Qualification: 
Ph.D
p_geetha@cb.amrita.edu

Dr. Geetha Srikanth currently serves as Assistant Professor (Sr.Gr.), at Amrita Centre of Excellence in Computational Engineering and Networking (CEN), Coimbatore Campus.

Professional Activities

  1. Coordinator for online IIRS Outreach Programme course on “Hyper spectral Remote Sensing and its Applications” conducted by Indian Institute of Remote Sensing during February 19, 2018 to March 12, 2018.
  2. Coordinator for online training course on “Close Range Photogrammetry and Terrestrial Laser scanning” conducted by Indian Institute of Remote Sensing during January 08, 2018 to January 12, 2018.
  3. Coordinator for online training course on “Overview of RS & GIS Applications for Natural Resource Management” conducted by Indian Institute of Remote Sensing during November 13, 2017 to December 01, 2017
  4. Participated in the 2-days workshop on “Integrated Urban Development and Co-Production for Indian cities: Water and Energy” organized by Technical University Berlin on the behalf of the Indo-German smart Initiative (IGSI) Urban Lab #2 Workshop from 6th – 8th December, 2017 at the Karunya Institute of Technology in Coimbatore.
  5. Participated a FDP on Advances in Waste Water Treatment and Air Pollution control techniques for "Air pollution" held by AICTE sponsored FDP at Annamalai University, Chidambaram from 13-25th November 2017.
  6. Coordinator for online training course on “Basics of Remote Sensing, Geographical Information System and Global Navigation Satellite System” conducted by Indian Institute of Remote Sensing during August 21, 2017 to November 18, 2017
  7. Organized the “Shared Task & Workshop on Machine Translation Systems in Indian Languages” (MTIL) – 2017 conducted at Centre for Computational Engineering and Networking (CEN) in association with CTTL, Mysore on September 7- 8, 2017.
  8. Invited as an external expert for the Selection Committee Meeting for the post of Research Assistant under DST-SERB project at Avinashilingam University on September 1, 2017.
  9. Coordinator for online training course on “Basics of Remote Sensing, Geographical Information System and Global Navigation Satellite System” conducted by this Indian Institute of Remote Sensing during August 22, 2016 to December 04, 2016.
  10. Participated in the NAAC –sponsored National Seminar on “Curriculum Design for Sustainable and Societal Development: A Road Map” held at Amrita Vishwa Vidhyapeetham (University), Coimbatore on August 12 - 13, 2016
  11. Coordinator of the online training course on “Basics of Remote Sensing, Geographical Information System and Global Navigation Satellite System” conducted by Indian Institute of Remote Sensing during August 10, 2015 to November 27, 2015.
  12. Participated the one day workshop on “Magic of Millets” organized by the Food, Nutrition and Health Education Centre, as part of World Food Day Celebrations on November 6, 2015.
  13. Co-ordinator for Edusat Programme for Remote sensing students conducted from IIRS Dehradun organized a workshop on CANSAT Building on April 25 - 26, 2015.
  14. Presented a paper @ the 4th IEEE ICCSP- 15 Conference at Adhiparasakthi Engineering College, Melmaruvathur from April 1 - 5, 2015.
  15. Participated in the National level workshop of GADM at Shakthi Institute of Engineering Technology, Coimbatore from February 25 - 27, 2015.
  16. Participated in the workshop regarding “Small Satellite Design and Development” at PES University, Bangalore from January 3 - 5, 2015.
  17. Chaired a session in the National-level conference “Environmental Conference 2014” organized by the Dept. of Environmental Science, Central University of Kerala on February 17 - 19, 2014.
  18. Participated in the “Dhruti: The Conference of women researchers in computing” at Amrita Vishwa Vidhyapeetham, Coimbatore from January 9 - 11, 2013.
  19. Coordinated “AMRITA Insight into Computer Aided Drug Design (AICADD – summer – 2012)” workshop cum hands on project training conducted by Computational Chemistry Group (CCG) of Centre for Excellence in Computational Engineering and Networking (CEN) at Amrita Vishwa Vidhyapeetham, Coimbatore from July 2, 2012 to July 11, 2012.
  20. Participated in the International Workshop on “WEBGIS AND ECOINFORMATICS” jointly organized by IIITM-K, Stuttgart University of Applied Sciences, Germany, Dept. of Geology, Govt. College Kottayam, India and Stuttgart Active Alumni Group – S & SE from October 28 - 30, 2008 at IIITM-K, Technopark, Thiruvanthapuram, India.

Invited Talks

  • Delivered a lecture at Sree Narayana Guru college Coimbatore Role of Biotechnology for future India March 5, 2019
  • Invited as a State Resource person to give a talk on Plastic a Boon or a Bane conducted by Tamilnadu Pollution control board throughout Tamil nadu(Coimbatore, Dharmapuri Salem,Trichy Madurai)During December 15-30.
  • Chaired a session in International conference on AMRITA International Public Health Conference – 2018 at Dept of community medicine Amrita Institute of medical Sciences Kochi
  • Invited talk on Coastal Ecosystem using Remote sensing and GIS at Chikkanna college of arts and science tiruppur on February 10, 2018.
  • Invited as a speaker for one day workshop on Writing a successful thesis or Dissertation Tips and strategies on January 11, 2018 at Sri Krishna college of Engineering and Technology Coimbatore-8
  • Delivered a lecture on "Mapping of Vector Borne Diseases using GIS" at PSGR Krishnammal College for women on September 26, 2017.
  • Delivered a talk on "Satellite Image Processing" at Avinashilingam University for Women on September 15, 2017.
  • Invited and Conducted a Two day workshop on "Geographic Information System (GIS) in control of vector borne diseases" by Department of Community medicine during June 14 – 15, 2017 at Sri Devaraj urs Medical College, Kolar.
  • Chaired a session in International conference on Environment and Health in changing climate at Department of Environmental Biotechnology. School of Environmental sciences Bharathidasan University September 14-16, 2016
  • Delivered a Guest Lecture on “Remote Sensing and GIS” conducted by Dept. of Civil Engineering at Jay Shriram Group of Institutions on February 10, 2016.
  • Delivered a Guest Lecture on “Application of Remote Sensing and GIS for Disaster Management” at Dept. of Environmental Sciences, Bharathiar University, Coimbatore on December 15, 2014.
  • Invited as chief guest for “Colours Day” at Bharathi Matriculation Higher Secondary School, Coimbatore on June 2015.
  • Guest Speaker in one day seminar on “GIS in conservation of natural resources” at Nehru Arts and Science College, TM Palayam, Coimbatore on January 9, 2013.

Achievements

  • Gold Medallist in PG for obtaining first rank in Bharathiyar University
  • Texmo Ramasamy Memorial Gold Medallist for obtaining first rank in Bharathiyar University.
  • Jawaharlal Nehru memorial award from Teen Murti Bhavan, New Delhi for obtaining first Rank in Bharathiyar University.
  • Ph. D. thesis highly commanded
  • Proficiency Prize in UG and PG
  • Best outgoing student from KASC Coimbatore during 1993

Funding Projects

Name of the Project

Funding Agency

Implementation

Improving Coconut Production in Kerala Using Soil data Through Remote sensing and GIS techniques

Coconut Development Board, Government of India,Kochi-Kerala

GIS,In Field Survey,Soil Suitability Analysis,Waterflow,Mineral Strength,Mapping of GIS database For three Years From 2013-2016

Publications

Publication Type: Book Chapter

Year of Publication Title

2019

Dr. Geetha Srikanth, “Toxicity Remediation, In:Environmental Toxicity Risk Assessment”, in MEV-004 Environmental Toxicology, IGNOU, 2019, pp. 28-43.

2019

Dr. Geetha Srikanth, “Toxicity Risk Assessment Planning, In:Environmental Toxicity Risk Assessment”, in MEV-004 Environmental Toxicology, IGNOU , 2019, pp. 13-27.

