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EROSION MAP OF INDIA
2014
Soil & Land Resources Assessment division
Land Resources Use & Monitoring group
NATIONAL REMOTE SENSING CENTRE, BALANAGAR, HYDERABAD
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EROSION MAP OF INDIA
National Remote Sensing Centre
Balanagar, Hyderabad
Indian Space Research Organization
2014
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Document Control Sheet
Document Number NRSC-RSAA-LRUMG-SLRAD-Jan.,2014-TR/Erosion
Title EROSION MAP OF INDIA
Type of Document Technical Report
Number of pages 11
Author(s) Soil and Land Resources Assessment Division
Reviewed by Group Head, LRUMG
Approved by DD (RSAA), NRSC
Abstract Assessment of soil erosion status is an important pre-requisite for land resources and conservation planning. Mapping of erosion due to wind and water on 1:50,000 scale for the entire country has been has been carried out using 3-seasons LiSS-III satellite data of 2005-06, SRTM / Carto DEM, Universal Soil Loss Equation, available soil and rainfall as well as land use/cover information. Adequate field checks were carried out for mapping and accuracy assessment. The water erosion (sheet) in the erosion map depicts polygons having soil loss greater than 10 tons/ha/year. The present document briefly discusses soil erosion processes and types along with methodology adopted.
Controlled by Head, Soil & Land Resources Assessment Division
Distribution Unrestricted
Reproduction Rights This report and its contents are the property of National Remote Sensing Centre
EROSION MAP OF INDIA
1. INTRODUCTION Unscientific land utilization incompatible with its carrying capacity leads to land degradation which has both environmental and
economic consequences. The information on land degradation is needed for a variety of purposes like planning reclamation
programs, rational land use planning, for bringing additional areas into cultivation and also to improve productivity levels in degraded
lands. Synoptic coverage in narrow and discrete spectral bands provided by space borne sensors at regular interval enabled
inventorying degraded land and monitoring their temporal behavior at operational level. In India various departments have reported
different area statistics for these lands. For example, according to NCA (1976), about 175 M ha of land constituting 53.3 per cent of
the TGA of 329 M ha is subject to various kinds of degradation. DAC, (1994) reported 107 million hectares of area under various
types of degraded lands.
In this context, the nation wide land degradation mapping has been taken up by the Department of Space along with partner
institutions under National Natural Resources Census (NRC) as one of the seven national resources aim at generating information
on degraded lands at 1:50,000 scale using kharif, rabi and zaid (summer season Resourcesat-1, LISS-III data for the period 2005-
06) and by adopting uniform classification scheme. The project has been successfully completed along with various state, central,
universities and others partner institutes. This classification scheme was finalized after elaborate discussions within the DOS set-up as
well as with various Central / State government departments concerned and academia.
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After completion of the project, land degradation process based maps were brought out for hosting on Bhuvan for the benefit of
various users. The details provided hereunder deals with “erosion ” process.
2. EROSION CLASSIFICATION SCHEME
Erosion by water and wind is the most important land degradation process that occurs on the surface of the earth. Rainfall, soil
physical properties, terrain slope, land cover and management practices play a very significant role in soil erosion. A brief
description of various erosion classes by water and wind is given below :
A. WATER EROSION
The displacement of soil material by water can result in either loss of topsoil or terrain deformation or both. This category includes
processes such as sheet erosion, rill, gully erosion and ravines.
A.1. SHEET EROSION
It is a common problem resulting from loss of topsoil. The soil particles are removed from the whole soil surface on a fairly uniform
basis in the form of thin layers. The severity of the problem is often difficult to visualize with naked eyes in the field.
A.2. RILL EROSION
When sheet erosion is severe and the surface runoff goes in the form of a concentric flow, tiny water channels are formed in the field
called rills. Rills are generally associated with the cultivated lands and are visible in the ploughed soil after first heavy showers.
