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.

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VIT University

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.

School of Civil Engineering

Chennai Campus

Department of Environmental and Water Resources Engineering

Vellore 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

With the growing trend of population and migration of people from rural to urban area, the cities of nation are becoming overcrowded. To manage the needs of people and also to safeguard the resources available, the planners and policy makers need to have a current landuse map of any city or town. The present study focuses on the preparation of landuse map of Chennai, the capital city of Tamilnadu. As the growth of the city is fast and uncontrollable, it would be well prudent if the landuse map of present-day city has been prepared. Though there are wide sources like Global Landcover Facility (GLCF) are available to get free satellite images and many studies have been carried out by preparation of landuse/landcover map from them, the attempt has been made to prepare landuse map from the very prominent web map service render by Google Earth images. The extraction of image tiles from Google Earth is made possible using an open source software named Elshayal Smart. The whole Chennai city could be covered using 735 individual tiles of Google earth images. After mosaicking and clipping the required city bound, onscreen digitization of various landuses/landcovers was done using ArcGIS software. The establishment of topology and hence the area of various classes were then obtained. The area occupied by built-up area is 126.58 sq.km, which is the highest as compared to other landcover classes like agricultural area (16.44 sq.km), open land (12.80 sq.km) and water bodies (07.19 sq.km). The results of landuse/landcover analysis of various zones of Chennai city would facilitate the city planners to maintain sustainable growth. ©IAEME Publication.

World University root node

International Journal of Civil Engineering and Technology

Land use / landcover mapping and sustainability analysis of Chennai city, Tamilnadu, India

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.

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

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

Landslides are the most frequently occurring events in the region of Nilgiris, especially during the monsoons for many decades. Such events are known for its damages that occurred on cut slopes or embankments alongside roads and highways in mountainous areas. Few landslides also occur in residential areas, causing death to human beings. So, it becomes highly essential to plan and mitigate the occurrences. Many efforts are being made to assist administrative authorities and local planners in identifying such vulnerable areas in hilly terrains which derive Landslide Hazard Zonation (LHZ) and Vulnerability map of concerned region/locality, like the National LHZ atlas/Vulnerability atlas at Macro level for India. In this study an attempt is made to generate a regional level LHZ map for Nilgiris district of Tamil Nadu, India, taking into account some of many causative and triggering factors like Slope, Rainfall, Geology and Landuse which are considered to be predominant in that area. One of the multi-criteria decision making techniques is Analytical Hierarchy Process (AHP), which provides a systematic approach for assessing and integrating the impact of various factors and it was used for preparation of LHZ map. The weightages derived through the process were used in "weight-averaging" the map layers to get LHZ map as an output for this region. Vulnerability analysis was carried out using the map overlay technique in GIS to identify and report vulnerable roads and settlements. Landslide Hazard Zonation (LHZ) map was integrated with Transportation (Road) Network map and Settlements map which resulted in generation of maps showing varying degree of vulnerability on roads and settlements. The results were compared with landslide inventory map and proved efficient in areas of high hazard potential. It was found that 1235 km of roads are highly vulnerable to landslides. Villages like Burliar, Kengarai, Kanakarai, Kinnakkorai, Mulligoor, Nanjanad, Thummanatti and Nellakotta need immediate attention for retrofitting of slopes.

Department of Structural and Geotechical Engineering

Regional Landslide Hazard Zonation and Vulnerability analysis using AHP and GIS - A case study of nilgiris district, Tamil Nadu, India

In developing country like India greater attention has been focused so far only on the ground water pollution. Unlike water the study on the soil contamination has not been much attended yet. In this background, it becomes necessary to study the soil contamination in Dindigul, where the soil is mostly degraded by tannery effluents. In order to assess the extent and level of soil contamination, soil samples were takeq at 60 locations in and around tannery industries and tested for various chemical parameters like Electrical conductivity, pH, Nitrogen, Phosphorus, Potassium, Iron, Manganese, Zinc and Copper. The GIS has its application in modeling pollution characteristics via generating continuous surfaces, overlay analysis etc. The interpolation method "kriging" was used to generate continuous surfaces for all the soil parameters. It is a process of using points with known values to estimate values at unknown points ie., a process of filling in data between the sample points. The overlay analysis was then performed by assigning weightages to the soil parameters to arrive the contamination levels. The results show that most of the areas were highly contaminated which make the land unfit for agriculture. Copyright © Enviromedia.