2019

Dr. Geetha Srikanth, “Industrial Safety Organization, In:Industrial Safety Management”, in MEVE-004 Industrial Sector, IGNOU , 2019, pp. 51-60.

2019

Dr. Geetha Srikanth, “Livestock and Aquaculture and Management Practices, In:Livestock And Aquaculture Pollution”, in MEVE-003 Agriculture and Allied Sector, IGNOU, 2019, pp. 39-61.

2019

Dr. Geetha Srikanth, “Aquaculture and Pollution, In:Livestock And Aquaculture Pollution”, in MEVE-003 Agriculture and Allied Sector, IGNOU, 2019, pp. 27-38.

2019

Dr. Geetha Srikanth, “Comprehensive Environmental Impact Studies, In:Introduction To Environmental Impact Assessment”, in MEVE-001 Environmental Impact Assessment for Environmental Health Analysis, IGNOU, 2019, pp. 47-62.

2019

Dr. Geetha Srikanth, “Measurement Of EIA, An Introduction To Environmental Impact Assessment”, in MEVE-001 Environmental Impact Assessment for Environmental Health Analysis, IGNOU, 2019, pp. 39-46.

Publication Type: Conference Paper

Year of Publication Title

2019

A. S, padmashree, N., Simmon, A., and Dr. Geetha Srikanth, “Role of technology utilizing water as a resource for sustainable development”, in International Conference for Data Sciences Machine Learning and Applications, CMR institute of technology Hyderabad, Telangana India, 2019.

2019

V. Rengaraj, Saravanana, V., Pariyakaruppan, S., Ashok Kumar Mohan, and Dr. Geetha Srikanth, “Augmenting Technology to Address Rural Sanitation”, in International conference for Data Sciences Machine Learning And Applications, CMR institute of technology Hyderabad Telangana India, 2019.

2019

Sk. B., Dr. Geetha Srikanth, and K.P., S., “Assessment of Watershed Areas of Western and Eastern Ghats using Geospatial Techniques”, in 2019 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, India, 2019, pp. 0127-0130.[Abstract]


Water is more essential for all living organisms in this world. The amount of rainfall in the forest is reducing rapidly while the need has increased. During summer the water shortage rises acutely in the forest areas. The dried up water bodies in and around the forest region drive the animals into the human habituated areas in search of water. The physical layout of area upstream from a specified outlet point is called as watershed or basin. If management of watershed is not done properly then there will be depletion of other natural resources based on this watershed. In this case GIS can be used to analyze the watersheds around the forest and to check the availability of water inside the forest. The result of the analysis of this collected forest areas will be useful to find areas where the water is available in forest. Thus the main objective is to locate artificial ponds in forests.

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2019

R. Paul K Reddy, Srija, S. Sai, Karthi, R., and Dr. Geetha Srikanth, “Evaluation of Water Body Extraction from Satellite Images Using Open-Source Tools”, in Proceedings of ISTA 2018 - Intelligent Systems, Technologies and Applications, Advances in Intelligent Systems and Computing, Singapore, 2019, vol. 910, pp. 129-140.

2018

A. V, R, V., Soman K P, and Dr. Geetha Srikanth, “Deep AirNet: Applying Recurrent Networks for Air Quality Prediction”, in International Conference on Computational Intelligence and Data Science, North Cap University, Guru gram, India, 2018.

2018

A. V, Dr. Geetha Srikanth, and Kp, S., “Outgoing Long wave Radiation Prediction Using Dynamic Mode Decomposition”, in International Conference on Soft Computing Systems (ICSCS-2018), Baselios Mathews II College of Engineering, India, 2018.

2018

A. V and Dr. Geetha Srikanth, “Mapping of Air Pollution and climatic changes using GDAS data in Palakkad Region-Kerala”, in ISITS International Conference on Innovative Technologies for Sustainable Earth, Karunya University, 2018, vol. 3.

2018

S. Aswin, Dr. Geetha Srikanth, and Vinayakumar, R., “Deep Learning Models for the Prediction of Rainfall”, in 2018 International Conference on Communication and Signal Processing (ICCSP), Adhiparasakthi Engineering College,Chennai, India, 2018, pp. 0666 – 0670.[Abstract]


Rainfall is one of the major source of freshwater for all the organism around the world. Rainfall prediction model provides the information regarding various climatological variables on the amount of rainfall. In recent days, Deep Learning enabled the self-learning data labels which allows to create a data-driven model for a time series dataset. It allows to make the anomaly/change detection from the time series data and also predicts the future event's data with respect to the events occurred in the past. This paper deals with obtaining models of the rainfall precipitation by using Deep Learning Architectures (LSTM and ConvNet) and determining the better architecture with RMSE of LSTM as 2.55 and RMSE of ConvNet as 2.44 claiming that for any time series dataset, Deep Learning models will be effective and efficient for the modellers.

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2017

E. V. Shanmugapriya and Dr. Geetha Srikanth, “A framework for the prediction of land surface temperature using artificial neural network and vegetation index”, in 2017 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 2017, pp. 1313 – 1317.[Abstract]


Unexpected and unrestrained extension of urban land cover areas, rural land cover area types have been replaced with artificial materials. Such impact needs to consider the factor of increasing Land surface temperature. It is a necessary aspect to be considered in monitoring various global changes. The most efficient method to find LST is by means of satellite data analysis. In this paper, prediction of LST uses vegetation indices for analyzing vegetation change parameters and soil moisture analysis then the statistical outcome of the study area as the processing inputs exploiting an artificial neural network (ANN). Spectral radiation having the ability to penetrate through clouds, hence the vegetation indices and LST can be evaluated even under critical, cloudy conditions. The ANN model were trained and then tested for respective cases where LST was attainable. This model takes a series of earlier period LST values, identify with the outline of transform within the data and promote prediction or future time values. The performance analyses of the framework were estimated based on typical evaluation methods of RMSE and Regression. The best resultant model was utilized to predict LST where the observing circumstances were available. Conclusions affirm that ANN model serves good in prediction of LST with the real world observations. The proposed study using ANN design is useful in predicting LST in Yercaud, a hilly region in Salem district, of Tamilnadu using the remotely sensed data even under various circumstances of the ecology.

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2017

S. N. Deve and Dr. Geetha Srikanth, “Land use modeling for sustainable crop development using fuzzy approach”, in Proceedings of the 2017 IEEE International Conference on Communication and Signal Processing, ICCSP 2017, 2017, vol. 2018-January, pp. 1473-1476.[Abstract]


To improve the crop yield design model and to relay the gained result in the system of Multi Criteria Decision Making (MCDM) approach for harvest growth in facility area of Tiruchirappalli. In the proposed method replicas are established to maximize the Crop/Yield Production, Net Benefits (NB), Manure Utilization and Employment Generation in the respective area of interest. The optimal solution for the command area using fuzzy approach was formulated by using various GIS and remote sensing techniques. The consequences of the two models are compared. The MCDM technique concentrates on developing crop suitability model. The current technique supports for decision making to yield conclusion in opposing state while preparation for diverse aims concurrently. © 2017 IEEE.

