LAND USE/ LAND COVER MAPPING OF KANPUR CITY USING REMOTE SENSING AND GIS

Saurabh Shiva Senior Research Fellow, M.P. Council of Science and Technology (MPCST), Bhopal

8817924706,Email:shiva.saurabh@gmail.com

Abstract Multispectral satellite data and GIS for land use/ land cover mapping has become as primary data sources. Remote sensing data is very useful due to its synoptic view, repetitive coverage and real time data acquisition and GIS for data integration and analysis. It also provides continuous monitoring for planning and management which depends on accurate information on land cover. Therefore land use/ land cover maps are prepared using multispectral and temporal satellite data which provides different levels of spatial information which are used for different application studies. This paper demonstrate the present status of land use-land cover in the Kanpur city on 1:50,000 scale by using satellite data of Resourcesat-1 LISS III (23.5 m) image and Landuse/land cover map and other maps had been prepared. Keywords: Landuse/Land cover, Resourcesat-1 & LISS-III, Remote Sensing, GIS. 1. INTRODUCTION The knowledge of land use and land cover is important for many planning and management activities concerned with the surface of the Earth. The term land cover relates to the type of feature present on the surface of the earth. Urban built up, forests, water bodies etc are the examples of land cover types. The term land use relates to the human activity associated with a specific piece of land. Geographical Information system (GIS) is a "Set of tools for collecting, storing, retrieving at will, transforming and displaying spatial data from the real world for a particular set of purposes" (Burrough, 1986). The rich experience gained over the past two decades in the implementation of a standard national land use/land cover classification amenable for use with remote sensor data for mapping on 1 : 250,000 scale and to some extent on 1 : 50,000 scale enhanced our ability to understand and manage countries natural resources. Earlier efforts to map the theme on 1:50,000 scale followed certain standards which required modifications in the current day’s context. To this extent, an exhaustive land use/land cover classification was evolved to facilitate an in-depth assessment of all the land use/land cover categories. The benefits of implementing/adopting a classification are tending to persuade for evolving a standard classification system that is guided by practical experience and continuous observation over the past many years and above all that meet the user requirements. The following points were considered ideal in terms of most favorable conditions. The classes in the classification system are hierarchically organized to find its applicability in different spatial scales and collapsible for comparison with the reported areas; adopt directly by user agencies with refinements at their end. The classification must be scientifically defensible presenting a logical progression of its applicability over large areas, amenable for use with remote sensor data. The classification scheme is adopted for extracting information for on most possible land use/land cover classes

in general and all the agricultural seasons in particular and hence enable to repeat the process at regular time intervals. The mapping process with the definitions, classification scheme and procedural steps for interpretation and mapping so as to maintain set standard operational procedures. The current issues related to input data that has the following components as, Satellite data and season of its acquisition, collateral data and legacy data, Classification scheme, Ground data collection, Classification of multitemporal data-sets. A key strategy of the current project is use of multispectral data sets for classification in a pursuit to achieve improved classification accuracies. The IRS P6 LISS III data, geometrically corrected within the framework of NNRMS specified standards is the primary input for classification and mapping. Multi-temporal data acquired during (April-May) while taking into account the crop calendar of an area will be used for the purpose. Digital Survey of India topographic map layer on 1: 50000 scale will form the base layer for the mapping activity. The map layer contains Administrative boundaries (International, State, District, Tehsil, and village and forest boundary), major roads, railway, drainage, settlements, etc. A good amount of data on themes like wasteland, forest that was generated earlier will form as an important source of reference while classification. These legacy layers may be re-projected as per the current mapping specifications before using them. The classification system amenable for use with remote sensor data varies with the objectives of the classification and the type of satellite data that is being used for the purpose. The nomenclature and definition of each of the categories is variable because of the said variations. There are various organizations in the country, which have evolved classification systems depending upon their objective and functionality. The sole objective of a classification scheme is to group together a set of observational units on the basis of their common attributes. It is essential to further re-group the above observational units so as to share additional attributes that are similar in nature and interrelated. 2. OBJECTIVES The project undertaken aims at developing an analytical overview of the various land use land cover classes of the Kanpur city and to generate the current information and present status of the study area of the various land use/ land cover classes. Creation of digital database of land use features representing urban development, to study the land use/ land cover pattern in Kanpur city from imagery and also to explore the factors responsible for urban expansion in Kanpur city. 3. STUDY AREA 3.1 Physiography The study area chosen is the Kanpur district of Uttar Pradesh. This is spread over area of 260 sq km. It is located at Latitude 26.4670° to Longitude North and 80.3500° East, and lies in northern India. It is situated on the southern bank of holy river Ganga and is about 126 meters above the sea level. Kanpur is divided into two districts namely Kanpur-Nagar and Kanpur-Dehat.It is surrounded by two main rivers of India, the Ganges in the north-east and the Pandu river

