Bio Geo Publication

STANDARDS FOR BIO-GEO DATABASE

Editors

Nisha Mendiratta

R Siva Kumar

K S Rao

Natural Resources Data Management System (NRDMS)Department of Science and Technology (DST)

Ministry of Science and TechnologyGovernment of India

V E R S I O N 1

Department of Science and Technology, Ministry of Science and Technology,Government of India, 2008

ISBN 978-81-7993-151-6

All rights reserved. No part of this publication may be reproduced in any form or by any means with-out prior permission of Department of Science and Technology.

Suggested format for citation

Mendiratta N, Siva Kumar R, and Rao K S (eds). 2008Stardards for Bio-geo Database, Version 1New Delhi: TERI (The Energy and Resources Institute)

Conceived and published byNatural Resources Data Management System (NRDMS) DivisionDepartment of Science and Technology (DST)Ministry of Science and Technology, Government of IndiaTechnology Bhavan, New Mehrauli RoadNew Delhi - 110 016Tel. 2656 7373 Email [email protected], [email protected], [email protected] 2651 9530 Web http://nrdms.gov.in

Publishing services provided by TERI PressThe Energy and Resources Institute Tel. 2468 2100 or 4150 4900Darbari Seth Block Fax 2468 2144 or 2468 2145IHC Complex India +91 Delhi (0) 11Lodhi Road E-mail [email protected] Delhi 110 003/India Web www.teriin.org

Photographs on cover (clockwise from left to right): landscape of Megadwatershed; hyacinth macaws; and amaranth crop

Printed in India by Batra Art Press, New Delhi

C O N T E N T S

Foreword ......... v

Preface ......... vii

Contr ibutors ......... ix

Bionotes ......... xi

S E C T I O N 1 An introduction to bio-geo data standards ......... 1

Nisha Mendiratta

S E C T I O N 2 Land use and land cover codes ......... 11

T S Kachhwaha, S P S Kushwaha,

R K Sood, R Thapa

S E C T I O N 3 Soil resource codification ......... 27

C S Walia and T S Kachhwaha

S E C T I O N 4 Biological codes ......... 113

K S Rao, J C Rana, R M Shar ma,Archana Singh

Annexure 1 ......... 165

List of insti tutions and subject exper ts

Annexure 2 ......... 171

Examples of integ ration of data for the Moolbar i watershed

F O R E W O R D

The sustainable development of a nation is closely relatedto careful and balanced utilization of naturalresources. The Himalayan ecosystem, though fragile, hasbeen a valuable asset for India in this context. The Department of

Science and Technology, through the Natural Resources Data

Management System (NRDMS), has prepared a Bio-geo Database

and Ecological Modelling for Himalayas.

Research teams drawn from as many as eleven agencies and

institutions have participated in the development of this valuable

database. It is a collective effort catalysed by the Department of

Science and Technology. This effort strives to provide a codification

scheme based on nationally accepted standards. I do hope that

this effort would be further fortified in the course of time.

I congratulate all people involved and concerned.

(T Ramasami)

Secretary, Department of Science and Technology,

Ministry of Science and Technology, Government of India

P R E F A C E

India, which became a signatory to the Global BiodiversityInformation Facility as an associate member in 2001,is taking great str ides in collating, compiling, anddocumenting data on land use, soil, and biological standards.

The data is being made available to the general public. While

most efforts are focused on making the information accessible

through developing meta-data standards, very few have

attempted to develop a database based on the users perspective

and use it in local-level planning. Though efforts had been made

to reach a consensus by involving all stakeholders in the

initiatives that took place three years ago, some of the users

may not agree with these standards. As the evolution of

standards is a continuous process, we await their comments

for their improvement. Obviously, due to the fact that most

databases addressed the issues at macro level and micro level,

the databases are not available.

The present efforts by the NRDMS (Natural Resources Data

Management System) Division of the DST (Department of

Science and Technology) in developing a coordinated

programme on Bio-geo Database and Ecological Modelling for

the Himalayas address the issues of micro-level database

development and the use of such database for local development

planning. The programme specifically addresses the issue of

codification of data elements for such a database, which could

become the starting point for national/international standards.

While some codifications exist at land use and land cover level,

none exist in the domains of soil and biological elements. This

document presents the efforts of the programme in developing the

codes and a first version of the codes for public use.

Any such effort needs the sustained support of programmes and

participants. Through this unique coordinated sub-programme, we have

taken the next step forward to develop the codification standards for

bio-geo databases. We would like to thank all the participating institutes

and the consultative team for their feedback and comments. Also,

special thanks are due to the project investigators of the Bio-geo

Database Programme, who have contributed in giving shape to this

manuscript.

We hope this attempt will ignite the scientific spirit among all

stakeholders to look at the present effort and strengthen it or develop

alternative viable approaches to codification, to enable the country to

stand as a leader in the field.

Nisha MendirattaR Siva Kumar

K S Rao

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Preface

C O N T R I B U T O R S

Ms Nisha MendirattaScientist E/Additional DirectorNatural Resources Data Management System DivisionDepartment of Science and TechnologyNew Delhi

Dr R K SoodDirector and Jt Member SecretaryHimachal State Council of Science and Technology, Simla

Dr T S KachhwahaScientist G and HeadForest Resources and Ecology DivisionUP Remote Sensing Applications CentreDepartment of Space, Lucknow

Dr S P S Kushwaha/ProfessorScientist G and HeadForestry and Ecology DivisionIndian Institute of Remote Sensing, Dehra Dun

Dr K S RaoReaderCentre for Interdisciplinary Studies ofMountain and Hill EnvironmentAcademic Research CentreUniversity of Delhi, Delhi

Dr C S WaliaPr ScientistNational Bureau of Soil Survey and Land Use PlanningNew Delhi

Mr R ThapaScientistHimachal Pradesh Remote Sensing Application Centre, Simla

Dr J C RanaScientistNational Bureau of Plant Genetic ResourcesRegional StationPhagli, Simla

Dr R M SharmaScientist, Zoological Survey of IndiaVijaynagarJabalpur 482 002

Dr Archana SinghResearch AssociateNational Bureau of Plant Genetic ResourcesRegional StationPhagli, Simla

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Contributors

B I O N O T E S

Nisha Mendiratta

Nisha Mendiratta is presently working as Scientist E/AdditionalDirector in the DST (Department of Science and Technology). Shegraduated in physics from Delhi University in 1987 and did herpostgraduation in agricultural physics from the IARI (Indian AgriculturalResearch Institute), New Delhi, in 1989, followed by a postgraduatediploma course in Satellite Remote Sensing and GIS at the IndianInstitute of Remote Sensing, Department of Space, Dehra Dun.

She started her professional career in 1990 as Scientist B at the NRSA(National Remote Sensing Agency), Hyderabad, of the Department ofSpace. She carried out core research in the field of microwave remotesensing applications for soil moisture estimation. She then joined theIIRS (Indian Institute of Remote Sensing), Dehra Dun, as a faculty in1991 and carried out intensive research in crop characterization usingsatellite data. She joined the NCMRWF (National Centre for MediumRange Weather Forecasting) Programme of the DST as Senior ScientificOfficer in 1992 and worked for range weather forecasting and cropweather modelling. In 1998, she joined the NRDMS (Natural ResourcesData Management System) Division of the DST as Scientist and hasbeen working in the specialized domain of natural resourcesmanagement.

She is the recipient of the meritorious PG fellowships at the IARI. Shehas several research papers/articles to her credit, which have been eitherpublished or presented at various national and international fora.