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A.3. GULLY EROSION
Gullies are formed as a result of localized surface run-off affecting the unconsolidated material resulting in the formation of
perceptible channels causing undulating terrain. They are commonly found in sloping lands, developed as a result of concentrated
run-off over fairly long time. They are mostly associated with stream courses, sloping grounds with good rainfall regions and foothill
regions.
A.4. RAVINES
The word ravine is usually associated with an intricate network of gullies formed generally in deep alluvium and entering a nearby
river, flowing much lower than the surrounding tablelands. Ravines are basically extensive systems of gullies developed along river
courses.
B. WIND EROSION
Wind erosion process includes both erosion as well as deposition areas. Three land degradation types were included under this
process.
B.1. SHEET EROSION / LOSS OF TOP SOIL
It implies uniform displacement of topsoil by wind action as thin layers / sheets. During wind storms, the dry finer soil particles
which could be suspended into air will be transported longer distances, while the heavier particles creeps on the surface and
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generally will be transported to shorter distances. The lifted medium to coarse soil particles may reduce the productivity of adjacent
fertile land when they are deposited in the form of sand castings.
B.2. STABILIZED DUNES
This is a depositional feature of wind erosion. Depending on the rainfall and protection available from grazing, the bare sand dunes
gradually establishes vegetal cover, thus making them to get stabilized.
B.3. PARTIALLY STABILIZED DUNES
In partially stabilized dunes, the erosion / deposition will be still active to some extent. When they establish a good vegetal cover
either in the form of grasses, shrubs and scrubs, they get stabilized and erosion / deposition activity will be minimal. By virtue of
vegetal cover and physiography, they are discernible on satellite imagery.
B.4. UN-STABILIZED DUNES
These are also sand dunes – a depositional feature of wind erosion process. They are generally devoid of any vegetal cover for
protection. The erosion / deposition process is quite active in these areas. The unstabilized sand dunes changes their location and
shape from season to season or year to year and hence they are often called shifting dunes.
3. METHODOLOGY
The various steps in the methodology adopted are - geo-rectification of satellite data, design and development of geo-database with
uniform scheme, delineation of erosion categories through on-screen visual interpretation, ground truth collection, soil chemical
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analysis, finalization of erosion polygon boundaries, quality checking, area estimation and statistics compilation. Brief details of
methodology are as follows :
• Georectified Resourcesat LISS-III data of 2005-06 covering Kharif (August – November), Rabi (January - March), Zaid
(April - May) seasons was used to address spatial and temporal variability in erosion.
• Methodology of the study is on-screen visual interpretation of different erosion classes on satellite data FCC following
standard visual interpretation techniques using the interpretation cues / classification scheme provided in manual.
• Sample points were identified for various erosion classes as per sample scheme and data collection formats provided in
project manual.
• The preliminarily interpreted land degradation map was finalised in light of ground truth data and soil characteristics to
arrive at the final map. Existing legacy spatial data of on forest cover, wastelands, salt affected soils, biodiversity, land
use / land cover etc. were made use of.
• The minimum mapping polygon size of 3 mm x 3 mm on 1:50,000 scale equivalent to 2.25 ha area were retained
• Two tier quality checking (QC) mechanism was adopted in this project viz., Internal QC (IQC) and External QC (EQC).
The IQC team essentially comprised of experts available within the partner institute, while EQC team comprised of experts
dawn from NRSC / SAC / RRSC and other national thematic mapping organizations. IQC team checked 100 percent
mapping process while EQC team checked10 % of the area randomly.
• Entire data was organized as geodatabase for proper organization and retrieval along with appropriate metadata as per
NNRMS standards
• District-wise erosion area statistics were generated.
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The erosion process matrix and visual interpretation cues are provided here under as table - 1 and 2 :
Table-1. Erosion process matrix
Erosion process
Erosion type
Field indicators Physiography Land cover Soil type Climate RS data Remarks
Water erosion Sheet erosion
• Muddy runoff during rainy season
• Soil color is lighter than surrounding soils.
• Concretions / coarse fragments on surface
Plains / valleys / pediments with >1-3% slope class
Crop lands/ fallows/ land with / without scrub/ degraded forests. Grass cover and thick forests reduce erosion rates. Poor vegetal cover enhances erosion rate.
