Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

&nbsp;

&nbsp;

VIT University

Analysing the changes in various landuses during the past, identifying the direction and type of urban sprawl, modelling its causative factors and predicting the future sprawl are some of the key areas which urban planners are generally interested in as they help them to properly plan cities in a more efficient way. In the present study, an attempt has been made to address these key areas using open-source geospatial data for the city of Vellore in India which has experienced significant urban growth in recent decades. Landuse maps were prepared using aerial photos, topographic maps and satellite images for the period 1967–2019 and using that a comprehensive urban sprawl analysis was carried out. The results indicated that the major highways that pass-through Vellore have strong influence on urban development as ribbon type of sprawl was witnessed along the principal transportation corridors. This has been confirmed while modelling of causative factors that when distance from highway increases, built-up density decreases. Similarly, the location of central business district (CBD) found to play a crucial role in urban growth as built-up density decreases when distance from CBD increases. Regression models were built to calculate the built-up density at any distance from city centre or major roads in space–time domain. The present study also developed models based on Seasonal ARIMA to forecast the future built-up density for the year 2045 using the built-up densities of 1967, 1991 and 2019. The results showed that more development is expected on suburban areas as those are the places where one can expect development to take place when compared to the interior zones which were already developed much during the past years. The methodology reported in this paper is well applicable for any city or town to analyse the landuse changes, model the causative factors and predict its future sprawl using completely the open-source data. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

World University root node

Department of Environmental and Water Resources Engineering

School of Civil Engineering

Vellore Campus

Modeling Earth Systems and Environment

Urban sprawl modelling and prediction using regression and Seasonal ARIMA: a case study for Vellore, India

Abstract. India being an agrarian nation widely depends upon rainfall for its agricultural productivity. The failure of rainfall and hence shortfall of productivity badly affects national economy. With an intricate nature of drought, the planning and management requires rigid monitoring for better understanding. The occurrence of drought and its severity varies in a regional level. The process of monitoring agricultural drought in a regional level requires long term analysis of vegetation. In this present work, the attempt has been carried out to study and monitor the spatial and temporal variation of agricultural drought for the state of Tamilnadu, India which is more prone to drought especially due to monsoon failure or change in monsoon. The long term Normalized differenced vegetation index (NDVI) of Global Inventory Modelling and Mapping Studies (GIMMS) for the period of 20 years (1984&amp;ndash;2003) was used to compute the most popular index called vegetation condition index (VCI) to identify the vegetation vigour. The fortnightly variation of VCI during major crop growing period of Kharif season (June to September) was used to monitor the spatio-temporal drought conditions of Tamil Nadu. The results proved that there is wide variation of drought intensity among the districts within the state. The keen observation of fortnightly variation of long term agricultural drought helps finding the onset, period and spatial extent of drought in various districts of the state. The districts which are most often prone to moderate to severe drought conditions during the analysis period were recognized in order to develop various strategies to improve the agricultural productivity in that region. The persistent drought in the state necessitates the government to take appropriate preventive measures to evade drought in future. Based on the severity of the drought level observed from the agricultural drought intensity maps prepared using VCI, the action plans could be prioritized by identifying the high risk zones.

Chennai Campus

Fulltext

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

MONITORING OF AGRICULTURAL DROUGHT USING FORTNIGHTLY VARIATION OF VEGETATION CONDITION INDEX (VCI) FOR THE STATE OF TAMIL NADU, INDIA

Increasing urbanization in Vellore, Tamilnadu creates a serious anthropogenic pressure resulting rapid change in land cover in recent time. Changing land use condition affects surface temperature. The relationship between surface temperature and land cover types has been studied for Vellore district interpreting satellite image of landsat-7 ETM+thermal infrared bands and values of NDVI for 2016. Analysis reveals that urban and most populous areas have higher surface temperature (35-43°C) than temperature in the dense forest cover areas (13-27°C) with high NDVI value (0.98) in scrub land and low value (-0.95) in water bodies. Several eco-geological influencing factors those interplay to bring about change in land cover were found correlated with thermal infrared band spectra and NDVI values. The study envisages the utility of thermal spectra and land use/land cover change in urban planning. © 2018 Technoscience Publications. All Rights Reserved.

Nature Environment and Pollution Technology

Relationship between surface temperature and land cover types using thermal infrared band and NDVI for Vellore District, Tamilnadu, India

VIT Unitversity

International Journal for Research in Applied Science and Engineering Technology

Engineering Study Of Bhuj Earthquake And Mitigation Measures

IOP Conference Series: Materials Science and Engineering

Comprehensive characterisation of groundwater quality in and around a landfill area for agricultural suitability

The spatio-temporal study of long term agricultural drought for monsoon dependent countries like India is very essential in order to develop various strategies to improve the agricultural productivity in the country. In the present study, an attempt has been made to assess the long term agricultural drought for period of 20 years from 1984 to 2003 for the state of Tamil Nadu, India using one of the popular NDVI based index called vegetation condition index (VCI). The Normalized differenced vegetation index (NDVI) from Global Inventory Modeling and Mapping Studies (GIMMS) has been used in the present study to compute the VCI for every fortnight during the crop growing period of June to September. The results showed that the state is experiencing moderate to severe drought situation during most of the years in the analysis period of 1984 to 2003. The recurrent drought in the state necessitates the government to take suitable preventive measures to avoid drought in future. The agricultural drought intensity maps prepared using VCI will help the state government authorities to identify the drought risk areas and prioritize their actions based on the severity of the drought level. © IAEME Publication.