R Siva Kumar

Brigadier R Siva Kumar obtained his PhD from the Indian Institute ofTechnology, Delhi. He served in army headquarters as Director, MilitarySurvey, and has been involved in framing and implementation of policies.At present he is head of the NRDMS and CEO, NSDI (National SpatialData Infrastructure) of the DST, spearheading the NSDI movement.He has travelled abroad widely and has studied various national mappingorganizations and spatial data infrastructure in developed countries.He has served as a member of many expert groups and is currently theMember Secretary of National Spatial Data Committee.

Brigadier Siva Kumar has been the recipient of a number of honoursand awards. He was awarded the Dolezal Prize of the International Societyfor Photogrammetry and Remote Sensing in the Congress at Held, Vienna,in 1996. He was awarded the Tat Scholarships for Study Abroad and theNetherlands Government Fellowship. Papers presented by him have wonprizes from the National Research and Development Corporation.

K S Rao

Dr Kottapalli Sreenivasa Rao is presently Reader (Associate Professor)at the Centre for Interdisciplinary Studies of Mountain and HillEnvironment, University of Delhi. After completing his PhD in 1987 heworked briefly (1987/88) as Mulberry agronomist at the CentralSericulture Research and Training Institute, Berhampur (West Bengal).He joined the G B Pant Institute of Himalayan Environment andDevelopment, an autonomous Institute of the Ministry of Environmentand Forests, Government of India, in 1989 and served the institute invarious capacities till 2003. During his tenure at this institute, Dr Raoled an interdisciplinary team of scientists on various aspects of sustainabledevelopment of fragile mountain ecosystems. Dr Rao has travelledextensively in the Himalayas and collaborated with several internationalscientists on various aspects of mountain development.

Dr Rao is currently involved in academic work related to bio-geo databaseand ecological modelling in the Himalayas and biodiversity assessmentin critical ecosystems in hill and mountain regions. He has so far published16 books and more than 150 research publications in both national andinternational scientific journals. He is a member of various academicscientific societies such as the National Academy of Sciences, Allahabad,and Fellow of the National Institute of Ecology. He was awarded VishishtVaigyanik Puraskar in 2005 by the Ministry of Environment and Forests,Government of India, for his extensive work on the Nanda Devi BiosphereReserve.

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Bionotes

SE C T I O N 1

A N I N T R O D U C T I O NT O B I O - G E O D A T AS T A N D A R D S

Background

The NRDMS (Natural Resources Data Management System), a scienceand technology programme of the Government of India, was launchedby the DST (Department of Science and Technology) to catalyse the evolution

of methodologies and techniques for formulating development strategies in a

scenario of large diversity of data sets, data users and data generating agencies.

This programme aims at developing and demonstrating the use of spatial

decision support tools for integrated planning and management of resources

at the local level and caters to the following aspects.

Develop district-level resource profiles on natural resources and other

allied sectors based on the concepts of GIS (geographic information

system).

Provide software support for data management, modelling, and operation

research.

Demonstrate the use of resource profiles and GIS methodology in micro-

level planning.

Promote R&D (research and development) in spatial data management

technology.

Train scientists and potential users.

Forge linkages with the users at different levels.

Carry out documentation and dissemination of the NRDMS methodology.

AN INTRODUCTION TO BIO-GEO

DATA STANDARDS SEC

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4Standards for bio-geo database

Under the NRDMS, databases are the backbone to pursue and implement

various R&D activities. These databases perform the following functions.

Make data available to scientists Published data may be difficult to

find or access, and collecting it from the literature is very time consuming.

Moreover, not all data is actually published in an article. As much as

possible, a particular type of information should be available in one single

place (book, site, database).

Make data available in computer-readable form Since the analysis

of data involves computers, data in computer-readable form (rather than

printed on paper) is necessary.

The computer became the storage medium of choice as soon as it was

accessible to ordinary scientists. Databases were distributed on tape, and later,

on various kinds of disks. When universities and academic institutes were

connected to the Internet or its precursors (national computer networks), it

is easy to understand why the Internet became the medium of choice. Further,

it is even easier to see why the World Wide Web (WWW, based on the Internet

protocol HTTP) has been the standard method of communication and access

for nearly all databases since the beginning of the 1990s.

Need for updation of available standards

The NRDMS Division has set up database centres in selected districts of the

country for the development of databases and preparation of computer-based

spatial resource profiles useful in formulation of district-level developmental

programmes and schemes. State governments like those of Andhra Pradesh,

Haryana, Karnataka, Uttar Pradesh, and West Bengal have been involved in

setting up database centres in their respective states. Several R&D projects

have also been carried out in areas like watershed management, groundwater

budgeting, biomass utilization, drought assessment, and landslide control to

demonstrate the utility of the NRDMS approach in micro-level planning.

Special emphasis is laid on the training of potential users of this emerging

5An introduction to bio-geo data standards

technology. Accordingly, specialized training modules have been developed

for the training of senior district-level officials and representatives of user

departments.

Multi-institutional stakeholders tend to collect the information and compile them

in their own domain specifications, which makes it difficult to understand for

other users. To ease the interoperability and free data flow across the common

database users, a uniform terminology and organization of data are required. To

achieve this codification of data elements, the National (Natural) Resources

Management System of Department of Space had issued NRIS (National

Resources Information System) standards in February 2000.

International efforts

It is of prime importance to include accurate geographical coordinates and altitude

specifications (geo-references) of observed or collected biological species, as this

allows biological information to be linked with other geophysical information.

Realizing this, several international programmes have attempted to link the

biological data sets to geographical locations. However, very few have actually

tried to use them for any scientific analysis or for developmental planning. The

attempts towards scientific analysis have mainly addressed the issues of such

electronic biological archives providing novel avenues towards testing evolutionary

and ecological theories across the worlds mountain ranges. Such studies use the

separation of global from regional environmental conditions along elevational

transects. It, thus, provides new perspectives for the comprehension of adaptation

in mountain biota. Similarly, information on rock chemistry and mountain

topography offers test conditions for edaphic drivers of biodiversity and species

radiation and in an evolutionary context across a suit of geographical scales.

The GMBA (Global Mountain Biodiversity Assessment), a cross-cutting network

of DIVERSITAS (a UN programme on biodiversity management), is one such

programme, which aims to encourage and synthesize research on high-elevation

organismic diversity, its regional and global patterns, and its causes and functions.


It is considered that existing and emerging databases are promising tools for

achieving such goals. The programme has seen that many research projects

generate data sets that are relevant for the scientific community, governmental

natural resource managers, policy-makers, and the public.

The GBIF (Global Biodiversity Information Facility) has a mission to make the

worlds primary data on biodiversity freely and universally available via the

Internet. In cooperation with the GBIF, the GMBA encourages a global effort to

mine geo-referenced archive databases on mountain organisms, build new

biodiversity databases, and link them with geophysical databases. When building

or analysing database information, it is essential to include geographical

coordinates and altitude specifications (geo-reference) for observed or collected

biological species, as this makes it possible to link biological and geophysical

information, particularly climate data.

