rapid urbanization as a result of its population's natural growth and migration from the neighboring countries as well as from other cities and rural areas of Jordan. The result of this was an unplanned expansion of Amman's urban area, which caused many problems. Thus, predicting future built up area is an important issue in order for future urban planning of the city. With the free access to the USGS Landsat archive and development of remote sensing techniques, detecting urban growth pattern (intensification or sprawl) and LULC change dynamics with temporally high frequent datasets become possible. Since the Landsat 1 was launched in 1972 as the first land-surface observation satellite, satellite data have been widely used for urban area analysis. Landsat archive data with longest record and global coverage allowed a great number of studies to detect long-term LULC change and urban expansion. With the Landsat archive data being open access, detecting long-term change dynamics is the trend of change detection analysis of complex systems. Numerous change detection methods were applied in previous studies. The most widely used method is Post Classification Change Detection (PCCD) method which can generate thematic map for each date and provide specific "from-to" change information. The key factor of producing high quality change detection results is producing accurate individual thematic map. Additionally, the prediction of future LULC in an area is very important process that provides urban planners and decision makers with the growth rates and the direction of urban expansion. This can help in planning for the needed public services and infrastructure in the future. In this regard, Markov model is an application of change detection that can be used to predict future changes in one area based on the rates of past change in the area. The method is based on probability that a given piece of land will change from one mutually LULC to another. These probabilities are generated from past changes and then applied to predict future change [14] . The general procedures of using Markov Change Detection Techniques (MCDT) are: first to create a transition matrix of pixels in each class for two time periods-this is basically the same as the cross-tabulation matrix that can be used for accuracy assessment. The main diagonal of the matrix contains pixels that have not changed, while other cells contain pixels that have changed. The next step is to generate probabilities of change between classes. This is accomplished by dividing each cell value by its row total. The result is the probability that a given class in date 1 will convert to another class in date 2 out of all possible changes [15] . The aim of this paper is to detect and reveal urban growth and LULC change dynamics in Amman, an area of observed high population growth in the past five decades, from 1984 to 2014 using GIS and remote sensing (RS) and to predict the future map of LULC in Amman. The objectives of this study can be specified as follows: • To analyze LULC change dynamics of Amman from 1984 to 2014. • To predict the future LULC in the area in 2030 focusing on the development of the built up area of Amman using Markov model. Description of the Study Area Amman governorate, the capital city of Jordan (Figure 1) , is an ideal study area for this research because it has undergone rapid population growth in the past 50 years. The study area is the west part and the populated area of Amman (The stretches from 31˚25"N to 32˚1"N latitude and from 35˚66"E to 36˚42"E longitude) which covers
doi:10.4236/jgis.2016.83035 fatcat:4l27caxevnckxm4zqqujbumr5a