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2017

N. S. Deve, Jasmineniketha, M., Dr. Geetha Srikanth, and Dr. Soman K. P., “Agricultural drought analysis for Thuraiyur taluk of Tiruchirappali District using NDVI and land surface temperature data”, in Proceedings of 2017 11th International Conference on Intelligent Systems and Control (ISCO), 2017, pp. 155-159.[Abstract]


Drastic changes in temperature and rainwater leads to the significant impact on drought which affects agricultural growth. Agricultural drought is a term which explains about reduction in the yield of crops due to abnormalities in rainfall as well as decline in soil moisture that affects agriculture, economy, social aspect, and environment. A trivial variation in the monsoon mainly affects the yield as well as the crops significantly. With the help of remote sensing data agricultural monitoring, management and assessment is done to calculate vegetation and temperature variations. Thuraiyur taluk in Tiruchirappalli District, of Tamilnadu (India) lies in a plain region between 11° 10′ N latitude and 78° 37′ E longitude. It depends mainly on the agriculture therefore the influence of drought affects the yield and the living of humans. The current study deals with the vegetation stress in the Thuraiyur taluk of Tiruchirappalli district with the usage of the Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI). The Landsat data is utilized for the computation of LST and NDVI. The mixture of LST and NDVI, helps to monitor agricultural drought and also as a counsel for farmers. By computing the relationship between LST and NDVI, it is noted that they have a high negative correlation. The correlation between LST and NDVI is -0.763 for the year 2013 and -0.685 for the year 2016. The LST when interrelated with the vegetation index helps to identify the agricultural drought, as demonstrated in the current study. © 2017 IEEE.

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2016

M. Kaviarasan, Dr. Geetha Srikanth, and Dr. Soman K. P., “GIS-based ground water quality monitoring in Thiruvannamalai district, Tamil Nadu, India”, in Proceedings of the International Conference on Soft Computing Systems, ICSCS 2015; Kumaracoil; India, 2016, vol. 397, pp. 685-700.[Abstract]


Ground water is a vital resource for drinking water around the world. The economic and ecological stability of many countries heavily relay upon groundwater availability. With rapid developments in industrial and agricultural sectors, the need for ground water is greater than ever before. Consequently, the quality of ground water is affected by fertilizers, effluents run off from industries, chemical dumping sites, domestic sewage, etc. Hence, it is necessary to constantly monitor ground water quality as it has a serious impact on human health. In this paper, we have analyzed ground water quality of Thiruvannamalai district of Tamil Nadu, India. The ground water samples are taken from 13 locations per area. Water Quality Index (WQI) is estimated for each area to ascertain for the potability of water. The physicochemical parameters like pH, Electrical Conductivity (EC), nitrates, fluorides, and chlorides sample data are compared against World Health Organization (WHO) standards. Geographical information system (GIS), an effi- cient tool for estimating water quality is used both in spatial and temporal domain. The results are useful in efficient monitoring and assessment of ground water and thus, for taking relevant measures to curb unrestrained exploitation. © Springer India 2016.

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2015

Dr. Geetha Srikanth and Kokila, M., “Estimation of air pollution using remote sensing technique in coimbatore-a case study”, in 2015 International Conference on Communications and Signal Processing (ICCSP), Melmaruvathur, India, 2015, pp. 794-798.[Abstract]


In almost all cities in the world, people breathe dirty air. Air pollution concentration has been rapidly increasing in the major urban areas mainly due to the increasing use of vehicles. Urbanization is changing the people's life style, along with it they have serious issues related to health and environment damage. Hysplit4 is simulation software which is used to simulate the trajectory and concentration of the pollutants. GDAS is the common data used for simulating both plot. Path of the pollutants is traced with respect to the given meteorological data (wind speed, direction, temperature), since the pollutants move according to local wind pattern and speed. Meanwhile, concentration plot is simulated to assess the amount of pollutants in specified geographical area. Both the plots have been for the particular study area according to the presence of the pollutants. Generation of these plots will help the environmentalist to pre plan the industrial site, safe chimney height, for planning road ways etc.

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2015

S. Santhosh, Kokila, M., Kavinandhini, M., and Dr. Geetha Srikanth, “Establishment of pre-processing station for denoising NOAA satellite images using Legendre Fenchel transformation method”, in ICIIECS 2015 - 2015 IEEE International Conference on Innovations in Information, Embedded and Communication Systems, Karpagam College of EngineeringCoimbatore; India, 2015.[Abstract]


The main focus of this paper lies in establishing a preprocessing (particularly for denoising) station for National Oceanic and Atmospheric Administration (NOAA) satellite images. Main theme behind this establishment is to make use of new algorithms for the purpose of denoising satellite's images. This paper makes use of total variation method based denoising and Legendre Fenchel transformation (ROF) based denoising for the removal of unwanted pixel information from an image. Further, this paper identifies that Legendre Fenchel ROF model suits better in denoising. The reason behind this identification is because of its computational speed while denoising an image without deteriorating the quality of an image. This paper uses the newly designed turnstile antenna for capturing signals (WXtoImg software is used in converting APT (Automatic Picture Transmission) signal of NOAA to an image) from NOAA satellite. Results are scrutinized and validated through various quality metrics. This station aims at solving the issue of denoising at less process time without degrading the quality of an image by the use of Legendre Fenchel ROF model. © 2015 IEEE.

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2014

C. Aswathy, Dr. Geetha Srikanth, and Haridas, N., “Drought Monitoring and Assessment for Karur District in Tamil Nadu Using Remote Sensing and GIS Techniques”, in 15 th Esri India User Conference 2014, 2014.[Abstract]


Drought is a natural hazard due to adverse climatic changes which affects various sectors like environment, society and economy. It occurs not only because of the scarcity of rainfall but also due to the inefficient water resource management. Studies indicate that over 30% of the entire land surface of earth is affected by drought. As a developing country, majority of Indian population depends directly or indirectly on agriculture. So the abnormal monsoon precipitation, causing loss of agricultural production, can highly influence the human life. In this paper, Karur district in Tamil Nadu which often has a very low annual rainfall is taken as the study area for drought monitoring. The technological evolution in remote sensing over the past few decades has opened a new era in the field of drought monitoring. Thus, use of remote sensing and GIS helps in developing early warnings about drought conditions which will be useful for planning the strategies for relief work. Drought analysis can be performed by calculating different drought indices like Standard Precipitation Index (SPI), Standardized Water Level Index (SWI) and Normalized Differences Vegetation Index (NDVI). Rainfall data from 2000-2009 is used to compute the Standardized Precipitation Index (SPI) in different time scales which is used in meteorological drought monitoring. Standardized Water Level Index (SWI) obtained from ground water level data is used for the hydrological drought analysis. Agricultural drought can be qualified using Normalized Differences Vegetation Index (NDVI) which is calculated from the satellite data.

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2011

Sa Prashanth, Dr. Geetha Srikanth, and Dr. Shanmugha Sundaram G. A., “Demand responsive public transportation using wireless technologies”, in ACWR 2011 - Proceedings of the International Conference on Wireless Technologies for Humanitarian Relief, Amritapuri, 2011, pp. 449-453.[Abstract]


Air pollution has been the bane of society for which we still have not got a satisfying solution. The air pollution due to automobiles constitutes around 60-90% of the total air pollution in the urban area. To curtail this, the mass transportation, bus facilities in particular, in any city has to be fine tuned in such a way that they serve the need of the people. In order to make the whole bus transportation easy and convenient for the public there is a need for optimizing the bus routes based on the destinations of the commuting passengers. In this paper, a demand responsive public transportation scheme is proposed, that also entitles the buses to run without a fixed schedule and adjust the schedules based on the passengers' convenience. On a given map, select places called as the "hot-spots" would serve as the present day bus stop equivalents. These hot-spots will have an appropriate hardware interface for the commuters. Upon suitable activation the passenger is making a request for the bus. This request is sent to a centralized scheduling server which will receive all such requests from various hot-spots, processes them and re-route the nearest bus to the passenger's location. Based on the passenger's destination, a route based on Djiktra's algorithm for least time of transit is generated. The communication between the server and the clients can be achieved though various technologies like GSM, Ethernet or a Wi-Fi enabled network set up. The signal that is sent from the clients to the server will again depend on the chosen network. This will enable the passengers to commute to their destination within a shorter time and in the shortest route possible.