Predominantly in soils with fine texture, low organic matter and weak structure.
Humid and semi-arid climates. Erosion rate is more with high intensity rainfalls.
Conspi-cuous in black soils than red and alluvial soils.
Information need to be deduced from available soil maps. RUSLE can be used to quantify soil loss.
Rills Conspicuous tiny rivulets or finger-shaped channels.
Plains / valleys / pediments with
>1-3% slope class
Predominant in crop lands/ fallows followed by land without scrub/ scrub land / degraded forests. Poor vegetal cover enhances erosion rate.
Predominantly in soils with fine texture, low organic matter and weak structure
Humid and semi-arid climates. Erosion rate is more with high intensity rainfalls.
Conspi-cuous in black soils than red and alluvial soils.
Information need to be deduced from available soil maps. RUSLE can be used to quantify soil loss.
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Gullies Well defined and permanent incised land neither cultivable nor traversable.
• Occurs on >5% slope lands.
• Starts at the lower element of slope and gradually creeps to upper slopes.
Mostly land with / without scrub.
Predominant in loams and associated textures.
Humid and semi-arid climates. Erosion rate is more with high intensity rainfalls.
Conspi-cuously manifested.
-
Ravines Well defined and permanent incised land neither cultivable nor traversable.
Network of deepened gullies.
Associated with major streams / river network.
Mostly land with / without scrub.
Predominant in loams and associated textures.
Humid and semi-arid climates. Erosion rate is more with high intensity rainfalls.
Conspi-cuously manifested.
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Wind erosion Sheet erosion Aeolian plains Barren land / land without scrub associated with
no / very poor vegetal cover
Soils with weak structure like sands and loamy sands.
Deserted regions associated with scanty rain and strong winds.
Discernible through deductive logic.
Refer existing wind erosion / desertification / soil maps.
Partially stabilized dunes
Sand dunes covered with sparse vegetal cover.
Aeolian plains Grass / scrubs. Soils with weak structure like sands and loamy sands.
Deserted regions associated with scanty rain and strong winds.
Discernible on optical remote sensing data.
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Stabilized dunes
Sand dunes covered with moderately dense vegetal cover.
Aeolian plains Grass / scrubs/ trees Soils with weak structure like sands and loamy sands.
Deserted regions associated with scanty rain and strong winds.
Discernible on optical remote sensing data.
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Un-stabilized dunes
Sand dunes devoid of any vegetation.
Aeolian plains Barren Soils with weak structure like sands and loamy sands.
Deserted regions associated with scanty rain and strong winds.
Discernible on optical remote sensing data.
-
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Table-2. Visual interpretation cues for mapping soil erosion using multi-temporal satellite data.
Erosion process
Erosion type Colour / Tone
(On standard FCC)
Texture(on LISS-III data)
Pattern Size Shape Association Remarks
Water erosion Sheet erosion
Slightly brighter than surrounding land of its class
Smooth to medium Contiguous patches
Small to large Irregular Sloping cultivated / lands with poor vegetal cover during rainy season.
Information need to be deduced from available soil information, slope and satellite data in conjunction. RUSLE can be used to quantify soil loss.
Rills Brighter than surrounding land of its class
Medium Discrete to contiguous patches
Small to medium
Irregular Sloping cultivated lands.
Mostly seen on ploughed land after first rains.
Gullies Brighter than surrounding land / gray in color depending on soil colour.
Medium to slightly coarse
Discrete to contiguous patches
Small to medium
Irregular First order streams.
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Ravines Medium gray to dark gray
Slightly coarse for shallow ravines and coarse for deep ravines
Contiguous patches
Large to very large
Irregular Stream / river banks
Image texture and association are to be given attention.
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Wind erosion Sheet erosion/ Loss of top soil
Various shades of yellow and light grey combination.
Smooth to medium Contiguous / mottling (in cultivated areas)
Large to very large
Regular / Irregular
Desertic plain areas with of active sand movement
In deserted areas; with little or no vegetal protection.
