Sustainable Development Practices Using Geoinformatics. Группа авторов
The completion of this edited book entitled “Sustainable Development Practices Using Geoinformatics” could not have been possible without the grace of almighty God.
We are grateful to Hon’ble Sunil Sharma, Chairperson, Suresh Gyan Vihar University, Jaipur for his encouragement and support. The words cannot express our indebtedness to Hon’ble Dr. Sudhanshu, Chief Mentor, Suresh Gyan Vihar University, Jaipur for his continuous guidance, expert suggestions and motivation during the completion of this edited book.
Special thanks are due to all the reviewers for their time to review the chapters. The editors would like to express heartfelt gratitude to all the members of editorial advisory board for their endless support and valuable instructions at all stages of the preparation of this edited book. We would like to mention the names of the members of editorial advisory board as Prof. M. S. Nathawat, IGNOU New Delhi, India; Dr. (Mrs) Tapati Banerjee, NATMO, Kolkata, India; Prof. Milap Punia, JNU, New Delhi, India; Prof. Rajendra Prasad, IIT (BHU), Varanasi, India; Dr. Devendra Pradhan, IMD, Government of India, New Delhi, India; Prof. Manoj K. Pandit, University of Rajasthan, Jaipur, India, Dr. Snehmani, SASE, DRDO, Chandigarh, India, Prof. Shakeel Ahmed, Jamia Millia Islamia, New Delhi, India; Prof. Suresh Prasad Singh, Himalayan University, Itanagar, India; Mr. Peeyush Gupta, NMCG, Ministry of Jal Shakti, Government of India, New Delhi, India
To all the colleagues, friends, and relatives who in one way or another shared their constant and moral support. The editors are eternally thankfully to Scrivener Publishing for giving the opportunity to publish with them.
Dr. Shruti KangaDr. Varun Narayan MishraDr. Suraj Kumar Singh Editors June 2020
1
The Impact of Rapid Urbanization on Vegetation Cover and Land Surface Temperature in Barasat Municipal Area
Aniruddha Debnath, Ritesh Kumar*, Taniya Singh and Ravindra Prawasi
Haryana Space Applications Centre, Hisar, Haryana, India
Abstract
India is a developing country and its growing phase is facing the trio of urbanization, modernization, and globalization. The study pertains to find out the impacts of rapid urban development on vegetation cover and its inter-relationship with the variability of Land Surface Temperature (LST). The study area, Barasat municipality, is facing rapid urbanization since mid of 1990s; hence, the number of people residing in Barasat is increasing rapidly, resulting in dense, concrete, and high-rise buildings. The Barasat city is adjacent to Kolkata metropolitan city and is a part of Greater Kolkata. Therefore, there is escalation in number of multi-storied buildings along with proliferating population leading to urban sprawl in the study area. These facts promote Barasat to be an Urban Heat Island (UHI). The study aims to show the change in variability of surface temperature from 2001 to 2017 with the help of geospatial techniques and using Landsat data of multiple dates in order to uncover the modification/variation in the urbanization and then correlate it with NDVI (Normalized Difference Vegetation Index), and LST. The 17 years’ time scale is very small period for change detection of urban land use change but enough to show the urban growth and its pattern and trend in relation to surface temperature variation. The remote sensing and GIS provides very useful tool for the analysis of changes in environmental condition due to human activity in the study area.
Keywords: Urbanization, UHI, NDVI, LST
1.1 Introduction
Urban land is primary resultant feature on the Earth surface, induced by human activities from centuries. Urban area is defined as the area having facilities of higher administrative departments in which most of the population belong to secondary and tertiary division, these segments comprises a city or a town, etc. (McGranahan, Satterthwaite, and International Institute for Environment and Development 2014). Urbanization can be simply defined as the conversion of any spatial entity from rural to urban with the help of technology and sustainable uses of resources (Datta 2007). Since ancient era, modification, and transformation of the geographical areas are steady, and great example of this is urban landform. World’s earliest industrial revolution took place in Britain in the 18th century, which caused the rural mass movement toward cities. This era was considered to be the footstep of urbanization. However, in India, the wind of urbanization was initiated by the Britishers, while India being once a domicile of British Empire. The modification in the settlements and settlement zone continue to vary till date, which commences urban sprawl (Narayan 2014).
In the phases of urban development, continuous changes on land surface are observed, from small houses to tall buildings, agriculture to industry, pervious surface to impervious (paved) surface, kaccha road to highway, etc. (Grimmond 1998; Gál and Unger 2009). The two most important controlling factors responsible for the development and also retreat of urban region are pull factors and push factors. With the rapid urban sprawl, it results in the increase of inhabitants with a balance of demand and supply. Along with the proliferation of the crowd toward a separate area, there is burgeoning demand of supply for the inhabitants, which further entice entrepreneurs. The urban sprawl cannot be controlled; hence, it appears as an interrelated network of a complex system. The socio-economic development of an urban area is an impact of migration that escalates the growth of urban society. The constant process of growth leads to urban spread and agglomeration, which is continually an ongoing process (Yeh and Li 2001).
The scope of application of “Remote Sensing and GIS” is widening day by day from cryosphere to biosphere to hydrosphere to atmosphere, etc. Subject to mankind, most of application parts are broadly used like study of land cover dynamics, spatial growth, trend analysis, rainfall monitoring, zoning of hazard risk assessment mapping, global climatic imbalance, atmospheric phenomenon, etc. (Wijeatne and Bijker 2006). Contemplating the urban application part, it is largely used in the fields of urban morphology structure, urban flooding, urban planning, ventilation mapping, urban climatic zones, urban pollution, urban population, urban growth modelling, etc. (Grimmond and Oke 1999; Gál and Unger 2009; Mirzaei 2015; Wong, Nichol, and Ng 2011). With the advancement in technologies, it is aimed to gather data from the underground and under water also. Various endeavors were done to discover the prototype of urban growth and examine the several spatial patterns of urban area with the help of various algorithms including geographical weighted regression, Sleuth model, multivariate regression, etc. In India, the urban growth scenario is changing rapidly and poses complexity in measuring urban growth parameters, but use of remote sensing and GIS techniques are becoming handy in to perform analysis on urban growth and its impact on natural vegetation and local surface air temperature.
Urban sprawl is a continuous process, which leads to decrease in the amount of green space and increase in the density of concrete garden of buildings (Capozza and Helsley 1989). To demarcate the consistency of vegetation canopy layer, NDVI (Normalized Difference Vegetation Index) is a very useful index (Bhandari, Kumar, and Singh 2012; Volcani, Karnieli, and Svoray 2005). The increase density of buildings is the major cause of increasing surface air temperature that is trapped by the building infrastructure (Unger, Sümeghy, and Zoboki 2001). From this point of view, the concept of Land Surface Temperature (LST) is inspired, which is the temperature of the near surface area within specified limit, but it is entirely different from atmospheric temperature. The LST is a new emerging concept in the field of remote sensing and it plays a key role in establishing an inter-relation between NDVI and LST (Deng et al., 2018). The relationship between LST and NDVI ponders on the concept of surface temperature in cram-full areas (Yuan and Bauer 2007). From this point of view, the area can be delineated as a Heat Island as the core area of the city experiences relatively high temperature than the surrounding and rural areas. The domain of UHI can be easily detected using these two crucial indices. The urban area that is comparatively hotter than the surrounding area can be considered as a UHI (Tso 1996).
India is home of 1,210,193,422 people (Census of India, 2011) and having a population density