The EUROMONT initiative is another of the many scientific projects that collect

and use large geo-referenced mountain biodiversity data sets to answer specific

questions in ecology, biogeography, and conservation biology. The GLORIA

(Global Observation Research Initiative in Alpine Environments) project on

monitoring the effects of global change on alpine plants, and MIREN (Mountain

Invasion Research Network), a network on invasive species in mountains, are

other examples. A thorough testing of biodiversity theories with comprehensive

data at the global scale, as obtained through EUROMONT, GLORIA or MIREN

would constitute a significant step in our understanding of mountain diversity

patterns. Many data sets are associated with short-term projects, and are thus

threatened by destruction at the end of the project. The new GMBA initiative for

a GIS mountain biodiversity database specifically aims to collect such sets in

order to prevent their destruction and initiate a first global assessment of the

primary causes of mountain biodiversity patterns. It is pertinent to note that the

Encyclopedia of Life1 is an umbrella initiative, which now encompasses all the global

efforts to integrate knowledge about the biological wealth on this planet.

1 http://eol.org


Initiatives of the DST

It has been felt that the nationally accepted standards with respect to the flora

and fauna are not available and in persuasion of the same, the research team

working under the NRDMSDSTs coordinated programme on Bio-geo

Database and Ecological Modelling has attempted to prepare the standards

(Version 1). The vertical upscaling of the existing codes from

1: 50 000 to 1: 12 500 for land use and soil, along with the addition of biological

codes for flora and fauna, has been attempted. This exercise has been pilot tested

using actual field data (1: 12 500 scale) collected by the research groups working

for the identified micro-watersheds Megad, Moolbari, and Mandhala

representing higher, middle, and lower altitudinal zones of the Himalayan

transects.

Development of the current initiative

An Expert Group was constituted by the DST to oversee the coordinated

programme of Bio-geo Database. Several versions of this document had been

prepared, discussed, and then revised based on suggestions of the group. The

following salient points emerged during some of the meetings.

During the meeting on 24 March 2003 at IIRS (Indian Institute of Remote

Sensing), Dehra Dun, it was agreed to add new levels to existing codes.

How the biological elements should be sampled was also discussed at this

meeting.

In the meeting held on 4 September 2003 at DST, representatives of the FSI

(Forest Survey of India) suggested that FSI codifications be taken as the starting

point for biological data codification. However, when the review committee

looked at the outputs during the meeting on 29 October 2003, it was felt that

the system was inadequate to address the concerns and it was recommended

to develop a new system after consulting the existing international system in

consultation with the BSI (Botanical Survey of India), ZSI (Zoological Survey


of India) and FSI. This document was circulated to all the national institutions

dealing with biological resources (Annexure 1).

The working research team submitted a draft version of biological standards

for consideration by the Expert Group members during the meeting held

on 16 January 2005, at IIT (Indian Institute of Technology) Roorkee.

During the Expert Group meeting during 1921 April 2005 at IIT Delhi,

based on the feedback from the SoI (Survey of India) and DoS (Department

of Space) officials, this document was in principle approved for further

development.

A draft version of standards for land use, soil, and flora and fauna was

presented during the meeting held during 910 November 2005 at the

JNU (Jawaharlal Nehru University), New Delhi, and the same was sent for

comments to all stakeholders in the country.

The modified draft version of this document was presented during the

NSDI (National Spatial Data Infrastructure) Workshop and also circulated

during the Task Force meeting held during 1819 December 2005 and

31 January 2006 at Hyderabad and New Delhi, respectively.

Technical contents were also circulated to the Department of Space,

National Bureau of Soil Science and Land Use Planning, National

Botanical Research Institute, ZSI, BSI, FSI, Watershed Management

Directorate, and the Department of Biotechnology.

Based on the inputs received, the document was further revised

during the meetings held during 2025 February 2006 at Almora, and

during 1314 November 2006 at JNU, New Delhi, and 1415 June 2007

at Kumaon University, Nainital.


Scope of work

The present effort is to provide a codification scheme using accession codes

based on existing nationally accepted data standards and upscaling them to the

international data standards. These are proposed to be dovetailed within the

NSDI framework. The SDI (spatial data infrastructure) is defined as a collection

of technologies, standards, policies, and human resources needed to acquire,

process, maintain, distribute, and improve utilization of spatial data for the

benefit of the economy and society. In India, like elsewhere, the SDI is being

developed at different levels of the hierarchy to provide the required data/

information for corresponding levels of decision-making. Of all the aspects in

the SDI, database standards are highly talked about and several protocols exist.

However, no efforts are made to define standard codes in terms of critical

information that is required by decision-makers. The present document attempts

to define a set of standard codes in the area of land use, soil, and biological

elements that are part of data elements. Examples of integration of codes for

the Moolbari watershed are given (See Annexure 2).

SE C T I O N 2

LAND USE AND LANDCOVER CODES

Introduction

Despite the high demand for information on environment and natural resources,

many existing maps and digital databases are not specifically developed to meet

the various user requirements. One of the main reasons for this gap, though

generally underestimated, is the type of classification or legend used to describe

basic information such as land cover and land use. Many of the existing

classifications are generally not comparable with one another and are very often

single-project-oriented or take a sectoral approach. Though many classification

systems exist throughout the world, there is no single internationally accepted

land cover or land use classification system.

The implementation of land-use planning and land management requires

cooperation among experts from the disciplines involved and integration of the

respective results in order to identify and evaluate all biophysical, socio-economic

and legal attributes of the land.

Any codification scheme based on accession codes aims to contribute to the

development of a common technical language in land resources planning and

management. This helps in developing terms, so that methods and concepts used

by the different sectors involved are understood by all partners in an identical

way, independent from their backgrounds and professional experiences.

Classification system for land use/land cover

Land use/land cover thematic maps should be prepared adopting the

classification system given in Table 1. For explanations on land use/land cover

category, the following documents may also be referred to.

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Standards for bio-geo database

Manual of Nationwide Land Use/Land Cover Mapping using Satellite Imagery

Part I and II (NRSA [National Remote Sensing Agency] 1989)

Manual of Procedure for Wasteland Mapping (NRSA 1986)

NRIS Node Design and Standard (NNRMS [National Natural Resources

Management], ISRO [Indian Space Research Organization] 2000).

It may be noted that under the category of forest, at level III, forest density such as

(i) dense and (ii) open has to be indicated. In the density class, dense means 40%

or more of the ground is covered by tree canopy, whereas open means more than

10% and less than 40% of the ground is covered with the tree canopy. Up to 10%

of canopy cover is regarded as degraded/underutilized forest. Scrubs are also to be

categorized into open and dense, based on crown density of up to 40% and more

than 40%, respectively. The name of the species in case of monoculture and the

name of the dominant species in case of mixed forest should be given at level 4/

level 5 classification of the forested area. The system of classification for notified

and non-notified (revenue and others) forests would remain the same. However,

the area estimates for non-notified forests are to be shown separately in the report.

Also, the forest encroachments for agricultural or other purposes should be shown

as per the actual land use, and the area under such categories is to be recorded

under area statistics for

the notified forestland.

Forest boundaries

should be taken from

the forest department.

Survey of India maps

may also be consulted

before finalizing forest

boundaries.

Similarly, in respect

of agricultural land,Cultivated and vegetated area in Piedmont of Mandhala watershed

15

Land use and land cover codes

boundaries of the

command area as

obtained from the

respective command

area development

authorities should

be depicted in the

map indicating the

geographical extent of

the command area.

Agricultural crops

include crops during kharif (summer season cropping), rabi (winter season

cropping) and zaid (both irrigated + unirrigated). The area under double crop

includes crops cultivated during kharif as well as rabi seasons. Fallow is the

vacant land that is without crop during kharif, rabi as well as zaid seasons.

Current fallow is the vacant land without crop in the year of study only due to

some temporary constraints, whereas permanent fallow is the agricultural land

where no crop has been grown for a very long period of time.