Partially stabilized dunes
Light grey to medium grey with light yellowish tones.
Medium Contiguous / discrete patches
Small to medium
Regular / Irregular
Desert sandy dunal area,
Sand dunes in desert areas with slight to moderate vegetal /grass cover
Stabilized dunes
Medium grey with light yellowish tones during dry season. Pink mottles during rainy season.
Medium to coarse Discrete patches Small to medium
Regular / Irregular
Desert sandy dunal area,
Sand dunes in desert areas with good vegetal / grass cover
Un-stabilized dunes
Various shades of yellow and very light grey combination.
Smooth to medium Contiguous / discrete
Medium to large
Irregular Desert sandy dunal area
Sand dunes in desert areas with no vegetal / grass cover
4. DATASET
Resourcesat-1 Data from LISS-III sensor of 3 seasons pertaining to 2005-06 are used in this study.
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5. SUGGESTED USE : The erosion maps should be used at broad level for the following purposes :
• Soil conservation and regional planning
• Watershed management
• Agricultural productivity improvement planning
• Scientific research involving carbon cycle, hydrologic cycle, energy budget studies, weather / climate prediction, etc.
6. LIMITATIONS Database should be used at scales equal or smaller than 1:100,000
7. DISCLAIMER
• Accuracy of different erosion classes are subjected to availability of suitable cloud free satellite data and accuracy of soil &
land cover information
• Data can’t be used for any legal purpose.
• Maps should not be used for commercial purpose.
PROJECT TEAM
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Andhra Pradesh
Andhra Pradesh State Remote Sensing Application Centre, Hyderabad Dr. K. Mruthyunjaya Reddy Mr. A. Nageswara Rao Mr. G. Gowtam Mrs. P. Lavanya National Remote Sensing Centre (NRSC) Mr. M. A. Fyzee Mrs. G. Sujatha Mr. Milind Wadodkar Mr. S. S. Thammappa
Arunachal Pradesh Arunachal Pradesh Space Applications Centre, Itanagar Dr. G.Ch. Chennaiah Mr. S. De Sarkar Mr. Harekrishna Dutta Mr. Chau ken Monglong Dr. Swapna Acharjee Mr. Liagi Tajo
Assam Assam Remote Sensing Applications Centre (Assam) Miss. Bharati Sarania Mr. Ramen Sarma National Institute of Rural Development – NER (Assam) Dr. K. Haloi
Bihar Centre for Development of Advanced Computing (C‐DAC), Pune Dr. Benidhar Deshmukh
Mr. Sandeep K. Srivastava, Mr. Sunil Londhe Ms. Upasana Dutta Mr. Swapnil Awaghade
Chhattisgarh
Regional Remote Sensing Centre ‐ Central Dr. Subrata N.Das Dr. S. S. Rao Dr. A. O. Varghese Dr. G. Sreenivasan Mr. A. Anand Mr. D. S. Prakasa Rao Mr. K. Hareef Baba Saheb
Gujarat Bhaskaracharya Institute for Space Applications & Geo‐informatics, Gandhinagar Dr. Vijay Singh Dr. Mahesh B. Chodvadiya Mr. Apurva Dalwadi
Goa Goa State Remote Sensing Centre Dr.Joseph. S. R.De Souza Mr. Mohan Girap NRSC, Hyderabad Mr. Milind Wadodkar