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2009

Dr. Geetha Srikanth, Sowmya V., V., V., and K. P. Soman, “An Approach to Study the Influence of Fish Abundance in Relation to Temperature using GIS- A Case Study on Aliyar River”, in 10th ESRI India User International Conference, New Delhi, 2009.[Abstract]


The Geographic Information System (GIS) is a rapidly growing technological field that incorporates graphical features with the tabular data in order to access real world problems. It has gained importance in the area of fisheries science and management. The foundation of GIS in mapping makes it as an initiative tool for fishermen. In the area of fisheries management, the GIS community has an opportunity to respond positively to immediate fisheries crisis around the world. For the creation of fish abundance in Aliyar reservoir, we have applied the GIS technique using ARCGIS 9.2. A GIS data case comprising of fish abundance related to temperature is created. The result of the study gives us an enormous knowledge to know about the abundance of fish in relation to temperature in Aliyar reservoir. Since India has a considerable livestock and poultry population, all efforts have to be mobilized to reclaim the resources and put them to use effectively. More »»

Publication Type: Journal Article

Year of Publication Title

2018

A. V, R, V., Soman K P, and Dr. Geetha Srikanth, “Deep AirNet: Applying Recurrent Networks for Air Quality Prediction”, Procedia Computer Science, vol. 132, pp. 1394-1403, 2018.

2018

A. V and Dr. Geetha Srikanth, “Mapping of Air Pollution and climatic changes using GDAS data in Palakkad Region-Kerala”, vol. 3, 2018.

2018

S. Aswin, Dr. Geetha Srikanth, and Vinayakumar, R., “Deep Learning Models for the Prediction of Rainfall”, 2018 International Conference on Communication and Signal Processing (ICCSP), pp. 0657-0661, 2018.[Abstract]


Rainfall is one of the major source of freshwater for all the organism around the world. Rainfall prediction model provides the information regarding various climatological variables on the amount of rainfall. In recent days, Deep Learning enabled the self-learning data labels which allows to create a data-driven model for a time series dataset. It allows to make the anomaly/change detection from the time series data and also predicts the future event's data with respect to the events occurred in the past. This paper deals with obtaining models of the rainfall precipitation by using Deep Learning Architectures (LSTM and ConvNet) and determining the better architecture with RMSE of LSTM as 2.55 and RMSE of ConvNet as 2.44 claiming that for any time series dataset, Deep Learning models will be effective and efficient for the modellers.

More »»

2018

V. Abhijith, Dr. Geetha Srikanth, Kp, S., and R, V., “Outgoing Long wave Radiation Prediction Using Dynamic Mode Decomposition”, International Journal of Engineering and Technology(UAE), vol. 7, pp. 986-989, 2018.[Abstract]


Weather prediction is a very tedious process since lot of factors affect it and because of that it is very non-linear in nature. Many research works have shown that the Outgoing Longwave Radiation (OLR) has a very concrete linear relation with many weather parameters includ-ing rainfall and it is one of the key factor in determining the global energy budget. In this work we are predicting the global surface OLR by using past OLR data and loading it onto Dynamic Mode Decomposition (DMD) algorithm. The DMD is a technique which uses data driv-en dimensionality reduction approach for extracting dynamically relevant features which uses time-resolved numerical data for prediction and analysis.

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2018

Dr. Geetha Srikanth, V, A., and Soman K P, “DeepAirNet”, Procedia Computer Science, vol. 132, pp. 1394-1403, 2018.

2017

Dr. Geetha Srikanth, E. Shanmugapriya, V., and Soman, K. P., “Hyperspectral Classification of Crop Field Using Vertex Component Analysis”, Journal of Advanced Research in Dynamical & Control Systems, vol. 13, no. Special Issue, pp. 822 – 827, 2017.[Abstract]


Recent advancements in remote sensing technologies allow us to categorize a wide range of crop varieties from satellite data processing methodologies. More precisely the hyperspectral images gives accurate results in classification techniques because of its high spectral and spatial resolutions. This study employs the spectral signature concepts in the backend to analyze the process The dimension of hyperspectral images are usually high ,hence we implement linear unmixing algorithm with respect to Vertex component Analysis(VCA).The resulting abundance maps represents the spectral information of the data vector. These abundance maps help to analyze the spectral compatibility of each material. The standard spectral signature of each crop is available is USGS database which is taken as a reference for classification results. Importance has given to the spectral features of crops to identify each species accurately without considering the dimensionality issues.

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2017

R. Mamtha, Dr. Geetha Srikanth, and Soman, K. P., “Spatio-Temporal Change Detection in Dam Surroundings-a Case Study of Malampuzha Dam, Palakkad”, Journal of Advanced Research in Dynamical & Control Systems, vol. 13, no. Special Issue, pp. 828 – 833, 2017.[Abstract]


Dam is a barrier that impounds water by creating a reservoir. The water in the reservoir can be used for
human consumption, agriculture and also to produce hydroelectric power. Dams are affected by both nature and
mankind. This provokes the need to observe deforestation activity around the dam for preserving the forest
destruction. The Malampuzha Dam in Palakkad is facing such threats leading to its destruction. Lands at images
were used to learn the dam and surroundings. An alteration recognition analysis was used as a method to study the
disturbances in forest cover from 2004 to 2016. The resultant classified Lands at imagery indicates major changes in
forest wrap. Numerical study shows the affected areas in barren land, crop land and settlements over the time period.
This study applies Support Vector Machine (SVM) and it will give the detail about the spatial dynamics around the
dam so that the disaster mitigation measures can be taken before if there is a threat to environment

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2017

J. M. Niketha, Dr. Geetha Srikanth, and Soman, K. P., “Remote Sensing based Vegetation Indices for Drought Monitoring”, Journal of Advanced Research in Dynamical & Control Systems, vol. 13, no. Special Issue, pp. 834 – 839, 2017.

2017

Dr. Geetha Srikanth and Subathra, A., “Noise Modeling Using 3D City Model and Arc GIS”, Journal of Advanced Research in Dynamical & Control Systems, vol. 13, no. Special Issue, pp. 840 – 846, 2017.

2017

T. V. N. Prabhakar and Dr. Geetha Srikanth, “Two-dimensional empirical wavelet transform based supervised hyperspectral image classification”, ISPRS Journal of Photogrammetry and Remote Sensing, vol. 133, pp. 37-45, 2017.[Abstract]


Hyperspectral image classification is one of the major field of application for hyperspectral imaging systems. Though hyperspectral data gives accurate results than their multispectral counterparts, they are computationally more complex due to their high dimensionality. One of the classical problem while dealing with supervised hyperspectral classification is the class imbalance problem that arises due to the limited availability of samples for training. In order to deal with high dimensionality, many feature mining techniques has been proposed in literature for hyperspectral images. In this paper, we propose a hyperspectral image classification method based on two-dimensional Empirical Wavelet Transform (2D-EWT) feature extraction and compare it with that of Image Empirical Mode Decomposition (IEMD) based extracted features and raw features. Here, the focus is upon the fact that the number of features trained should be less than what is to be tested. Since the computational time for classification is also of prime importance, only some of the fast and best of the classifiers are selected. Sparse-based classifiers are one of the fast and efficient method for supervised classification of hyperspectral images. Subspace Pursuit (SP) and Orthogonal Matching Pursuit (OMP) algorithms are used in our experiments for sparse-based classification. Other classifiers used are Support Vector Machine (SVM) and Hybrid Support Vector Selection and Adaptation (HSVSA). The proposed methodology gives improved performance in terms of classification evaluation measures for hyperspectral image classification task. © 2017 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)

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2017

S. V. Samhitha, Krishnan, S. M., Reddy, P. S. V., and Dr. Geetha Srikanth, “Photogrammetric processing of historical declassified data in north east region of India”, International Journal of Civil Engineering and Technology, vol. 8, pp. 759-767, 2017.[Abstract]