Data requirements

For preparing the land use/land cover thematic maps, Resourcesat-1 LISS-IV

(multispectral) or IKONOS colour images pertaining to three periods kharif,

rabi, and summer seasons (preferably of the same agricultural year) are to be

used. However, digital data can be used if digital classification is employed.

Besides, other collateral data in the form of maps, charts, census records, reports,

and especially large-scale topographical maps should be used.

Methodology

The land use/land cover thematic maps have to be prepared adopting either

visual or digital interpretation techniques in conjunction with collateral data

such as topographical maps and census records. If digital method is followed,

Terrace cultivation in Megad watershed

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the digital output is to be converted into a vector map of correspondence with

other theme maps. The total number of classes would vary from area to area.

The imagery has to be interpreted and ground checked for corrections. After

field checking, the thematic map can be finalized.

The thematic maps should be checked for quality before the same are finalized.

This is essential to maintain high standards of map accuracy. The quality

assurance checks would be carried out three times.

1 Per-field interpretation stage

2 Field verification before finalizing the contents of map

3 After digitization of final map themes, field verification should be undertaken

in all categories of mapping units occurring in the map sheet.

The final output will have attribute codes as shown in Table 1.

Moolbari watershed: a view of the diminishing forest cover due to agriculture

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Final output

The final output would be thematic maps of land use/land cover and forest

area in digital form. Hard copies of the maps could be taken out as part of the

atlas by assigning different colours and hatching patterns. Yellow, green, and

brown colour should be used for depicting different categories of agriculture,

forest, and wasteland, respectively (See Map 1 in Annexure 2).

01-00-00-00-00 Built-up

01-01-00-00-00 Towns/cities (Urban area)

01-01-01-00-00 Residential

01-01-01-01-00 Colonies

01-01-01-01-01 Single-storey

01-01-01-01-02 Multi-storey

01-01-01-02-00 Non-colonies

01-01-01-02-01 Single-storey

01-01-01-02-02 Multi-storey

01-01-02-00-00 Industrial

01-01-02-01-00 Salt pans

01-01-03-00-00 Commercial

01-01-03-01-00 Bus stands

01-01-03-02-00 Rly yards

01-01-03-03-00 Airport

01-01-03-07-00 Market/mandi*

01-01-04-00-00 Recreational

01-01-04-01-00 Parks/gardens

01-01-04-02-00 Playground

01-01-04-03-00 Stadium

01-01-05-00-00 Public and semi-public amenities

01-01-05-01-00 Educational institutions

LAND USE/L AND C OVER CL ASSIFIC ATION SYS TEM AND

TABLE 1 ATTRIBUTE CODE (LUSE.LUT)

LU-CODE Descr-L1 Descr-L2 Descr-L3 Descr-L4/L5

1:1M 1:25 000 1:50 000 1:25 000/12 500

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1:1M 1:25 000 1:50 000 1:25 000/12 500

01-01-05-02-00 Cantonments

01-01-05-03-00 Govt. institution*

01-01-05-04-00 Health centre*

01-01-05-05-00 Communication

Institution*

01-01-06-00-00 Mixed built-up land

01-01-07-00-00 Open spaces/vacant land

01-01-08-00-00 Others

01-01-08-01-00 Reclaimed

01-01-08-02-00 Slum areas

01-02-00-00-00 Villages (rural area)

01-02-01-00-00 Habitations/hamlets

02-00-00-00-00 Agriculture

02-01-00-00-00 Crop land

02-01-01-00-00 Kharif

02-01-02-00-00 Rabi

02-01-03-00-00 Kharif+rabi (double cropped)

02-01-04-00-00 Zaid crop (summer)

02-01-05-00-00 Rabi + zaid (double cropped)

02-01-06-00-00 Kharif+zaid (double cropped)

02-01-07-00-00 Kharif+rabi+zaid (triple cropped)

02-02-00-00-00 Fallow

02-02-01-00-00 Current fallow

02-02-02-00-00 Permanent fallow

02-03-00-00-00 Plantations

02-03-01-00-00 Tea

02-03-03-00-00 Rubber

02-03-06-00-00 Citrus

02-03-07-00-00 Apple

02-03-08-00-00 Almond

02-03-09-00-00 Apricot

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1:1M 1:25 000 1:50 000 1:25 000/12 500

02-03-10-00-00 Jamun

02-03-11-00-00 Mango

02-03-12-00-00 Papaya

02-03-13-00-00 Pear

02-03-14-00-00 Walnut

02-03-15-00-00 Pomegranate

02-03-16-00-00 Litchi

02-03-17-00-00 Guava

02-03-18-00-00 Banana

02-03-19-00-00 Anjeer

02-03-20-00-00 Ber

02-03-21-00-00 Chiku

02-03-22-00-00 Cherry

02-03-23-00-00 Strawberry

02-03-24-00-00 Peach

02-03-25-00-00 Mixed

03-00-00-00-00 Forest

03-01-00-00-00 Evergreen/semi-evergreen

03-01-01-00-00 Dense/closed

03-01-01-01-00 >70%

03-01-01-01-01 Chir pine

03-01-01-01-02 Silver oak

03-01-01-01-03 Deodar

03-01-01-01-04 Bargad

03-01-01-01-05 Bhimal, beul

03-01-01-01-06 Kail

03-01-01-01-07 Bhojpatra

03-01-01-01-08 Peepal

03-01-01-01-09 Eucalyptus

03-01-01-01-10 Ashok

03-01-01-01-11 Asan

03-01-01-01-12 Jamun


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500

20



1:1M 1:25 000 1:50 000 1:25 000/12 500

03-01-01-01-13 Gurjan

03-01-01-01-14 Dhamni

03-01-01-01-15 Mixed sp.

03-01-01-02-00 40%70%

03-01-01-02-01 Chir pine

03-01-01-02-02 Silver oak

03-01-01-02-03 Deodar

03-01-01-02-04 Bargad

03-01-01-02-05 Bhimal, beul

03-01-01-02-06 Kail

03-01-01-02-07 Bhojpatra

03-01-01-02-08 Peepal


03-01-01-02-10 Ashok

03-01-01-02-11 Asan

03-01-01-02-12 Jamun

03-01-01-02-13 Gurjan

03-01-01-02-14 Dhamni

03-01-01-02-15 Mixed sp.

03-01-02-00-00 Open

03-01-02-01-00 10%40%

03-01-02-01-01 Chir pine

03-01-02-01-02 Silver oak

03-01-02-01-03 Deodar

03-01-02-01-04 Bargad

03-01-02-01-05 Bhimal, beul

03-01-02-01-06 Kail

03-01-02-01-07 Bhojpatra

03-01-02-01-08 Peepal


03-01-02-01-10 Ashok

03-01-02-01-11 Asan

21



1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500

03-01-02-01-12 Jamun

03-01-02-01-13 Gurjan

03-01-02-01-14 Dhamni

03-01-02-01-15 Mixed sp.

03-01-02-02-00 70%

03-02-01-01-01 Sal

03-02-01-01-02 Teak

03-02-01-01-03 Shisham

03-02-01-01-04 Babul, kikar

03-02-01-01-05 Bhillar


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500

22


03-02-01-01-06 Toon

03-02-01-01-07 Karanj

03-02-01-01-08 Poplar

03-02-01-01-10 Kachnar

03-02-01-01-09 Jhingan

03-02-01-01-11 Khair

03-02-01-01-12 Siris

03-02-01-01-13 Mulberry

03-02-01-01-14 Neem

03-02-01-01-15 Semul

03-02-01-01-16 Kadam

03-02-01-01-17 Willow

03-02-01-01-18 Oak

03-02-01-01-19 Bamboo

03-02-01-01-20 Mixed sp.