Haryana Haryana Remote Sensing Application Centre, Hissar Dr. R. S. Hooda
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Dr. Mothi Kumar Mr. Satbir Singh Mr. Anil Kumar Central Soil Salinity Research Centre, Karnal Dr. A.K.Mandal Dr. Gurbachan Singh
Himachal Pradesh Himachal Pradesh Remote Sensing Centre, Shimla Dr. R. K. Sood Dr. Rajendra Thapa Ms. Kalpana Negi Mr. S. S. Deol
Jammu & Kashmir Directorate of Environment, Ecology & Remote Sensing Mr. S. A. R. Shah Dr. Tasneem Keng Dr. Shakeel Ahmed Mr. Owas Ahmed
Jharkhand Jharkhand Space applications Centre, Ranchi Dr. A.T. Jeyaseelan Mr. Najmul Hoda, Mr. Vinod Kumar Honnavar, Mr. Niraj Kumar
Karnataka Karnataka State Remote Sensing Applications Centre, Bengaluru Dr. D. K. Prabhuraj Ms. B. L. Jyothi Ms. R. Chaithra Ms. R. Shilpa Mr. K. Srinath Mr. Rushya Shrungeshwara
Ms. K. Geetha Kumari Ms. S. Sunitha Ms. R. Rekha Mr. K. T. Guruswamy Mr. P.Manjunath University of Agricultural Sciences, Dharwad Dr. G. S. Dasog Dr. P. L. Patil Mr. M. S. Korade
Kerala Soil Survey Dept., Thiruvananthapuram Dr. P.N. Premachandran Mr. Thomas Cherian Mr. P. Ramesh Mr. C. S. Dathan Mr. B. Saharsh Mr. Binesh Anthony Mr. Anil. M.Joseph Mr. P. V. Pradeep
Madhya Pradesh Remote Sensing Applications Centre, Bhopal Dr. R. Sharma, Dr. G. D. Bairagi, Mr. N. K. Sharma Mr. G. S. Tagore NRSC, Hyderabad Dr. K. Sreenivas Mr. S. S. Thammappa Mr. Milind Wadodkar
Maharashtra Maharashtra Remote Sensing Applications Centre , Nagpur
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Dr. Vinod Bhothale Dr. A. K. Sinha Mr. Prashant Rajankar Mr. I. K. Ramteke
Manipur Manipur Remote Sensing Applications Centre (Manipur) Mr. Y. Nilkanta Mr. N. Gagan
Meghalaya North Eastern Space Applications Centre Mr. Ranjit Das Mrs. Pratibha T. Das Dr. K. K. Sarma Ms. H. Suchitra Devi Ms. Jenita Merry Nongkynrih Mr. Diganata Barman Mr. Liagi Tazo Mizoram MIRSAC, Aizawl
Dr. R. K. Lallianthanga Mr. Robert Lalchhanhima Sailo Mr. H. Lalhmachhuana Ms. H. Mingthangpuii
Nagaland Nagaland Science & Technology Council, Kohima Dr. Nesa Hiese Mr. Ditho Katiry
Odisha
Odisha Space Applications Centre, Bhubaneswar Mr. A. K. Mohapatra
Mr. P. Mishra Ms. Binitha Tripathy Mr. S. K. Das Mr. K. S. Pattanaik Mr. Arun K. Mohapatra Mr. P. K. Pagoda Mr. A. Das
Punjab Punjab Remote sensing Applications Centre, Ludhiana Dr. P. K. Sharma Dr. V. K. Verma Dr. Anil Sood Dr. D. C. L oshali Dr. Minakshi Mr. Deepak Mehra Mr. Narinder
Rajasthan RRSC‐West, Jodhpur Dr. J. R. Sharma Dr. A. K. Bera Dr. S. Rama Subramoniam Rajasthan State Remote Sensing Applications Centre, Jodhpur Dr. N.K. Kalra, Dr. Joshi, Dr. N. L. Purohit, Dr. F. K. Joshi, Dr. Rakesh Kachwwaha Central Arid Zone Research Institute, Jodhpur Dr. Amal Kar Dr. P. C. Moharana Dr. Mahesh Kumar
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Birla Institute of Technology, Jaipur Dr. M. P. Punia Mr. Peeyush Gaurav