This article deals with the photogrammetric processing of historical data i.e. KH- 9 Hexagon images. KH-9 was a series of photo reconnaissance satellites used for mapping purposes during 1970-1989 by CI (Central Intelligence) over USSR and its neighboring countries. It has been declassified for public use in year 2000. In this article, an attempt is made to restore geometry of photography and photogrammetrically process the data for generating planimetrically correct images. KH-9 Hexagon imagery doesn't have any sensor information and numerous inherent distortions are involved while processing. In order to make use of this historical declassified data, for studying the temporal variations happened in the north east region during 30 to 40 years, photogrammetric processing is must. In this study, sixteen KH-9 Hexagon images covering North East region of India are processed. Space Resection is developed to derive the approximate orientation parameters from corner coordinates of image and some approximate assumptions about the camera from literature. Block of images covering North East region have been adjusted using controls from Bhuvan and SRTM DEM. self calibration has been done by observing more control points and brown additional parameters algorithm. Photogrammetric data has been validated by generating ortho images. ERDAS IMAGINE has been used for adjustment. Thus, it is used for several applications such as Change Detection, Environmental Monitoring in North East region. © IAEME Publication.

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2016

Dr. Geetha Srikanth, Santhosh, S., Sundaram, S., and Soman, K. P., “Theoretical investigation of sunlight based radiation estimation from daylight span in India”, Journal of Chemical and Pharmaceutical Sciences, vol. 9, no. 1, pp. 571-575, 2016.

2016

Dr. Geetha Srikanth, Niranjana, S. R., Pari, S., Joseph, M., and Raj, V. Antony, “Structural, vibrational, optical and dielectric studies on L-Isoleucine D-Norvaline”, Research Journal of Pharmaceutical, Biological and Chemical Sciences, vol. 7, no. 3, pp. 2371-2376, 2016.[Abstract]


Amino acids family crystals exhibit excellent nonlinear optical and electro optical properties. L-Isoleucine D-Norvaline single crystals belongs to the amino acid group and has been grown from aqueous solution by slow evaporation solution growth technique at room temperature. The crystals were obtained after a period of 45 days. The compound crystallizes in the noncentrosymmetric space group C2 of the monoclinic system. Powder X-ray diffraction analysis revealed the crystallinity of the grown crystal. Infra-red and Raman spectroscopy techniques were used to elucidate the vibrational behaviour of chemical bond and its functional groups present in the compound. TGA was carried out to ascertain the thermal stability of the crystals. Optical absorption spectrum was recorded in the wavelength region of 200 nm to 1400 nm. The optical band gap of the grown crystal was found to be 4.78eV. The SHG efficiency of LIDNV crystals was examined by Kurtz powder method.

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2016

Dr. Geetha Srikanth, A, S., S, N. Deve, and KP, S., “Geospatial Application using web GIS”, Journal of Chemical and Pharmaceutical Sciences, vol. 9, no. 4, pp. 2416 - 2419 , 2016.[Abstract]


Rapid technological growth in developments of web based geographical information systems, visualization (tours, flythrough) and navigation with 3D models plays a vital role in the application of geographical information systems. The purpose of this study is to build an interactive system and deploy a platform to visualize, navigate, analyze, and interact the 3D city models stored on the 3D city Database via web supporting which can easily access and enhance the effectiveness of 3D web-based Geographical Information System (GIS) and gives an experience and information for user needs with the ability to do with 3D data. City GML (XML-based standard) data model is used for the representation of 3D urban objects. In this context, the buildings are composed as textured 3D model by using softwares (Arc scene, Google sketch up) and stored in cityGML format which access massive rendering of large number of objects and conservation of geometry semantic properties. Integration of Google Earth and Google Maps API which aims to get 3Dcity models and attribute data of the Area of interest by using XML databases and
to create a web based 3D geospatial application.

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2016

M. Vijay, Dr. Geetha Srikanth, and Kp, S., “Case study of diurnal temperature changes caused by anthropogenic activity using meteorological data in Coimbatore District”, International Journal of Control Theory and Applications, vol. 9, pp. 7743-7748, 2016.[Abstract]


A case study was carried out to measure the Diurnal Temperature Changes in Coimbatore caused by anthropogenic activities which are victims of climatic changes. Temperature information is analyzed which serves as a tool for verification while using remote sensing methods. As a cause of pollution in metropolitan cities, increasing temperature in different time periods are observed. Thermal changes are recorded, also owing to the daily fluctuations in Carbon monoxide emission which affects the atmosphere. A study on the environment of Coimbatore reveals that the temperature is comparatively cooler with respect to the past days and this paper reveals the impact of temperature in the environment. Factors such as variations within the region composition plays a vital role in temperature changes. This paper focus on how surface temperature affects the daily temperature cycle in Coimbatore. This paper concludes that surface temperature rises whereas daily temperature fluctuation causes in decreases temperature.

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2016

T. Zacharia and Dr. Geetha Srikanth, “Pan sharpening using Adaptive Fusion”, Journal of Chemical and Pharmaceutical Sciences, vol. 9, no. 1, pp. 498-501, 2016.[Abstract]


Pansharpening refers to fusion of a multispectral (MS) image with a panchromatic (PAN) image to obtain an image with both high spatial and spectral resolution. Among the many existing pansharpening methods the most widely used is the component substitution method. In this paper an improved model of this existing method is proposed which is based on the matting model and an adaptive fusion technique known as the harmony search algorithm. In this model the MS image which can be decomposed to three components via, the alpha channel, spectral foreground and background is used to reconstruct a high resolution MS image by substituting the PAN image instead of the alpha channel. The fusion is done using an adaptive technique, the harmony search which finds the optimal weight value for effective fusion and it is observed that this method gives a better value for many quantitative indices.

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2016

Dr. Geetha Srikanth and Kokila, M., “Waste Water Sludge Treatment Using Rice Bran”, Integrated Waste Management in India: Status and Future Prospects for Environmental Sustainability, Environmental Science and Engineering, pp. 133–138, 2016.[Abstract]


Activated sludge process is the most commonly used aerobic wastewater treatment system. It uses a culture of microorganisms that utilizes organic matter in sewage for its sustenance, growth and synthesis of new cells. Problems like sludge bulking and foaming are the serious issues in this systems, which is formed because of excessive filamentous growth, high F/M ration or due to poor settling of waste sludge. Some methods are there, for removing the sludge bulking which are quite expensive. The efficient and cheap way of sludge removal is using rice bran, since it has enough nitrogen and phosphorous, filamentous bacteria growth is suppressed and favourable microorganism growth is enhanced. The shortcomings such as low density structure and less sedimentation rate are rectified while using rice bran which is estimated by SSVI OR SVI test. Additionally, laboratory test were conducted which reveals nitrogen and phosphorous do not dissolve completely from the rice bran.

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2016

R. Mamtha, M. Niketha, J., and Dr. Geetha Srikanth, “Analysis of deforestation and land use changes in Kotagiri Taluk of Nilgiris District”, Indian Journal of Science and Technology, vol. 9, no. 44, 2016.[Abstract]


Deforestation is one of the main purposes for global warming and contributor of greenhouse effect. In recent years, Remote Sensing and Geographical Information System have the prospective to deliver precise information regarding terrestrial use and forest surface changes. The current analysis assesses the usefulness of high resolution satellite data and GIS techniques for analyzing the change of terrestrial use and forest surface change of Kotagiri Taluk of Nilgiris district for 2013-2016. The Landsat imageries of 2013 and 2016 were analyzed using software. A total of twelve land use regions were identified. The comprehensive study has revealed that the region under forest has increased from 973.34 km2 and 996.45 km2 and settlement from 44.29 km2 to 50.28 km2. The analysis shows that there was major alteration in the pattern of terrestrial use and deforestation of trees for urbanization. There has been a vast change in the strategy of forest surface and terrestrial usage throughout the region of Kotagiri which eventually results in loss of natural ecosystem.