03-02-01-02-00 40%70%

03-02-01-02-01 Sal

03-02-01-02-02 Teak

03-02-01-02-03 Shisham

03-02-01-02-04 Babul, kikar

03-02-01-02-05 Bhillar

03-02-01-02-06 Toon

03-02-01-02-07 Karanj

03-02-01-02-08 Poplar

03-02-01-02-10 Kachnar

03-02-01-02-09 Jhingan

03-02-01-02-11 Khair

03-02-01-02-12 Siris

03-02-01-02-13 Mulberry

03-02-01-02-14 Neem

03-02-01-02-15 Semul

03-02-01-02-16 Kadam


1:1M 1:25 000 1:50 000 1:25 000/12 500

23


03-02-01-02-17 Willow

03-02-01-02-18 Oak

03-02-01-02-19 Bamboo

03-02-01-02-20 Mixed Sp.

03-02-02-00-00 Open

03-02-02-01-00 10%40%

03-02-02-01-01 Sal

03-02-02-01-02 Teak

03-02-02-01-03 Shisham

03-02-02-01-04 Babul, kikar

03-02-02-01-05 Bhillar

03-02-02-01-06 Toon

03-02-02-01-07 Karanj

03-02-02-01-08 Poplar

03-02-02-01-10 Kachnar

03-02-02-01-09 Jhingan

03-02-02-01-11 Khair

03-02-02-01-12 Siris

03-02-02-01-13 Mulberry

03-02-02-01-14 Neem

03-02-02-01-15 Semul

03-02-02-01-16 Kadam

03-02-02-01-17 Willow

03-02-02-01-18 Oak

03-02-02-01-19 Bamboo

03-02-02-01-20 Mixed sp.

03-02-02-02-00

24



1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500

03-02-02-02-06 Toon

03-02-02-02-07 Karanj

03-02-02-02-08 Poplar

03-02-02-02-10 Kachnar

03-02-02-02-09 Jhingan

03-02-02-02-11 Khair

03-02-02-02-12 Siris

03-02-02-02-13 Mulberry

03-02-02-02-14 Neem

03-02-02-02-15 Semul

03-02-02-02-16 Kadam

03-02-02-02-17 Willow

03-02-02-02-18 Oak

03-02-02-02-19 Bamboo

03-02-02-02-20 Mixed sp.

03-02-03-00-00 Scrub forest

03-02-03-01-00 Dense

03-02-03-02-00 Open

03-02-04-00-00 Forest blank

03-03-00-00-00 Forest plantations

03-05-00-00-00 Shifting cultivation

03-05-01-00-00 Old shifting cultivation

03-05-02-00-00 Abandoned shifting cultivation

03-05-03-00-00 Current shifting cultivation

03-06-00-00-00 Crop land in forest/forest encroachments

04-00-00-00-00 Wastelands

04-01-00-00-00 Salt-affected land

04-02-00-00-00 Gullied/ravinous land

04-02-00-01-00 Sheet

04-02-00-02-00 Rills

04-03-00-00-00 Land with scrub

04-03-00-01-00 Dense

25



1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500


1:1M 1:25 000 1:50 000 1:25 000/12 500

04-03-00-02-00 Open

04-04-00-00-00 Land without scrub

04-05-00-00-00 Sandy land

04-06-00-00-00 Mining/industrial waste

04-06-00-01-00 Mining waste

04-06-00-02-00 Industrial waste

04-07-00-00-00 Barren rocky/stony waste/sheet rock

04-07-00-01-00 Barren rocky

04-07-00-02-00 Stony waste

04-07-00-03-00 Sheet rock

04-08-00-00-00 Cold desert land

05-00-00-00-00 Water bodies

05-01-00-00-00 River

05-01-01-00-00 Water channel area

05-01-02-00-00 Sandy area

05-01-04-00-00 River island

05-01-05-00-00 River bed cultivation

05-01-06-00-00 Flood plain

05-02-00-00-00 Canal/diversion channel

05-02-00-01-00 Major

05-02-00-02-00 Minor

05-03-00-00-00 Lakes

05-04-00-00-00 Reservoirs/dams

05-04-00-01-00 Hydroelectric

05-04-00-02-00 Irrigation

05-05-00-00-00 Tanks/village ponds

05-06-00-00-00 Cooling pond/cooling reservoir

05-07-00-00-00 Abandoned quarries with water

06-00-00-00-00 Wetlands

06-01-00-00-00 Inland wetlands

06-01-01-00-00 Waterlogged

06-01-02-00-00 Marshy/swampy

26



1:1M 1:25 000 1:50 000 1:25 000/12 500

06-01-03-00-00 Ox-bow lakes

07-00-00-00-00 Grassland/grazing land

07-01-00-00-00 Dense

07-02-00-00-00 Degraded

08-00-00-00-00 Snow covered

08-01-00-00-00 Perennial

08-02-00-00-00 Glacial area

08-02-00-01-00 Glacier

08-02-00-02-00 Glaciated lakes

08-02-00-03-00 Moraines

08-02-00-03-01 Terminal

08-02-00-03-02 Lateral

08-02-00-03-03 Medial

LU land use; Descr description; L level; 1:1 M 1:1 million

The level 4 and level 5 details in Table 1 are suggestive, based on the Himalayan

region case studies and could be updated by adding the details available in

other regions for complete code standards for the country.

Field name Field type Key field Remarks

LU-code 10,10,C Y Feature code

Descr-L1 30,30,C N Level I classes

Descr-L2 30,30,C N Level II classes

Descr-L3 30,30,C N Level III classes

Descr-L4 30,30,C N Level IV classes

Descr-L5 30,30,C N Level V classes

LU land use; Descr description

TABLE 2 STRUCTURE OF LUSE.LUT

* Based on field information

Note Hyphen sign (-) has been used in the feature codes in all the look-up tables as separator between the

subclasses. This separator sign is used only to improve readability. This sign is not to be entered in the

database tables.

SE C T I O N 3

S O I L R E S O U R C EC O D I F I C AT I O N

SOIL RESOURCE CODIFICATION

Introduction

Soil is recognized as one of the most valuable life-supporting natural resources;

on its proper use depends the social and economic development of a country.

As an important component of the geosphere and biosphere systems, soils

directly provide food, fuel, fibre and fodder for a variety of basic human and

livestock needs. It is the most valuable resource because it takes several

hundreds of years to develop a centimetre of soil layer.

Soils vary widely in space and time and in their capacity to provide crops,

forestry, and grasses, as no two soils are equally suitable for a land utilization

type. There is evidence that our soils are undergoing degradation at an

unacceptable rate with the risk of jeopardizing the food security of our future

generations. The process of soil degradation is triggered by excessive pressure

on land to meet the demands of a rapidly growing population for food, fibre,

and fuel. It is therefore, important that we use this basic resource as per its

capability to ensure sustained use for food and other needs.

In order to make optimum use of our limited resources, we must have an in-

depth knowledge about different soils, their characteristics, behaviour, kind

and degree of problem, and their extent and distribution on the landscape.

This is achieved through soil survey and mapping. The scale of mapping,

however, depends upon the purpose and the kind of terrain.