(Yamuna) in the south. Kanpur metropolis forms a part of Ganga sub -basin in the Central Indo-Gangatic Plain and exhibits more or less a flat topography with the master slope from north-west to south-east. The average elevation of land surface is 125 meter m.s.l. The area is drained by the river Gange and its tributary Pandu.

Fig 1: Kanpur Physical Feature Map

3.2 Geology The district lies in the Ganga basin which is formed of alluvium of the early quaternary period with no hard or consolidated rock exposures are encountered. The main constituents (sand, silt and clay) of alluvium occur in variable proportions in different sections. The mineral products of the district of saline earth from which salt petre and salt are derived and limestone conglomerates (U.P. District Gazetteers Kanpur). 3.3 Geomorphology Kanpur region shows a drastic shifting of the river Ganga which is governed by the fluvial dynamics of the river Ganga. Various geomorphological units and their mutual relationship clearly shows the presence of two distinct geomorphic zones associated with the two major episodes of changes in the sedimentation pattern of the river (Srivastava and Singh, 1999). The area of city has been geomorphologically divided into two units.(I) Low lands or Younger Alluvial Plain &(II) Up lands or Older Alluvial Plain. The Low land or Younger Alluvial Plain has been identified as flat to gently sloping and slightly undulating terrain of large aerial extent, formed by river deposition, and is limited along river

Ganga with the breadth not exceeding 5 km. The sediments comprise of recent unconsolidated alluvial material of varying lithology. The fluvial land-forms such as Palaeo channel, Meander scars, and oxbow lakes are common features. Further west of Younger Alluvial Plain is the area of stable upland which has been produced by extensive deposition of older alluvium comprising of coarse to fine sand, silt and clay. The patches of salt encrustations have been reported in the area around Panki and Chakeri. 3.4 Hydrogeology Kanpur metropolis forms a part of Central Ganga Alluvial Plain, underlined by unconsolidated sediments of Quaternary age comprising silt, clay, sand of various grades, gravel and kankar in varying proportion. Study of the boreholes drilled by C.G.W.B. under its exploratory/deposit well programme and a subsequent perusal of sub -surface geological cross sections,(i) The unconsolidated alluvial sediments deposited over the undulatory surface of the basement rock, (encountered in borehole at Panki at the depth of 505 mbgl) show alternative clay and granular beds. The sandy horizons at different depths form the main repository of ground water.(ii) The thick pile of sediments down to bed rock broadly, consist of 3 tier aquifer system as 1st Group of Shallow Aquifers (upto 150 m) depth bgl),2nd Group of Moderately Deep Aquifers (Existing between 150-250m depth),3rd Group of Deep Aquifers (below 250 m depth). 3.5 Climate Kanpur’s climate is characterized by hot summer and dryness except in the south west monsoon season. The climate in Kanpur can be divided broadly into four seasons. The period from March to the mid of June is the summer season which is followed by the south-west monsoon, which lasts till the end of September, October and first half of November from the post -monsoon or transition period. The cold season spreads from about the middle of November to February. The climate is of a tropical nature and shade temperature varies from 200 C to 480 C. Rainy season extends from June to September, with the period of maximum rainfall normally occurring during the months of July and August. About 89 percent of the annual rainfall is received during the monsoon months (June to September). The total rainfall in the district varies from between 450 mm to 750 mm. The annual rainfall in Kanpur Nagar was recorded 441 mm in actual in 2004 and 783 mm in general (Statistics Diary 2005). The relative humidity varies from 15% to 85%. The relative humidity in Kanpur ranges from less than 30 percent in the summer season to 70 percent in monsoon season. 4. DATA USED Resourcesat-1 LISS III of Indian Remote Sensing Satellite were used for landuse mapping. LISS III (Linear Imaging Self Scanning System) sensor has 23.5 spatial resolution and four bands such as Green (0.52 - 0.59 μm: band 1), Red (0.62 - 0.68 μm: band 2), NIR (0.77 - 0.86 μm: band 3) and SWIR (1.55 - 1.70 μm: band 4). Apart from the space-based data, ancillary data such as topographic map on 1:50,000 scale with a 20 m contour interval were also used in this study.