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2016

S. H. Aazam, Dr. Geetha Srikanth, and Soman, K. P., “Watershed management for Namakkal district using GIS”, International Journal of Control Theory and Applications, vol. 9, pp. 4401-4407, 2016.[Abstract]


The Eastern Ghats of southern Tamil Nadu is composed of prominent delta valley of the river Cauvery. Being a perennial river, Cauvery extends its sub-watershed across the paths of Salem and Namakkal. It is evident to measure and put forward the pavement of this river across the study area. This paper uses the images of LISS 3, SRTEM; constructive and destructive analyses are further carried out with the above images. This basin area of sub-peninsular extends over different morphological area of the delta valley. The study is coupled with the information delivered by the survey of India toposheets. The morphometric and anatomical analysis is carried out by employing ArcGIS 9.1 software platform. Various theoretical and visual aspects of the basin are analyzed and interpreted, especially the remarkable hindrance due to astounding influence of geology, geo-morphology and tectonics of the basin. The results are discussed in this paper. Digital Elevation Model for the study area is prepared using ERDAS IMAGINE 9.1. © International Science Press.

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2016

M. J. Babu, Dr. Geetha Srikanth, and Soman, K. P., “MODIS-Aqua Data Based Detection and Classification of Algal Blooms along the Coast of India Using RLS Classifier”, Procedia Computer Science, vol. 93, pp. 424-430, 2016.[Abstract]


In the field of marine biology, researches reveal that there exists a constant increase in Algal bloom (AB) count, along the coast of India. This work aims at detecting and classifying six most frequently appearing algal blooms in this region (viz.:Trichodesmium erythraeum, Noctiluca scintillans/miliaris, Cocholodinium ploykrikoides, Chattonella marina and Karenia mikimotoi blooms). The uniqueness of ocean's optical properties such as remote sensing reflectance (Rrs) and normalized water leaving radiance (nLw) during bloom period serve as the underlying features on whose grounds classification is performed. These parameters are acquired from Aqua/MODIS sensor measurements and Regularized least squares classifier is used in GURLS library for classification. An overall classification accuracy of 94.37% is obtained using both Rrs and nLw features, which is superior to the previously conducted studies for monitoring ABs using optical properties of water. Given a MODIS image, a map is developed wherein the pixels with ABs are highlighted and the causative species is recognized. A MODIS image is available every two days and hence frequent generation of AB moitoring maps is possible, which is of great significance in the fisheries industry. © 2016 The Authors. Published by Elsevier B.V.

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2016

A. S. Balaji, Dr. Geetha Srikanth, and Soman, K. P., “Change detection of forest vegetation using remote sensing and GIS techniques in Kalakkad Mundanthurai Tiger Reserve - (a case study)”, Indian Journal of Science and Technology, vol. 9, no. 30, 2016.[Abstract]


Background/Objectives: Advancements in the field of remote sensing techniques and sensors used have made monitoring of forest resources an easier task. Forests are ecosystems that provide habitat and fodder for wild animals, timber and help maintain the global temperature balance. They face threats both by nature and mankind. So therein comes the need to monitor vegetation from time to time, for preserving the ecosystem. Methods/Statistical Analysis: The Kalakkad Mundanthurai Tiger Reserve (KMTR) area is posed to such threats leading to change in forest cover and type. Multi-temporal Landsat imageries were used to study the area. A change detection analysis was carried out to determine the disruptions in forest cover from 2005 to 2015. Findings: Overlaying the classified multi-temporal images indicated significant changes in forest cover. Statistical analysis shows the approximate amount of vegetation affected and afforested over the time period. Applications/Improvements: The findings can be included for the vegetation monitoring and conservation activities carried out by NGOs and governmental organizations.

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2016

B. Bhavya, Dr. Geetha Srikanth, and Soman, K. P., “Wind farm potential assessment using GIS”, Intelligent Systems Technologies and Applications, vol. 385, pp. 105-113, 2016.[Abstract]


Wind energy harvest mainly resides on the place where the trapping of wind energy is efficient along with a self-sustained transmission grid. It becomes a compete source of renewable energy and a proper Geographic Information System (GIS) is required for mapping. This paper employs such techniques for the identification of wind potential area along with the pavement of the transmission grid in Avinashi taluk of Tamil Nadu. This helps in the potential identification of the wind farm installation place, there by solving the energy crisis in Avinashi. © Springer International Publishing Switzerland 2016.

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2016

G. Pa Kumar, Dr. Geetha Srikanth, and Shanmugasundaram, G. Ab, “Real time water utility model using GIS: A case study in Coimbatore district”, Intelligent Systems Technologies and Applications, vol. 385, pp. 115-123, 2016.[Abstract]


Wind energy harvest mainly resides on the place where the trapping of wind energy is efficient along with a self-sustained transmission grid. It becomes a compete source of renewable energy and a proper Geographic Information System (GIS) is required for mapping. This paper employs such techniques for the identification of wind potential area along with the pavement of the transmission grid in Avinashi taluk of Tamil Nadu. This helps in the potential identification of the wind farm installation place, there by solving the energy crisis in Avinashi. © Springer International Publishing Switzerland 2016.

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2016

T. V. Nidhin Prabhakar and Dr. Geetha Srikanth, “Empirical wavelet transform for improved hyperspectral image classification”, Advances in Intelligent Systems and Computing, vol. 384, pp. 393-401, 2016.[Abstract]


Capturing images in thousands of contiguous spectral bands has been made simpler with the emergence of technology in the field of hyperspectral remote sensing. Despite of these huge data available for analysis, Hyperspectral images (HSI) face many challenges due to high dimensionality, noise, spectral mixing and computational complexity. Several preprocessing methods can be used to overcome the above mentioned issues. In this paper, an enhancement technique using 2D-Empirical Wavelet Transform (EWT) is used as a preprocessing step for the HSI reconstruction prior to sparsity based classification (Subspace Pursuit and Orthogonal Matching Pursuit). The effectiveness of the proposed method is proved by comparing the classification results obtained with and without applying preprocessing. Experimental analysis shows a significant improvement in the classification accuracies i.e., for 40% of training samples, OMP shows an improvement in overall classification accuracy from 66.12% to 93.20% and SP shows an improvement from 66.36% to 92.74%. © Springer International Publishing Switzerland 2016.

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2016

J. M Babu, Dr. Geetha Srikanth, and Kp, S., “Classification of Remotely Sensed Algal Blooms along the Coast of India using Support Vector Machines and Regularized Least Squares”, Indian Journal of Science and Technology, vol. 9, no. 30, 2016.[Abstract]


Background/Objectives: The recent times have observed an inflation in frequency of occurrence of Algal Blooms (ABs). In this work, seven most commonly occurring species (i.e., Trichodesmium erythraeum, Noctiluca scintillans/miliaris, Cocholodinium ploykrikoides, Chattonella marina, Karenia mikimotoi and Protoperidinium species) that have contributed to major ABs along the coastline of India in the years 2002 to 2015 are classified. Methods/Statistical Analysis: Processing the data procured by MODIS Aqua sensor, classification of seven species of algae is performed based only on the feature of remote sensing reflectance (Rrs). In contrast to the existing algorithms like band-ratio and interpretation of water discoloration, classification of blooms is based on Support vector machine (SVM) and Regularized Least Squares (RLS) algorithms. Findings: Classification is executed using LIBSVM and GURLS library for fast and efficient performance. The classification accuracies achieved using both the classifiers are comparable; the overall accuracy using SVM classifier is 88.37%, whereas that obtained with RLS classifier is 89.98%. Applications/Improvements: These results reveal that the above mentioned algorithms are capable of effectively detecting these ABs which is of immense interest in fisheries and healthcare industries. The algorithms can be further trained with bloom parameters based on in-situ datasets from additional occurrences.