Soil surveys have been conducted by several organizations, even non-

governmental organizations, using different base maps of various states to

prepare an inventory of the soil resources, so that we can develop a rational

land-use plan. However, the soil resource data generated by different sources

did not maintain uniform standards, and therefore, could not be correlated,

SE

CT

IO

N

3S

EC

TI

ON

3

SE

CT

IO

N

3S

EC

TI

ON

3

C S Walia and T S Kachhwaha

30


collated, and exchanged. As such, there is need to harmonize data coming

from different sources and represent data in a clear and unambiguous manner

understandable by all. This is achieved by arriving at a set of standards that

are universal and which can be referred to by all data managers and resource

specialists. The NRIS (National Resource Information System) has recognized

the value of standards and embarked upon the development and establishment

of a set of standards (NNRMS 2000). Accordingly, some standards have been

worked out for soil resource database by the NBSS&LUP (National Bureau

of Soil Survey and Land Use Planning), which is a nodal agency in this field.

Soils in India are classified according to the United States Department of

Agriculture Soil Taxonomy (USDA 1975). In this category, there are seven

categories. From the highest to the lowest category, these are Order, Suborder,

Greatgroup, Subgroup, Family, Series, and phases of series. One can derive

more and more information as one proceeds from order to soil series and

their phases. Soil taxonomy is a system for classifying soils and is designed for

improving communication amongst soil scientists working in different places

and amongst other uses of soils. It also serves as a correlation tool for soil

surveys. As such, it cannot be used in isolation.

Thus, the purpose of soil taxonomy is to delineate soil classes at various

levels of generalization,

permitting us to

understand as truly as

existing knowledge

permits, the relationship

amongst various soils and

the factors responsible

for their attributes. The

system is designed for

making and interpreting

soil surveys, and as such,

it is well suited forMandhala watershed: cultivation in coarse-loamy mixedhyperthermic Dystric Eutrudepts in piedmont

31

Soil resource codification

general evaluations of the

agricultural potential of the land

or map unit. The specificity of the

evaluation made is related to the

categoric level at which the soil is

classified. Soil taxonomy plays an

important role in the soil survey

programme. It forms the basis

of soil correlation and for

separating and defining mapping

units in the soil resource mapping programme. Soils are mapped at

subgroup association at 1:1 million scale, associations of soil families at state

level (1:250 000) and association of soil series at district level (1:50 000).

Mono-series with its phases are the mapping unit of large-scale (1:12 500) maps

for micro-watersheds. So, a hierarchical approach is adopted in soil taxonomy,

and as we move from the highest to the lowest category, increasing number of

properties are incorporated. It is, therefore, essential that categoric level must be

matched with cartographic accuracyonly then it is possible to make useful

interpretations of soil data. It is obvious, therefore, that the Greatgroup category

cannot be used for detailed soil survey. Hence, the coding scheme for soil layer

has been started from soil order level to soil series and its phases. The coding

structure (as explained in Appendix 1) of soil database was based upon Keys to

Soil Taxonomy (1994), currently being followed by INARIS (Integrated National

Agricultural Resource Information System) and NRIS. But the codification of

soil database up to Subgroup level has been revised adopting Keys to Soil Taxonomy

(1998) as a base so that each soil can find its current taxonomical identification

for data integration and to maintain effective linkages with other national and

international organizations. Soil codes pertaining to phases of soil series have

also been proposed to store the soil database for larger-scale maps.

NBSS&LUP in 2001 started a mission mode project INARIS Soil

Resource Data under the NATP (National Agricultural Technology Project)

Megad watershed: cultivation in coarse-loamy,mixed, frigid, Typic Cryofluvents

32


of the Indian Council of

Agricultural Research with the

objective to create a national-level

soil resources database

management, which focused on

the following.

Developing a systematic soil

information system and

practise shar ing of

information on soil resources

Acting as data bureau for development agencies, planners, and

administration

Developing data sharing/exchange facilities through a dedicated website

Under the project, a spatial database has been created by digitizing

the soil map of different states at 1:1 million scale, with soil boundaries showing

the association of soil families. The project has been initiated with

the identification and coding of fields. The fields for soil resources and

associated information have been identified and grouped under state information,

state, polygon, soil site, and physical and chemical characteristics. Codification

of spatial elements was done as per NRIS but non-spatial elements were also

coded to develop thematic maps and to develop querries at different themes and

for terrain analysis. Certain data gaps were identified and have to be filled up

through progressive soil survey. The project ended with the creation of a spatial

database, development of querry file, data mining, and user feedback. The DST

(Department of Science and Technology) has taken a major initiative to create a

bio-geo database for some sample watersheds in Himachal Pradesh and

Uttarakhand. The soil database will be generated at 1:12 500 scale using remote

sensing data showing phases of soil series on the map. The soil map is to

be digitized and soil will be codified as per the codes listed in Appendix 1.

Moolbari watershed: terrace cultivation in Fine-loamy, mixed, thermic, Dystric Eutrudepts

33


Non-spatial data will be coded to attach to the soil layer to generate the thematic

maps and derived spatial data by integrating the two databases using GIS

environment. Soil data will also be linked to the other data such as land use/land

cover, climatic, hydrologic, socio-economic, and physiographic data to develop

an integrated watershed development plan. The coding scheme with its description

part at different scales for all the elements, followed by its structure, is given in

tables 1 to 7. An example of soil resource codification, as followed in Moolbari

watershed, district Simla, Himachal Pradesh, is given in Annexure 2 (Map 2).

Soil.dat will contain profile descriptions for each soil class/SOIL-CODE. In this

table, soil properties will be defined for individual soil horizon, which will be based

on soil reports prepared under the Bio-geo Database programme. This table will

be linked to the soil layer attribute table via SOIL-CODE as the key field.

TABLE 1 STRUCTURE OF SOIL . LUTField name Field type Key field Remarks

SOIL-CODE 32, 32,C Y 32-digit primary link CODE (Explained later)

ASS1-CODE 32, 32, C Y Secondary link CODE (f irst association), same

values as SOIL-CODE

ASS2-CODE 32, 32,C Y Ter tiary link CODE (second association), same

values as SOIL-CODE

ORDER 15,15,C N Order description

SB-ORDER 15,15,C N Sub-order description

GR-GROUP 30,30,C N Greatgroup description

SB-GROUP 30,30,C N Sub-group description

FAMILY-TEX 30,30,C N Family level textural description

FAMILY-MIN 30,30,C N Family level mineral description

FAMILY-TEMP 30,30,C N Family level temperature region description

SERIES 30,30,C N Series name

SOIL SERIES PHASE 30,30,C N Series phases name

Note Soil.lut should be created taking care to include all the occurrences along with their associated categories. For example;

if category 01-01-01-01-01-01-01-01 has associations with 02-02-02-02-02-02-02-02 and 03-03-03-03-03-03-03-03,

then the LUT should mandatorily contain three records pertaining to CODEs 01-01-01-01-01-01-01-01, 02-02-02-02-02-

02-02-02 and 03-03-03-03-03-03-03-03

34


Coding scheme for soil layer (SOIL.LUT): Soil code will be AA-BB-CC-

DD-EEFFGG-HH-IIJJKKLLMMNNPPQQ (32 digit). Detailed soil codes,

along with description up to soil series phase level are given in Appendix 1.

