DETECTING LANDUSE/LANDCOVER CHANGES ALONG THE RING ROAD IN PESHAWAR CITY USING SATELLITE REMOTE SENSING AND GIS TECHNIQUES

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1 Full length Research Paper DETECTING LANDUSE/LANDCOVER CHANGES ALONG THE RING ROAD IN PESHAWAR CITY USING SATELLITE REMOTE SENSING AND GIS TECHNIQUES Zahir Ali 1 & Ihsan Ullah 2 1 Pakistan Space and Upper Atmosphere Research Commission (SUPARCO), POBox 8402, Karachi 75270, PAKISTAN. 2 Institute of Geography Urban and Regional Planning, University of Peshawar, Peshawar, PAKISTAN. Accepted: 25 JANUARY, ABSTRACT JOURNAL OF GEO AND ENVIRONMENTAL SCIENCE RESEARCH VOL. 4(1), pp , JANUARY 2016 REF NUMBER: ONLINE: any countries in the world are experiencing an unprecedented growth of population and M urbanization. This has resulted in the increased pressure on available resources. This situation is particularly true in many cities in both developed and developing countries. The extremely rapid urban and population growth likewise pose numerous pressing problems to mankind such as environmental degradation, congestion and traffic, crime, unforeseen swiftness of structural changes, homelessness and unemployment. In order to cope with the consequences of rapid urban development, there is a strong need for devising an efficient system for urban landuse planning and management. While realizing the problems of an unprecedented sprawl of urban areas and its impacts, a study to evolve an operational system of monitoring, mapping and management has been carried out. This paper highlights the techniques used for extracting all the necessary information for mapping urban landuse/landcover changes in temporal context. This paper provides an operation solution for planning and management of urban environment through integrated use of Satellite Remote Sensing and Geographic Information System. KEYWORDS: Landuse, landcover, change detection, remote sensing, digital image processing *Corresponding Author. [email protected], [email protected]

2 Page 2 PESHAWAR INTRODUCTION Change detection in land use and land cover can be performed on a temporal scale such as a decade to assess landscape change caused due to anthropogenic activities on the land [1]. These anthropogenic activities on land are as a result of rapid urbanisation and industrialisation. Land use and land cover change have been recognised as important drivers of global environment change [2]. Land use and land cover are two separate terminologies which are often used interchangeably [3]. According to Longley [4], land cover refers to the physical materials on the surface of a given parcel of land, while land use refers to the human activities that takes place on or make use of land e.g. residential, commercial, industrial etc. Jensen [5] in his investigation of urban landscape perceived land use as a way by which human beings utilise land while land cover exists as a natural environmental system. Recently cities all over the world have experienced rapid growth because of the rapid increase in world population and the irreversible flow of people from rural to urban areas. Specifically, in the larger towns and cities the rate of population increase has been constant and nowadays, many of them are facing unplanned and uncontrolled settlements at the densely populated sites or fringes [6]. To prevent from such occasions urban planners need detailed updated maps for thorough planning and management. However, most city planners have a lack of such maps and often they possess old data which is not relevant for current decision making. Even if they do not hold a detailed updated map of the city area a regularly updated map with an acceptable resolution can at least give them an impression about the changes in the city area. With this rapid growth in population throughout the world, it is crucial to have a well-concerted plan for urban expansion. Satellite or Airborne images give urban planners synoptic views of large areas which allow them to lay plans for urban expansion effectively. This study involves digital change detection of landuse/landcover (from digitally classified satellite remote sensing data) of two time periods (January 1992 and January 2002). The Date of Pass of satellite remote sensing plays a significant role in minimizing the ambiguities in change detection arising due to difference in meteorological conditions. Using 1992 and 2002 SPOT Panchromatic and Multi-Spectral imagery of the Peshawar area, this paper demonstrates how to use digital enhancement and GIS techniques in processing those images for urban planning and to monitor changes that took place over the past 10 years. The aim of this paper is to detect the main changes occurred in southern part of Peshawar city. The study area is the Ring Road Area of the Peshawar city. The approach used in this study to detect the land use and land cover changes involved digital change detection using different digital image processing techniques. The study will assess the capability of knowledge based change detection approach which less dependent on field observations and secondary data. OBJECTIVES The main objective of this research is to assess automatic knowledge-based approaches in digital land use change by using Digital Image Processing Techniques. This objective could be achieved through: Spectral classification of multi-temporal images in order to produce landuse and landcover maps. Derivation of land use information from land cover classes by using the out dated land use maps supported by the field knowledge expressed in terms of rules. Combination of knowledge on land cover and land use change in order to produce land use change map.

3 Page 3 PESHAWAR STUDY AREA The study area selected is the Ring Road area located in the southern part of Peshawar city. Peshawar is the capital city of the Khyber Pakhtunkhwa (KP) province which is the northern province of Pakistan. The study area is located within coordinates of latitude between 33 o 55'N & 34 o 02'N and between 71 o 27'E & 71 o 38'E longitude. The total study area is about Sq. km. The average elevation of the study area is approximately 359 meters in the south above mean sea level in the north. In this area the summers are hot (45 o C as a maximum average temperature) and the winters are cold (5 o C as minimum average temperature). Agriculture is widely practiced in this area due to presence of rich soil and the abundance of water. Figure 1: Location of the Study Area DATASETS AND MATERIALS USED SPOT scenes having path-row acquired on January 1992 and January 2002 were employed in this study. Other materials used were topographic map sheets of the Survey of Pakistan (having scale 1:50,000). The topographic maps were used for geometric correction of the satellite data and drawing annotation layer. Also the ERMapper software was used for data rectification and classification techniques. The datasets used in this study are; A topographic map of 1969 at scale 1:50,000 SPOT XS image of 1992 SPOT Panchromatic data of 1992 SPOT XS image of 2002 SPOT Panchromatic data of 2002