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2016

M. Kokila and Dr. Geetha Srikanth, “Air Pollution Estimation in Coimbatore District Using Local Meteorological Data in Hysplit4”, Journal of Chemical and Pharmaceutical Sciences, vol. 9, pp. 515-518, 2016.[Abstract]


Air contamination is a major issue in recent years, a region experiences pollution from its own zone's air pollution as well as with the contamination from its neighboring areas. These contamination's development is majorly because of wind. So with this thought a data set with local meteorological data is made. The created data set is reenacted with the assistance of hysplit4. The data, for example, wind pace wind course and blending layer stature, is encircled into a configuration which hysplit4 can read. With some design setup, reenactment results are obtained. Which is further checked for right tuft begin and their aggregate scattering territory.

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2016

M. Kavinandhini, Dr. Geetha Srikanth, and Dr. Soman K. P., “Climatic impacts and reliability of large scale wind farms in Tamil Nadu”, Indian Journal of Science and Technology, vol. 9, no. 6, 2016.[Abstract]


Objective: The main objective of this paper describes how the large scale windfarms affect the climate of south west monsoon region. Methods/Analysis: Method used for analysing climatic parameters of before and after installation of wind farms is Gaussian mixture model. ArcGIS and QGIS software is used for image and geo-information analysis. Data from the commercial wind turbine of south west monsoon region like temperature, relative humidity, precipitation, wind speed is used to find the climatic variation. Findings: Large scale wind farms significantly affect the various climatic parameters. These impacts depends on the static stability, increase or decrease in the climatic parameters. Conclusion/ Application: Improvements can be made by taking the ground temperature measured by satellite image and identify the warming effect of night and day time warming effect of large scale wind farm area of southwest monsoon regions.

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2015

Dr. Geetha Srikanth, Abhiram, M., and N. Priya, D., “Fog Harvesting–A Wind Flow Perspective in Western Ghats, Coimbatore, Tamil Nadu”, Indian Journal of Science and Technology, vol. 8, no. 28, 2015.[Abstract]


During the past few decades the world has witnessed a phenomenal rise in the growth of population, which has in turn resulted in an increase in the demand for fresh water. Thus, creating an exigency to identify an alternative sustainable freshwater resource to subdue the rising demand for fresh water. Fog, an often-overlooked aspect of the hydrological process, can be one such resource. Several experimental studies were conducted around the globe to gauge the potential of fog as an alternative freshwater resource in high altitude regions. Studies have indicated, that the sites, which were chosen to assess the fog potential of a region, have mostly been random, which might have undermined the fog harvesting potential of the region. The inaccessibility and the harsh environment of the high altitude terrain have also been significant impediment in the experimentation process. This paper is an endeavor to address these issues. In this paper, a hybrid approach between traditional fog quantifications and mathematical modeling, using physically based impaction model aided by complex terrain analysis has been used to quantify the process of fog collection and identification of potential fog harvesting sites of a region. A case study has been done using this approach to analyze the fog harvesting potential of Western Ghats in Ettimadai region and 10054’47.4”N76053’00.6”E has been identified as an ideal location for fog harvesting and has been observed to produce an average yield of 7.67 ± 0.7Lday−1.

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2015

M. .Kokila, Dr. Geetha Srikanth, and .P.Soman, K., “A Contextual Investigation for Variation in Weather Parameter for Coimbatore District”, Procedia Computer Science, vol. 58, pp. 507-515, 2015.[Abstract]


Weather parameters are critical parameter which is to be considered for understanding atmospheric variation. The aim of this paper is to see how the parameter values fluctuates for three decades. Three decade information is isolated into two and K-means machine learning calculation is utilized for bunching the divided data. Then how the information focuses are conveyed around the centroid of every sectioned data group is confirmed. At long last the group for initial one and half decade is compared with the second one and half decade to know how the information focuses are strayed in dynamic year. This gathering is validated with silhouette value.

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2015

S. Parvathy, Dr. Geetha Srikanth, and Kp, S., “Novel Regression-Gis based Approach for the Analysis of Spread of Dengue in Palakkad”, Indian Journal of Science and Technology, vol. 8, no. 24, 2015.[Abstract]


In this paper we try to analyze what is the relationship between number of dengue cases reported with that of the different environmental factors like temperature, rainfall etc. For doing this, we make use of regression analysis along with GIS. This method also helps in predicting the future course of the disease spread as we will be in a position to identify the dependence on different factors. We got a Coefficient of determination R² value of 0.9218, implying that our method is efficient for accurately identifying the relationship between the different parameters and number of cases reported.

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2015

M. Kokila, Dr. Geetha Srikanth, and Ravindran, G., “Air pollution mapping of an urban city using Hysplit”, Journal of Chemical and Pharmaceutical Sciences, vol. 8, no. 4, pp. 770-774, 2015.[Abstract]


Owing to the severe industrialization and urbanization many cities and its people are suffering from air pollution and its aftermath, analysis of the same is not done for many cities in full scale level. Air pollution modeling tools prevail to analyse the dispersion of air pollution considering various atmospheric parameters. In this work the analysis of quantum of air pollution and the dispersion of air pollution is done for two main monsoon period in Coimbatore (South west monsoon and North East monsoon). During the period of March to May owing to less moisture content wind movement will not be so rapid to ensure proper dispersion. A small comparison is made between two years plot to note the variation between these periods. Results shows the dispersion of pollutant owing to the monsoon variation, field data is not collected for the analysis and only secondary data available is used in this study.

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2015

M. Kaviarasan, Dr. Geetha Srikanth, and K. P. Soman, “Multivariate Statistical Technique for the Assessment of Ground Water Quality in Coonoor Taluk, Nilgiri District, Tamilnadu, India”, Indian Journal of Science and Technology , vol. 8, no. 36, 2015.[Abstract]


Ground water is one of the most important resources which play a key role in sustainable development. Over the last few decade, the industrial development and population growth has increased the water utilization which creates stress on both water and land resources. In such scenario, assessment of water quality is essential for proper management and utilization. This paper presents the usage of statistical method like Principal Component Analysis and Pearson Correlation coefficient analysis for analysing temporal variations of the ground water. From Coonoor Taluk of Nilgiri district, various samples were collected to analyse physico-chemical factors. The quality of the ground water and the compositions are to be determined by Water Quality Index (WQI) calculation method. A comparison of each parameter with that of standard permissible limit as recommended by WHO.

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2015

M. K. Mohan and Dr. Geetha Srikanth, “Pre-processing of hyperspectral data (EO-1 Hyperion): A case study of Kozhikode in Kerala”, International Journal of Applied Engineering Research, vol. 10, no. 20, pp. 19244-19249, 2015.[Abstract]


The paper deals with Hyperspectral satellite data pre-processing and analysis for the application of finding the agricultural extent of a region. The Hyperion sensor of the National Aeronautics and Space Administration (NASA) which is carried by the Earth Observing 1 (EO-1) satellite, acts as the source of Hyperspectral images. These Hyperion images are of high spectral resolution with 242 bands and high spatial resolution of 30 meters. Before analyzing the images for agricultural applications or for any other applications, these images have to be pre-processed. Hyperion images come in different formats like level 0R (L0R), level 1R (L1R), level 1Gs (L1Gs) and level 1Gst (L1 Gst). For the purpose of this work the level 1R data of Kozhikode, Kerala is downloaded from the Earth explorer site provided by USGS. The Level 1R data, which is radiometrically corrected, has to undergo many pre-processing steps including geometric correction, destripping, subsetting of the images according to region of interest, noise and dimensionality reduction and finally atmospheric correction. ENVI 4.7 (the Environment for Visualizing Images) a powerful image processing system is used to perform the pre-processing of the data. ENVI provides an array of tools for processing hyperspectral data such as mapping tool, agricultural stress analysis tool, vegetation index tool, linear spectral unmixing and matched filtering. ENVI enables the provision to select GCPs (Ground Control Points) to georeference the image and the SPEAR (Spectral Processing Exploitation and Analysis Resource) tool in ENVI encompasses tools like Log residuals, Empirical line correction, Internal Average Relative Reflectance and many more for atmospheric correction and Vertical strip removal for destripping. Thus with pre-processing of available Hyperspectral data, the hyperspectral remote sensing which is rapidly advancing with the promise of land cover mapping, agricultural yield and many more applications can have more accuracy and greater predictability. © Research India Publications.