TABLE 2 STRUCTURE OF SOIL . DATField name Field type Key field Remarks

SOIL-CODE 32,32,C Y 32-digit link CODE

SOIL-DEPTH 10,10,N,0 N

MIN-DEPTH 6,6,N,2 N

MAX-DEPTH 6,6,N,2 N

SAND-PER 5,5,N,2 N

SILT-PER 5,5,N,2 N

CLAY-PER 5,5,N,2 N

TEXTURE 15,15,C N

pH 5,5,N,2 N

EC 5,5,N,2 N

OC-PER 5,5,N,2 N

AV-P205 5,5,N,2 N

AV-K2O G,G,N,2 N

EX-Ca 5,5,N,2 N

EX-Mg 5,5,N,2 N

EX-Na 5,5,N,2 N

EX-K 5,5,N,2 N

CEC G,G,N,2 N

BASE-SATN-PER G,G,N,2 N

ESP G,G,N,2 N

LCC 5,5,C N Land capability class

LCAP-CODE G,G,C N Translated land capability class core as per

LANDCAP.LUT

LlC 5,5,C N Land irrigability class

LANDIR-CODE 2,2,C N Translated land irrigability class code as per

LANDCAP.LUT

PROD-POTEN 10,10,C N

MAX-INFILTRA 5,5,N N

HS-CODE 2,2,C N CODE for run-off potential as per HYDSOIL.LUT

derived from Max-filtra

SOILIR-CODE 2,2,C N Derived soil irrigability class codes as per

SOIL1RR.LUT using criterion table given later

LOCATION 50,30,C N

35


ATTRIBUTE C ODES FOR L AND C APABILIT Y CL ASSES:

TABLE 3 L A N D C A P. L U TLCAP-CODE Description

Class Sub-class Unit

01-00-00 I

01-01-00 Erosion

01-01-01 Intensity - 1


01-02-00 Wetness



01-03-00 Climate



01-04-00 Soil



02-00-00 II

02-01-00 Erosion



02-02-00 Wetness



02-03-00 Climate



02-04-00 Soil



03-00-00 III

03-01-00 Erosion



03-02-00 Wetness



03-03-00 Climate


36


LCAP-CODE Description



03-04-00 Soil


04-00-00 IV

04-01-00 Erosion



04-02-00 Wetness



04-03-00 Climate



04-04-00 Soil



05-00-00 V

05-01-00 Erosion



05-02-00 Wetness



05-03-00 Climate



05-04-00 Soil



06-00-00 VI

06-01-00 Erosion



06-02-00 Wetness



06-03-00 Climate



37


LCAP-CODE Description


06-04-00 Soil



07 -00-00 VII

07-01-00 Erosion



07 -02-00 Wetness


07 -02-02 Intensity - 2

07 -03-00 Climate

07 -02-00 Wetness


07 -02-02 Intensity - 2

07 -03-00 Climate


07 -03-02 Intensity - 2

07 -04-00 Soil


07 -04-02 Intensity - 2

08-00-00 VIII

08-01-00 Erosion



08-02-00 Wetness



08-03-00 Climate



08-04-00 Soil



98-98-98 Habitation mask *

99-99-99 Water body mask **

* Habitation mask polygons taken from layer settlea

** Water body mask polygons taken from layer drainp

38


STRUCTURE OF THE TABLE L ANDC AP.L UTField name Field type Key field

LCAP-CODE G,G,C Y

CLASS 15,15,C N

SUB-CLASS 15,15,C N

UNIT 15,15,C N

STRUCTURE OF THE TABLE


WSP-CODE 2,2,C Y Feature Code

PRIORIT Y 15,15,C N Code Description

STRUCTURE OF THE TABLEField name Field type Key field Remarks

HS-CODE 2,2,C Y Feature code

RUNPOT 15,15,C N Run-off potential

ATTRIBUTE TABLE FOR HYDROLOGIC AL SOIL UNIT S

TABLE 5 HYDROSOL.L UTHS-CODE Runpot

01 Low

02 Moderately low

03 Moderately high

04 Highest

98 Habitation mask*

99 Water body mask**



TABLE 4 WATERSHED PRIORIT IES FOR SOIL C ONSER VATION WSP.L UTWSP-CODE Priority

01 Low

02 Medium

03 High

04 Very high

98 Habitation mask *

99 Water body mask **



39




LANDIR-CODE 2,2,C Y Feature code

Description 100,25,C N Code description



SOILiR-CODE 2,2,C Y Feature code

Description 100,25,C N Code description

TABLE 7 ATTRIBUTE TABLE FOR SOIL IRRIG ABILIT Y: SOILIRR.L UTSOILiR-CODE Description

01 A None to slight limitations for sustained use under irrigation

02 B Moderate soil limitations for sustained use under irrigation

03 C Severe soil limitations for sustained use under irrigation

04 D Very severe soil limitations for sustained use under irrigation

05 E Not suited for irrigation





TABLE 6 ATTRIBUTE TABLE FOR L AND IRRIGABILIT Y: L ANDIRR.LUTLANDIR-CODE Description

01 Few limitations for sustained use under irrigation

02 Moderate limitations for sustained use under irrigation

03 Severe limitations for sustained use under irrigation

04 Very severe limitations, marginal for sustained use under irrigation

05 Not suitable for sustained use under irrigation pending further investigations

06 Not suited for use under irrigation, also not arable





40


The standardized codes up to group level are given below.

AA : Order (two digits)

BB : Suborder (two digits)

CC : Greatgroup (two digits)

DD : Subgroup (two digits)

EEFFGG : Soil family (six digits)

HH : Soil series (two digits)

I, J, K, L, M, N, P, Q : Phases of soil series (16 digits) surface

texture (I), slope (J), erosion (K), surface

stoniness (L), salinity (N), sodicity (N), and

flooding (P)

References

NNRMS. 2000National (Natural) Resource Information System NRIS node design and standardsBangalore: ISRO (Indian Space Research Organization)

USDA (United States Department of Agriculture). 1975Soil Survey Staff (1975) Soil Taxonomy: a basic system of the classification formaking and interpreting soil surveysWashington DC: USDA

USDA (United States Department of Agriculture). 1994Soil Survey Staff (1994) Keys to Soil Taxonomy (6th edn)Washington DC: USDA Soil Conservation Service

USDA (United States Department of Agriculture). 1998Soil Survey Staff (1998) Keys to Soil Taxonomy (8th edn)Washington DC: USDA Natural Resource Conservation Service

Appendix 1

Coding scheme for soil layer (SOIL.LUT): AA-BB-CC-DD-EEFFGG-HH-

IIJJKKLLMMNNPP (32 digits)

LEVEL 1 SUBGROUP C ODES FOR SOIL S IN SOIL.L UTCode Order (AA) Suborder (BB) Greatgroup (CC) Subgroup (DD)

01-01-01-01 Alfisols Aqualfs Plinthaqualfs Typic Plinthaqualfs

01-01-02-02 Natraqualfs Vertic Natraqualfs

01-01-02-03 Vermic Natraqualfs

01-01-02-04 Albic Glossic Natraqualfs

01-01-02-05 Albic Natraqualfs

01-01-02-06 Glossic Natraqualfs

01-01-02-07 Mollic Natraqualfs

01-01-02-08 Typic Natraqualfs

01-01-03-01 Duraqualfs Typic Duraqualfs

01-01-04-01 Fragiaqualfs Aeric Fragiaqualfs

01-01-04-02 Plinthic Fragiaqualfs

01-01-04-03 Umbric Fragiaqualfs

01-01-04-04 Typic Fragiaqualfs

01-01-05-01 Kandiaqualfs Arenic Kandiaqualfs

01-01-05-02 Grossarenic Kandiaqualfs

01-01-05-03 Plinthic Kandiaqualfs

01-01-05-04 Aeric Umbric Kandiaqualfs

01-01-05-05 Umbric Kandiaqualfs

01-01-05-06 Typic Kandiaqualfs

01-01-06-01 Glossaqualfs Arenic Glossaqualfs

01-01-06-02 Histic Glossaqualfs

01-01-06-03 Grossarenic Glossaqualfs

01-01-06-04 Aeric Glossaqualfs

01-01-06-05 Fragic Glossaqualfs

01-01-06-06 Mollic Glossaqualfs

01-01-06-07 Typic Glossaqualfs

01-01-07-01 Albaqualfs Aeric Vertic Albaqualfs

01-01-07-02 Chromic Vertic Albaqualfs

01-01-07-03 Vertic Albaqualfs

01-01-07-04 Udollic Albaqualfs

42


Code Order (AA) Sub order (BB) Greatgroup (CC) Sub group (DD)