Fig. 2: Satellite Image of Kanpur City

Software Used ERDAS 9.0 – has been used for digital image processing and creation of various themes. ARC GIS 9.1 - has been used for data integration and generation of maps. 5. METHODOLOGY Keeping in view the objective and research question, literature was consulted to select appropriate and relevant research methods for this study. Visual or digital image interpretation techniques are applied to extract information from imagery data. In this way a map showing various land use and land cover types and different thematic layers of the area was produced. 5.1. Image Geometric Correction and Subset Geometric correction includes correction of geometric distortions due to sensor, scanning system, the curvature and rotation of the earth. It is one the digital image pre-processing functions that is normally required prior to main data analysis. The errors can be corrected by using a suitable number of Ground Control Points (GCP) that are points on the earth whose both image coordinates and map coordinates are known. The IRS LISS III imagery was geo-coded using the reference points from the respective GCPs. From the geo referenced imagery, the study area of was extracted from the data preparation tool in Erdas i.e. a subset of the study area was created. 5.2. Image Enhancement Image enhancement is one of the important image processing functions. It is the improvement of the digital image quality and to assist in subsequent visual interpretation and analysis. Image

enhancement involves techniques for increasing the visual distinctions between features by improving tonal distinction between various features in a scene using technique of contrast stretching.

Fig.3.Flow chart showing methodology of landuse/landcover mapping. 5.3. Image classification The image classification is the most important part of digital image analysis. The objective of image classification is to automatically classify all the pixels in a digital image into one of the several land cover classes or themes. The statistical based decision rules are applied for determining the land cover identity of each pixel in an image. Digital image classification uses spectral information represented by the digital numbers in one or more spectral bands to classify each pixel based on the spectral information. There are a variety of approaches taken to perform digital classification. In the present study one of the approaches was performed, namely unsupervised classification. Unsupervised classification is a technique that groups the pixels into clusters based on the distribution of the digital numbers of the image. In this type of classification, the identifies of land-cover types to be specified as classes within a scene are not generally known a prior because ground reference information is lacking or surface features within the scene are not

