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Modelling and Monitoring Urban Landscape Dynamics over Haridwar, India

by Nitin Malik, Sakshi Gothi, Ritu Saini, Pradeep Aswal
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 45
Year of Publication: 2019
Authors: Nitin Malik, Sakshi Gothi, Ritu Saini, Pradeep Aswal
10.5120/ijca2019918569

Nitin Malik, Sakshi Gothi, Ritu Saini, Pradeep Aswal . Modelling and Monitoring Urban Landscape Dynamics over Haridwar, India. International Journal of Computer Applications. 181, 45 ( Mar 2019), 12-15. DOI=10.5120/ijca2019918569

@article{ 10.5120/ijca2019918569,
author = { Nitin Malik, Sakshi Gothi, Ritu Saini, Pradeep Aswal },
title = { Modelling and Monitoring Urban Landscape Dynamics over Haridwar, India },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2019 },
volume = { 181 },
number = { 45 },
month = { Mar },
year = { 2019 },
issn = { 0975-8887 },
pages = { 12-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number45/30420-2019918569/ },
doi = { 10.5120/ijca2019918569 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:09:09.824452+05:30
%A Nitin Malik
%A Sakshi Gothi
%A Ritu Saini
%A Pradeep Aswal
%T Modelling and Monitoring Urban Landscape Dynamics over Haridwar, India
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 45
%P 12-15
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Rampant urbanization brings opportunities for new infrastructural developments, however, it also has brought serious losses of vegetation land, forest land and water resources. The modelling and projecting of land use pattern is essential to document the urban profile of the city and assessment of consequent environmental impacts. Current study aims to highlight the impact of rapidly urbanizing Haridwar city not only inside the boundaries of the city but also its neighboring rural and semi urban areas. In the first part of the paper, one of the most popular supervised classification algorithm (maximum likelihood) is implemented to quantify the human inference in the city. In the second part the impact is calculated by executing an Urban Landscape Dynamics tool. In order to temporally access the impact of urbanizing, openly available land sat satellite images are used for the year 2008 and 2016.

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Index Terms

Computer Science
Information Sciences

Keywords

Remote Sensing GIS Land Use Land Cover Urban Growth Modeling Urban Landscape Dynamics

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