4 Page 4 PESHAWAR METHODOLOGY GEOMETRIC CORRECTION Geometric correction of the SPOT RAW images was carried out using ERMapper software. First a single SPOT RAW image was geometrically corrected using image to map rectification technique. Registration of the image to the 1:50,000 scale topographic maps were done by selecting 25 Ground Control Points (GCPs). The Root Mean Square (RMS) error accepted was less than 1 pixel (20 m) at the first order and the nearest neighborhood transformation. Once a single image is rectified, the remaining three images were rectified using image to image rectification technique. Average RMS error of less than 0.5 is achieved for all the images. All scenes were radiometrically and geometrically corrected to a map projection LM1PAK1 and geodetic datum INDIAN75. Some enhancement techniques were also applied to all four scenes to enhance its information. The common area of the two date s imagery was then selected and subsets were achieved for the study. IMAGE CLASSIFICATION The overall objective of image classification is to automatically categorize all pixels in an image to landuse/landcover classes or themes. The principle involved is that different features manifest spectral reflectance and emittance properties [7]. In order to detect the landuse/landcover changes in the study area, the January 1992 and January 2002 scenes were classified into 20 classes with an unsupervised isodata classification technique. These classes were combined into a total of five classes which are cultivated land, plantation/miscellaneous trees, barren land, high build up area and low build up area. Designation of classes was based on spectral analysis, limited field checking, and the use of band ratios. Image characteristic such as tone, texture colour and pattern are translated into land use attributes. The translation process (transfer function) is guided by local knowledge (e.g. landuse/landcover map or agriculture statistics) which was collected during field work or background studies [8]. Different colours have been assigned to these different classes/regions for analysis and defined in the legend. After assigning classes, the desired statistics were calculated and compared with each other for the 10 years change detection. The final False Colour Composite (FCC) images and Landuse / Landcover images are shown in the Figures.

5 Page 5 PESHAWAR Figure 2: False Colour Composite (FCC) of the study area, having path-row , Dated January Figure 3: False Colour Composite (FCC) of the study area, having path-row , Dated January 2002

6 Page 6 PESHAWAR Figure 4: Landuse / Landcover of the study area, having path-row , Dated January 1992

7 Page 7 PESHAWAR Figure 5: Landuse / Landcover of the study area, having path-row , Dated January 2002 RESULTS AND DISCUSSION The performance of the unsupervised maximum likelihood classification was tested for change detection. The area summary report was prepared for the study area. The areas for each classes/ regions have been calculated carefully. By comparing these calculations it is found that barren land, cultivated land and low build up area have decreased while plantation/miscellaneous and high build up area have increased due to urbanization. The comparison graph for both data has shown below.

8 Page 8 PESHAWAR Figure 6: Comparing landuse categories for both years An overall increase was found in the build-up area while the cultivated land has been decreased. The main reason for this cause is the shifting of people from rural areas to city area for their business and other jobs. Similarly some developmental works in this area because of the Ring Road Project also play an important role. The net area (in sq.km) increase or decrease for the different landuse categories delineated from satellite data of two time periods has shown in the Figure. Figure 7: The net area increase or decrease in sq.km for the landuse categories in both years

9 Page 9 PESHAWAR CONCLUSIONS From this study, it is concluded that; Satellite remote sensing technique is more economical and efficient than conventional mapping surveys as it reduces field work to some extent. Multi-date temporal SPOT Panchromatic and Multi-Spectral data can be used and changes can be mapped that took place over the last years. The multi-date datasets are required to be rectified and co-registered. Different change detection techniques can be applied to detect changes. Verification of the changes in the field is necessary for accuracy assessment. In a nut shell, the results of this study seem realistic and the areas showing change were in agreement with ground truth. This study demonstrated that the digital image processing technique is an effective tool in detecting landuse/landcover changes. REFERENCES [1] Gibson, P. and Power, C. (2000). Introductory Remote Sensing: Digital Image Processing and Applications. Routledge, p. 249, ISBN [2] Turner, M. G., Meyer, W. B., and Skole, D. L. (1994). Global land-use/land-cover change: towards an integrated study. Ambio, 23, pp [3] Dimyati, M., Mizuno, K., Kitamura, T. (1996). An Analysis of Land Use/Cover Change using the combination of MSS Landsat and Land Use Map: A Case Study in Yogyakarta, Indonesia. International Journal of Remote Sensing, 1996, 17(5), pp [4] Longley, P., Donnay, J., Barnsley, M. (2001). Remote Sensing and Urban Analysis Taylor and Francis. London, p.117 [5] Jensen, J., (2007). Remote Sensing of the Environment: An earth Resource Perspective (2nd Edition). Pearson Education, Inc, p.450. [6] Amarsaikhan, D., Tsolmongerel, O. (1997). Some Results Of Using Spatial Enhancement Techniques. Journal of Informatics, Ulaanbaatar, Mongolia, pp [7] Thomas N, Hendrix C, Congalton RG. (2003). A comparison of urban mapping methods using highresolution digital imagery. Photogrammetric Engineering and Remote Sensing, 69, pp [8] Quarmby, N.A. and J.L. Cushnie (1989). Monitoring Urban Land Cover Changes at the Urban Fringe from SPOT HRV Imagery in south-east England. Int. J. of Remote Sensing, 10, pp