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Land Use and Land Cover Change Detection Using Remote Sensing and GIS Technologies: a Case Study of Mirzapur Union, Gazipur District, Bangladesh

Raihana Yesmin
Department of Soil, Water and Environment, University of Dhaka, Bangladesh

A. S. M. Mohiuddin
Department of Soil, Water and Environment, University of Dhaka, Bangladesh

M. J. Uddin
Department of Soil, Water and Environment, University of Dhaka, Bangladesh

Mohammad Abdus Shahid
Bangladesh Space Research and Remote Sensing Organization (SPARRSO), Bangladesh

Abstract/ Executive Summary:

A study was conducted with a view to identify and quantify the changes in land use and land cover that occurred during the last 20 years at Mirzapur Union, Gazipur district, Bangladesh using remote sensing (RS) and geographical information systems (GIS) technologies. Two Landsat TM images for 1989 and 2009 with 30 m spatial resolution were used to determine the temporal land cover changes. Subsequently, ground verification was conducted in the study site. The study revealed that forests and water bodies decreased by 20.29 and 6.25% respectively, while settlements were found to have increased by 28.64%. In the same period of time, bare lands were found to have increased by 20.91% due to the effect of clearing of forests which were not replanted again. A lot of new infrastructures had been built in this period and the population doubled, resulting in the deforestation of the Sal forest (Shorea robusta). The most prominent features are the emergence of brick fields and various industries. This study demonstrates the usefulness of RS and GIS technologies for resource management and urban planning.

Keywords: Land use and land cover; Landsat imageries; Georeferencing; Change detection; Deforestation.

Location: Mirzapur Union, Gazipur district, Bangladesh

Start Date: 00-00-1989

End Date: 00-00-2009

Program Area: Resource Development and Management

Non-commodity: GIS

Objectives:

To monitor and analyze the spatio-temporal land use and land cover change patterns in Mirzapur Union, Gazipur district, Bangladesh using multi-temporal Landsat imageries for the past 20 years.

Methodology:

The study area was selected because migration of huge population as it is very near to Dhaka and is a good site for an urban development center. As a result of population pressure, the local people are destroying forests, trees and valuable cultivable land to develop various industries and brick fields. As a result, the forest area is gradually decreasing and the environment is changing significantly. Considering the above situations, two Landsat Thematic Mapper (TM) images, for 1989 and 2009, with resolution of 30 m (projection: Bangladesh Transverse Mercator) were used in this study. Some secondary data sources were also used, such as topographical, soil and physiographic maps. The image related methodology adopted for this study involved digital image processing (DIP) and GIS analyses. DIP analysis was carried out using a computer system having data layer software configuration, with the ERDAS IMAGINE image processing software used for geo- referencing, classification and enhancement of the images, and other related processing. The Arc Info software was used for digitizing, displaying and analyzing all the vector layers. The Landsat images were preprocessed to remove data errors and anomalies. The DIP system was used to determine the land covers. A sufficient number of ground control points (GCPs), which were readily identifiable on the pre- rectified image, were selected for calculation of a least-square fit, and the results were then used to adjust the image to image coordinates. The preferred GCPs were taken from recognizable, permanent features, such as road intersections, ponds and large buildings, and the points were well dispersed for accurate rectification. The images were projected on to a plane, and then rotated and scaled to a map projection system. For each image transformation, the root mean square (RMS) error was calculated, with the maximum being 1.5 pixels. This corresponds to a ground distance of 45 m for the TM images. Using this procedure, each raw satellite image was resample, using the nearest neighbor algorithm, and transformed into a file referenced to the Universal Transverse Mercator (UTM) projection. A digital classification scheme was developed to categorize five major land cover types (settlement, water body, forest, bare land and valley). The Landsat images were classified using image processing techniques to enable the assignment of land cover classes to areas of similar spectral characteristics. The unsupervised classification was based on the ISODATA algorithm available in the ERDAS Imagine software.

Source of Information: Malaysian Journal of Remote Sensing & GIS (MJRS&GIS), Vol. 3, Num. 2, Year-2014; ISSN: 1511-7049

Article Link (Online Journal):

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

Significant changes were detected in land use and land cover in Mirzapur Union during the last 20 years (1989-2009). These changes occurred in different land covers, such as forests and water bodies, which decreased by 20.29 and 6.25% respectively; and settlements and bare lands, which increased by 28.64% and 20.91% respectively. All of these changes were due to the increase of population and unplanned urbanization destroying the local forest resources.

Knowledge Management: Journal