Sikkim State Council of Science & Technology, Gangtok Dr. M.L. Arawatia Mr. D. G. Shrestha Regional Remote Sensing Centre ‐East, Kolkata Dr. A. Jeyaram Dr. V. M. Chowdary Ms. Swati
Tamil Nadu Tamil Nadu Agricultural University, Coimbatore Dr. S. Natarajan Dr. R. Sivasamy Dr. Kumara Perumal Dr. P. Kannan
Tripura
Tripura Space Application Centre (Tripura) Mr. Subrata Paul Mr. Sujit Das
Uttar Pradesh Remote Sensing Applications Centre ‐ UP, Lucknow Dr. Alok Mathur Mr. Sajan A. Punnoose Dr. Kaushlendra Singh Dr. Shahzad Khan Mr. Sushil Chandra Mr. Varun Kumar Indian Institute of Remote Sensing, Dehradun Dr. S. K. Saha
Dr. K. P. Sharma Dr. M. Kudrat Dr. Suresh Kumar Dr. D. Mitra, Dr. A. Velumurgan
Uttarakhand Uttarakhand Space Applications Centre, Dehradun Dr. M. M. Kimothi Mr. Sunil Chandra Ms. Asha Rawat Ms. Asha Thapliyal Ms. Sushma Gairola
West Bengal Remote Sensing Cell, Dept. of Science & Technology, Govt. of W. B., Kolkata Dr. P. Chakrabarti Ms. Subrata B. Dutta, Ms. Susmita Dasgupta Mr. Bimlesh Samanta Ms. Debashree Maitra
Regional Remote Sensing Centre‐East, Kharagpur Dr. A. Jeyaram Dr .D. Dutta
Delhi & Union Territories NRSC, Hyderabad Dr. K. Sreenivas Mr. S. S. Thammappa Mr. M. A. Fyzee Mr. Milind Wadodkar
PROJECT MANAGEMENT Project Directors
Dr. Y. V. N. Krishna Murthy
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Mr. G. Behera Dr. P.S. Roy Dr. V. Raghavswamy Dr. P. G. Diwakar
Supervision & Technical Guidance Dr. T. Ravisankar
Dr. K. Sreenivas Dr. B. R. M. Rao
Technical Lead Team Mr. M. A. Fyzee Mr. S. S. Thammappa
Mrs. G. Sujatha Mr. Milind Wadodkar
Software development Mr. N. Seshadri Sekhar Mr. N. Srinivas Mr. Lesslie
Geodatabase Organisation & Analysis Mrs. G. Sujatha Mr. Milind Wadodkar
Quality Assurance Team Dr. B. R. M. Rao Dr. L. Venkataratnam Dr. L. M. Pande Dr. Jitendra Prasad Dr. R. L. Mehta Dr. A. K. Barman Dr. T. Ravisankar Dr. K. Sreenivas Mr. M. A. Fyzee Mr. S. S. Thammappa Mrs. G. Sujatha
Mr. Milind Wadodkar Co‐ordination for North‐eastern states
North Eastern Space Applications Centre, Umiam Dr. S. Sudhakar Dr. P. P. Nageswara Rao
Cartographic Support Ms. D. V. Ramani Mr. B. S. S. Prasad
Operations Support Mr. S. Thirunavukkarasu Mr. D. Janardhan Rao Mr. A. V. Raju Mr. P. G. Vijaya Kumar Mr. P. Venugopal Mr. D. N. Rao Mr. K. Sanathanan Mr. K. Anjaneyulu
Secretarial Support Mr. E. Shankaraiah Ms. Malini Raj Kumar Ms. P. Yamuna Mr. M. N. Ramesh Babu Mr. V. B. Sastry Mr. A. Ashok Kumar Mr. Bikya Naik
Enrichment of land Degradation data sets NBSS&LUP/ ICAR
Dr. Dipak Sarkar Dr. C .P. Obi Reddy Dr. Rajeev Srivastava Dr. G. S. Sidhu Dr. A. K. Sahoo
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Dr. K. S. Anil Kumar Dr. Siladitya Bandopadhyay Mr. Nirmal Kumar Mr. Ravindra Naitam NRSC / ISRO Dr. P. S. Roy Mr. G. Behera Dr. T. Ravisankar Dr. K. Sreenivas Smt. G. Sujatha Mr. M. A. Fyzee
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