International Journal of Civil Engineering and Technology

GIS based agricultural drought assessment for the state of Tamilnadu, India using vegetation condition index (VCI)

The study of long term agricultural drought becomes essential for monsoon dependent countries like India in order to identify the drought prone areas and develop various strategies to improve the agricultural productivity in the country. The present study attempted this by assessing the long term agricultural drought for a period of 20 years from 1984 to 2003 for the State of Tamil Nadu, India using one of the popular indexes called Normalized Differenced Vegetation Index (NDVI) anomaly. The NDVI from Global Inventory Modeling and Mapping Studies (GIMMS) which is an open source data, has been used in the present study to compute the NDVI anomaly. The agricultural drought intensity maps prepared using NDVI anomaly will help the state government authorities to identify the drought risk areas and prioritize their actions based on the severity of the drought level. The result showed that the State experienced moderate to severe drought situation during most of the years in the analysis period of 1984 to 2003. The drought affected area and its percentage in the entire state during the study period confer the fact that the current drought condition of the state could have been foreseen two decades back and hence enabled the agrarian society to be precautionary. The recurrent drought in the state necessitates the Government to take suitable preventive measures to avoid drought in future.

Disaster Advances

Assessment of long term agricultural drought in Tamilnadu, India using NDVI anomaly

Mapping of land use changes using satellite imagery are essential due to its various applications. The present study has been conducted in urban and semi-urban areas of Vellore district, Tamil Nadu, India to analyse the dynamics of land use changes during 1977 - 2015 using multi-temporal satellite images like Land sat 1977 MSS, TM 2009 and SR, OLI/TRS 2015 respectively and were detected by ERDAS IMAGINE 2014.Three land use classification maps (1977, 2009 and 2015) were developed. Analysis shows that urban area has been increased more in 2015 (26.46%) than in 1977 (1.93%) which will further be increased by 37.58% in 2035. Interestingly, it predicts that agricultural land and crop land will be increased by 433.77 km2 and 113.4 km2 subsequently in future. It is assumed that the analysed results of the study will help district administration for framing the ground of making Vellore as a smart and sustainable city. © Research India Publications.

International Journal of Applied Engineering Research

Remote sensing and GIS technique enable to assess and predict landuse changes in Vellore district, Tamil Nadu, India

The study of long term meteorological drought for monsoon dependent countries like India is very essential for planners and policy makers to develop various strategies to improve the agricultural productivity in future. In recent years, an average of nine farmer suicides per day is reported which indicates the severity of the problem due to increasing drought prone areas in India. Spatio-temporal analysis of meteorological drought for Tamilnadu state in India was attempted in the present study using one of the widely used indices called Standard Precipitation Index (SPI) with 30 years of rainfall data (1980-2009) as input and year wise drought intensity maps were prepared using Geographic Information Systems (GIS). It was found that the year 2002 is the worst affected year as more than 20 districts have experienced extreme drought conditions due to insufficient rainfall. It was noticed from drought intensity maps that extreme drought conditions do not occur all of a sudden in one year and occurs over a period of at least 2-3 years. This necessitates the government to be alert and to take suitable preventive measures whenever the trace of severe or extreme drought conditions is felt in a year. Modelling of SPI using rainfall deviation as independent variable was also attempted using regression analysis as strong positive correlation exists between SPI and rainfall deviation with Pearson's correlation coefficient of above 0.98 was obtained for most of the districts. Second order and third order polynomial models were fitted for various districts and state respectively with R2 values of above 0.8. The developed regression models can be used to determine well in advance, the district wise or state as a whole, the level of dryness or wetness in future years which will facilitate planners and policy makers to take suitable steps for drought preparedness and mitigation. © 2017, Disaster Advances. All rights reserved.

Spatio temporal analysis and modelling of meteorological drought for the state of Tamilnadu, India using Standard Precipitation Index (SPI) and GIS

Procedia Technology

Use of High Resolution Google Earth Satellite Imagery in Landuse Map Preparation for Urban Related Applications

Geotechnical and Geological Engineering

Spatial Variability of Rock Depth Using Simple Kriging, Ordinary Kriging, RVM and MPMR

Department of Analytics

School of Computer Science and Engineering

Journal of the Indian Society of Remote Sensing

Estimation of surface runoff in Malattar sub-watershed using SCS-CN method