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2015

P. Kavitha and Dr. Geetha Srikanth, “Hyperspectral satellite data (EO1-Hyperion) preprocessing: A case study of paddy field in Palakkad”, International Journal of Applied Engineering Research, vol. 10, no. 20, pp. 19256-19259, 2015.[Abstract]


Image pre-processing should be performed in advance of every analysis and therefore there are numerous image pre-processing methods developed for hyperspectral satellite data. Hyperspectral imaging provides abundant information with which the characteristics of objects in a scene can be studied. The present study is to use the hyperspectral data in the Palakkad district to do the pre-processing methods in ERDAS IMAGINE 9.2. This study describes about the pre-processing methods of hyperspectral images, the first step is to correct the image radiometrically and geometrically, and then use the corrected image for doing the subset, denoising in ERDAS IMAGINE 9.2 and the last step is atmospheric correction, which is one of the most important correction method. The preprocessing steps are done for reducing the adverse effects of absorption and scattering due to the atmospheric agents and those that alters the real radiance value that should appear at the sensor. This paper analyzes the image pre-processing steps for improving the quality of a hyper spectral image for doing the future works. © Research India Publications.

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2015

T. V. Nidhin Prabhakar, Xavier, G., Dr. Geetha Srikanth, and Soman, K. P., “Spatial preprocessing based multinomial logistic regression for hyperspectral image classification”, Procedia Computer Science, 2015.[Abstract]


The paper presents a fast, reliable and efficient method for improving hyperspectral image classification aided by segmentation. The Multinomial Logistic Regression(MLR) algorithm can be extended to a semi-supervised learning of the posterior class distribution using unlabeled samples actively selected from the dataset. Classification results obtained from regression model is improved by performing a maximum a posteriori segmentation as it considers the spatial information of the hyperspectral image. The addition of the spatial processing step prior to the above mentioned classification scheme improves the overall accuracy of the process. The accuracies obtained before and after applying the preprocessing are compared. © 2015 The Authors.

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2015

M. Arya, Dr. Geetha Srikanth, and Soman, K. P., “Effect of wind farms in crop production of Kanyakumari district”, Indian Journal of Science and Technology, vol. 8, no. 28, 2015.[Abstract]


This paper describes how the wind farms effect the crop production of Kanyakumari District. Remote sensing technology along with GIS has been used here for finding the NDVI values. Paddy yield data were also used for finding the effect of wind farms. Along with the NDVI values, we use temperature, humidity and Rainfall data for finding the Crop production rate. Erdas imagine 8.3 along with ArcGis have been used as the software for image and geo-information analysis.

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2013

B. S. R, KP, S., and Dr. Geetha Srikanth, “Performance analysis and comparative study of geometrical approaches for spectral unmixing”, International Journal of Scientific & Engineering Research, vol. 4, no. 7, 2013.

2013

B. S. R, Dr. Geetha Srikanth, V, N. Prabhakar, and Kp, S., “Performance analysis of minimum volume based geometrical approaches for spectral unmixing”, International Journal of Science, Engineering and Technology Research (IJSETR) , vol. 2, no. 7, 2013.[Abstract]


Hyperspectral imaging is an area of interesting researches in the current scenario. The HSC(Hyperspectral cameras) used in this field is having high spectral resolution and low spatial resolution and by this reason, the spectra of pixels in the acquired data will appear as mixtures of spectra of various endmembers present in that area. Here spectral unmixing comes as a major process in the hyperspectral image analysis part. Spectral unmixing is a process by which user gets the number of pure reference materials called (endmembers),their spectral signatures and their corresponding abundance maps from the acquired hyperspectral data.In this paper performance analysis of three minimum volume based geometrical approaches namely MVSA(Minimum volume simplex analysis),MVES(Minimum volume enclosing simplex),and SISAL(simplex identification via split and augmented lagrangian) are done by applying them on the real hyperspectral data set AVIRIS Cuprite,taken over Nevada,U.S and the results are evaluated with reference to U.S.G.S spectral library which is available online.

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2011

Ma Rabeeth, Anitha, Ab, and Dr. Geetha Srikanth, “Purification of an antifungal endochitinase from a potential biocontrol agent Streptomyces griseus”, Pakistan Journal of Biological Sciences, PJBS, vol. 14, pp. 788-797, 2011.[Abstract]


Streptomyces griseus (MTCC 9723) is a chitinolytic bacterium isolated from prawn cultivated pond soil of Peddapuram Village; East Godavari District was studied in detailed. Chitinase (EC 3.2.1.14) was extracted from the culture filtrate of Streptomyces griseus and purified by ammonium sulfate precipitation, DEAE-cellulose ionexchange chromatography, Sephadex G-100 and Sephadex G-200 gel filtration chromatography. The molecular mass of the purified chitinase was estimated to be 34, 32 kDa by SDS gel electrophoresis and confirmed by activity staining with Calcofluor White M2R. Chitinase was optimally active at pH of 6.0 and at 40°C. The enzyme was stable from pH 5-9 and up to 20-50°C. The chitinase exhibited Km and Vmax values of 400 mg and 180 IU mL -1 for colloidal chitin. Among the metals and inhibitors that were tested, the Hg +, Hg 2+ and P-chloromercuribenzoic acid completely inhibited the chitinase activity at 1 mM concentration. The purified chitinase showed high activity on colloidal chitin, chitodiose, and chitooligosaccharide. An in vitro assay proved that the crude chitinase, actively growing cells of S. griseus having antifungal activity against all studied fungal pathogen. This result implies that characteristics of S. griseus producing endochitinase made them suitable for biotechnological purpose such as for degradation of chitin containing waste and it might be a promising biocontrol agent for plant pathogens. © 2011 Asian Network for Scientific Information.

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2001

Dr. Geetha Srikanth, Balasubramanian, S., Hemalatha, K. A., Yasmin, S. H., and Premalatha, V. K., “A two parameter Weibull distribution method for predicting cations in the ground water of Cauvery delta of Tamilnadu.”, Indian journal of environmental health, vol. 43, no. 3, pp. 83-91, 2001.[Abstract]


A two parameter Weibull distribution model was applied to evaluate the quality of ground water collected from 50 wells in four regions (CSB, VSB, RCA, NDA) of Thanjavur district. The data of the cations (Ca, Mg, K, Na) and EC were used to predict the ground water quality. The shape (a) and scale (b) along with mean and percentile were zoned. A hybrid approach of the Weibull distribution model was done to estimate the mean. This hybrid approach may be used to predict and forecast the ground water quality. From the study the cationic parameters in the wells were not uniform which may be attributed to contamination either by surface flow or sea water.

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Publication Type: Conference Proceedings

Year of Publication Title

2010

Dr. Geetha Srikanth, Nithya K., and , “Antibacterial Potential of Aquous Extract of Coleus Ambonicus Against Selected Pathogens”, Proceedings of 2nd National Conference on Current Scenario in Microbial Biotechnology (CSMB-2010). Department of Biotechnology, K. S. Rangasamy College of Technology, Tiruchengode, Tamilnadu, pp. 112-117, 2010.