Application of remote sensing and GIS to the study of land use/cover change and urbanization expansion in Basrah province, southern Iraq

Abstract

In recent years, land use/cover dynamic change has become a key subject that needs to be dealt with in the study of global environmental change. In this paper, remote sensing and geographic information systems (GIS) are integrated to monitor, map, and quantify the land use/cover change in the southern part of Iraq (Basrah Province was taken as a case) by using a 1:250 000 mapping scale. Remote sensing and GIS software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation, sand, urban area, unused land, and water bodies. Supervised classification and normalized difference build-up index (NDBI) were used respectively to retrieve its urban boundary. An accuracy assessment was performed on the 2003 LULC map to determine the reliability of the map. Finally, GIS software was used to quantify and illustrate the various LULC conversions that took place over the 13-year span of time. Results showed that the urban area had increased by the rate of 1.2% per year, with area expansion from 3 299.1 km 2 in 1990 to 3 794.9 km 2 in 2003. Large vegetation area in the north and southeast were converted into urban construction land. The land use/cover changes of Basrah Province were mainly caused by rapid development of the urban economy and population immigration from the countryside. In addition, the former government policy of "returning farmland to transportation and huge expansion in military camps" was the major driving force for vegetation land change. The paper concludes that remote sensing and GIS can be used to create LULC maps. It also notes that the maps generated can be used to delineate the changes that take place over time.

Analysis of Land Use and Land Cover Changing Patterns of Bangladesh Using Remote Sensing Technology

“…This research identifie the land cover changes of Bangladesh in different periods using supervised classification in ArcMap software. Hadeel et al (2009) were showing the application of remote sensing and GIS for LULC change using supervised classification in June 2009. In Northern Australia, mapping of land covers a comparison of objective oriented and pixel-based classification methods are developed using this process (Whiteside and Ahmad, 2005).…”

Retrieval of Land-Use/Land Cover Change (LUCC) Maps and Urban Expansion Dynamics of Hyderabad, Pakistan via Landsat Datasets and Support Vector Machine Framework

“…Land-use and land cover types here are divided into 5 key types, namely built-up area (as indicated by impervious surface), agricultural land, vegetation, waterbodies, and barren land [75], via remote sensing (RS) image classification techniques. RS has been the most cost-effective and convenient manner for developing and analyzing LUCC information, because attributes can be obtained without directly getting in touch with the ground surface, therefore it has been used in many developing cities [32,71,76], where sensors are always absent or insufficient in these places. In particular, Landsat 8 OLI RS-based datasets have been adopted to retrieve a total of 8 land cover classes in Cambodia, Laos, Myanmar, Thailand, Vietnam, and other Southeast Asia countries with high accuracies [77], while SPOT-VEGETATION satellite data from 1998-2000 have also been used to derive regional land-cover maps within South and Southeast Asia [78].…”

Remote Sensing-Based Urban Land Use/Land Cover Change Detection and Monitoring

“…Defining the effects of land-use and land-cover change on the Earth system be contingent on a sympathetic of past land-use rehearses, contemporary land-use and land-cover patterns, and prognostications of forthcoming land use and cover, as pretentious by human distribution, economic development, technology and other factors [4,5,7,8]. Concerning urban the structure of and composition, it can be realized there are many objects that made up of small different material in the spatial arrangement that gives heterogeneous pixels in the earth observation satellite imageries.…”