Layer stacking of the Bands

Image Rectification

Satellite Image of IRS LISS- III

Area Calculation

Image subset

Land use/Land cover

Image classification

Image enhancement

similar spectral characteristics into unique clusters according to some statistically determined criteria. The analyst then re-labels and combines spectral clusters into information classes. 5.4. Land use/ Land cover Mapping The classes that result from the unsupervised classification are spectral classes. Because they based on the natural groupings in the image values, the identity of the spectral classes will not be known earlier. Unsupervised classification (assigning 80 classes) was performed on the subset imagery of the study area. The 80 classes were regrouped into four classes built-up land, agricultural land, open land, and water bodies. 5.4.1. Recoding and Area Calculation Different thematic layers such as Dense urban, Medium urban, Urban with vegetation, Sub urban, Airport, Park/Plantation, Agriculture, Water/River, Open land, River bed, Industrial area and Miscellaneous were made to mosaic over the base map by recoding so as to prepare the final land use/land cover map for the study area. After generating the different thematic layers the area information were extracted from the attribute table and then transferred to the Microsoft excel sheet. Then we calculate the area of different land use/ land cover classes in sq.km and the area of percentage covered of the total area of Kanpur city. 6. RESULT The objective of this study forms the basis of all the analysis carried out in this chapter. The results are presented inform of maps, charts and statistical tables. They include the static, change and projected land use land cover of each class. In the land use/land cover mapping we apply unsupervised classification method. In the classification method, we derive twelve land use/ land cover classes, which are as follows:-

Figure 4: Land use/ Land cover Map of Kanpur City

These are the present statistics of the Kanpur city generated and calculated by Land sue / land cover map.

Table 1: Land Use Land Cover Distribution

Class Area in hectares Area in Sq km Percentage

Dense Urban 1069.63 10.70 1.36

Medium Urban 11882.02 118.82 15.07

Urban with Vegetation 848.97 8.49 1.08

Sub Urban 3506.11 35.06 4.45

Airport 124.42 1.24 0.16

Agriculture 29629.56 296.30 37.58

Park/ Plantation 830.94 8.31 1.05

Industrial Area 287.19 2.87 0.36

Water/River 2210.11 22.10 2.80

Open Land 19294.33 192.94 24.47

River Bed 1426.35 14.26 1.81

Miscellaneous 7737.52 77.38 9.81

Total 78847.14 788.47 100.00

Figure 5: (a) Graph showing the Area covered by different land use/ landcover classes according to the generated map (b) Percentage of area covered by different land use/ land cover classes 7.0 CONCLUSION The present study dealt with the analysis of spatial and temporal changes that have been taken place in Kanpur city using remote sensing and GIS. The classification of land use/ land cover for the study area was performed using unsupervised classification method. From the present study it was found that extensive urbanization in Kanpur city is an outcome of increasing population mainly through in-migration and industrialization. Satellite data used for the presents study gave a clear view of the significant changes that have taken place in the land use/ land cover pattern for Kanpur city. Post classification comparison has been done with the help of available census data. From the analysis of the census data as well as land use/ land cover map generated from the satellite data it has been observed that there have been significant changes in the different land use/ land cover pattern of Kanpur city. The Major findings of the study included considerable decline in the cultivated land and intensive urban development. From the observations made in the study, it should be mentioned that Kanpur has grown haphazardly as the growth pattern deviated from the land use norms set in the Kanpur’s city master plan as city development plan developed by Kanpur Nagar Nigam under the Jawaharlal Nehru National Urban Renewal Mission (JNNURM). This has occurred largely due to extensive increase of small scale sector drawing greater employment opportunities for the people migrating from the neighboring states. It has been observed that Kanpur has grown in all direction, while a planned growth should occur along the defined and the well developed transport corridors. Kanpur has followed the traditional urbanization pattern with the mixed pattern of commercial and residential use with the effect there has been substantial increase in the squatter population of Kanpur. The future scenario of Kanpur would include increase in the present limits in the urban boundary with the necessary urban extension required for accommodating the increasing pressure of growing population.

Area in Sq km

10.70118.82 8.49

35.06

1.24

296.302.87

22.10

192.94

14.2677.38

8.31

Dense Urban

Medium Urban

Urban with Vegetation

Sub Urban

Airport

Agriculture

Park/ Plantation

Industrial Area

Water/River

Open Land

River Bed

Miscellaneous

Percentage

1.3615.07 1.08

4.45

0.16

37.580.36

2.80

24.47

1.819.81

1.05

Dense Urban

Medium Urban

Urban with Vegetation

Sub Urban

Airport

Agriculture

Park/ Plantation

Industrial Area

Water/River

Open Land

River Bed

Miscellaneous

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