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.

-

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.

-

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.

-

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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