Abstract
Modeling and assessment of land use/cover and its impacts play a crucial role in land use planning and formulation of sustainable land use policies. In this study, remote sensing data were used within geographic information system (GIS) to map and predict land use/cover changes near Amman, where half of Jordan’s population is living. Images of Landsat TM, ETM+ and OLI were processed and visually interpreted to derive land use/cover for the years 1983, 1989, 1994, 1998, 2003 and 2013. The output maps were analyzed by using GIS and cross-tabulated to quantify land use/cover changes for the different periods. The main changes that altered the character of land use/cover in the area were the expansion of urban areas and the recession of forests, agricultural areas (after 1998) and rangelands. The Markov chain was used to predict future land use/cover, based on the historical changes during 1983-2013. Results showed that prediction of land use/cover would depend on the time interval of the multi-temporal satellite imagery from which the probability of change was derived. The error of prediction was in the range of 2% - 5%, with more accurate prediction for urbanization and less accurate prediction for agricultural areas. The trends of land use/cover change showed that urban areas would expand at the expense of agricultural land and would form 33% of the study area (50 km × 60 km) by year 2043. The impact of these land use/cover changes would be the increased water demand and wastewater generation in the future.
Highlights
Mapping of land use/cover and its change provides invaluable information for managing land resources and for projecting future trends of land productivity [1]
Remote sensing data were used within geographic information system (GIS) to map and predict land use/cover changes near Amman, where half of Jordan’s population is living
From remote sensing and GIS perspectives, this study evaluates the effect of time-interval on predicting land use/cover change with the Markov chain model so that the time interval of satellite imagery with the highest accuracy of prediction will be recommended for predicting future land use/cover
Summary
Mapping of land use/cover and its change provides invaluable information for managing land resources and for projecting future trends of land productivity [1]. The output maps, in the form of digital layers, can be overlaid and analyzed within a GIS to provide information on percentage land use/cover and its change among or between a time-series of satellite images or aerial photography Based on this knowledge, future land use trends can be postulated and action plans can be framed. The high increase in Jordan’s population has resulted in unplanned land use/cover changes turning the limited agricultural lands into urbanized areas [1,15]. These trends are expected to exert more pressure on the country’s limited resources of water and agricultural land. Spectives, this study evaluates the effect of time-interval on predicting land use/cover change with the Markov chain model so that the time interval of satellite imagery with the highest accuracy of prediction will be recommended for predicting future land use/cover
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