01-01-07-05 Aeric Albaqualfs

01-01-07-06 Aquandic Albaqualfs

01-01-07-07 Mollic Albaqualfs

01-01-07-08 Umbric Albaqualfs

01-01-07-09 Typic Albaqualfs

01-01-08-01 Cryaqualfs Typic Cryaqualfs

01-01-09-01 Vermaqualfs Natric Vermaqualfs

01-01-09-02 Typic Vermaqualfs

01-01-10-01 Epiaqualfs Aeric Chromic Vertic

Epiaqualfs

01-01-10-02 Aeric Vertic Epiaqualfs

01-01-10-03 Chromic Vertic Epiaqualfs

01-01-10-04 Vertic Epiaqualfs

01-01-10-05 Aquandic Epiaqualfs

01-01-10-06 Arenic Epiaqualfs

01-01-10-07 Grossarenic Epiaqualfs

01-01-10-08 Aeric Umbric Epiaqualfs

01-01-10-09 Udollic Epiaqualfs

01-01-10-10 Aeric Epiaqualfs

01-01-10-11 Mollic Epiaqualfs

01-01-10-12 Umbric Epiaqualfs

01-01-10-13 Typic Epiaqualfs

01-01-11-01 Endoaqualfs Aquandic Endoaqualfs

01-01-11-02 Arenic Endoaqnalfs

01-01-11-03 Grossarenic Endoaqualfs

01-01-11-04 Udollic Endoaqualfs

01-01-11-05 Aeric Endoaqualfs

01-01-11-06 Mollic Endoaqualfs

01-01-11-07 Umbric Endoaqualfs

01-01-11-08 Chromic Vertic Endoaqualfs

01-01-11-09 Vertic Endoaqualfs

01-01-11-10 Aeric Fragic Endoaqualfs

01-01-11-11 Fragic Endoaqualfs

01-01-11-12 Typic Endoaqualfs

01-02-01-01 Cryalfs Palecryalfs Andic Palecryalfs

01-02-01-01 Vitrandic Palecryalfs

Code Order (AA) Suborder (BB) Greatgroup (CC) Subgroup (DD)

43


01-02-01-02 Aquic Palecryalfs

01-02-01-03 Oxyaquic Palecryalfs

01-02-01-04 Xeric Palecryalfs

01-02-01-05 Ustic Palecryalfs

01-02-01-06 Mollic Palecryalfs

01-02-01-07 Umbric Palecryalfs

01-02-01-08 Typic Palecryalfs

01-02-02-02 Glossocryalfs Lithic Glossocryalfs

01-02-02-03 Vertic Glossocryalfs

01-02-02-04 Andic Glossocryalfs

01-02-02-05 Vitrandic Glossocryalfs

01-02-02-06 Aquic Glossocryalfs

01-02-02-07 Oxyaquic Glossocryalfs

01-02-02-08 Fragic Glossocryalfs

01-02-02-09 Xerollic Glossocryalfs

01-02-02-10 Umbric Xerric Glossocryalfs

01-02-02-01 Ustollic Glossocryalfs

01-02-02-11 Xeric Glossocryalfs

01-02-02-12 Ustic Glossocryalfs

01-02-02-13 Mollic Glossocryalfs

01-02-02-14 Umbric Glossocryalfs

01-02-02-15 Eutric Glossocryalfs

01-02-02-16 Typic Glossocryalfs

01-02-03-01 Haplocryalfs Lithic Haplocryalfs

01-02-03-02 Vertic Haplocryalfs

01-02-03-03 Andic Haplocryalfs

01-02-03-04 Vitrandic Haplocryalfs

01-02-03-05 Aquic Haplocryalfs

01-02-03-06 Oxyaquic Haplocryalfs

01-02-03-07 Lamellic Haplocryalfs

01-02-03-08 Psammentic Haplocryalfs

01-02-03-09 Inceptic Haplocryalfs

01-02-03-10 Xerollic Haplocryalfs

01-02-03-11 Umbric Xeric Haplocryalfs

01-02-03-12 Ustollic Haplocryalfs

01-02-03-13 Xeric Haplocryalfs


44


01-02-03-14 Ustic Haplocryalfs

01-02-03-15 Mollic Haplocryalfs

01-02-03-16 Umbric Haplocryalfs

01-02-03-17 Eutric Haplocryalfs

01-02-03-18 Typic Haplocryalfs

01-03-01-01 Ustalfs Durustalfs Typic Durustalfs

01-03-02-01 Plinthustalfs Typic Plinthustalfs

01-03-03-01 Natrustalfs Vertic Natrustalfs

01-03-03-02 Leptic Torrertic Natrustalfs

01-03-03-03 Torrertic Natrustalfs

01-03-03-04 Aquic Arenic Natrustalfs

01-03-03-05 Aquertic Natrustalfs

01-03-03-06 Aquic Natrustalfs

01-03-03-07 Aridic Leptic Natrustalfs

01-03-03-08 Arenic Natrustalfs

01-03-03-09 Petrocalcic Natrustalfs

01-03-03-10 Salidic Natrustalfs

01-03-03-11 Mollic Natrustalfs

01-03-03-12 Leptic Natrustalfs

01-03-03-13 Haplargidic Natrustalfs

01-03-03-14 Typic Natrustalfs

01-03-04-01 Kandiustalfs Grossarenic Kandiustalfs

01-03-04-02 Aquic Arenic Kandiustalfs

01-03-04-03 Plinthic Kandiustalfs

01-03-04-04 Aquic Kandiustalfs

01-03-04-05 Arenic Aridic Kandiustalfs

01-03-04-06 Arenic Kandiustalfs

01-03-04-07 Aridic Kandiustalfs

01-03-04-08 Udic Kandiustalfs

01-03-04-09 Rhodic Kandiustalfs

01-03-04-1 0 Typic Kandiustalfs

01-03-05-01 Kanhaplustalfs Lithic Kanhaplustalfs

01-03-05-02 Aquic Kanhaplustalfs

01-03-05-03 Aridic Kanhaplustalfs

01-03-05-04 Udic Kanhaplustalfs

01-03-05-05 Rhodic Kanhaplustalfs


45


01-03-05-06 Typic Kanhaplustalfs

01-03-06-01 Paleustalfs Aquertic Paleustalfs

01-03-06-02 Oxyaquic Vertic aleustalfs

01-03-06-03 Udertic Paleustalfs

01-03-06-04 Vertic Paleustalfs

01-03-06-05 Psammentic Paleustalfs

01-03-06-06 Grossarenic Paleustalfs

01-03-06-07 Aquic Arenic Paleustalfs

01-03-06-08 Plinthic Paleustalfs

01-03-06-09 Aquic Paleustalfs

01-03-06-10 Oxyaquic Paleustalfs

01-03-06-11 Petrocalcic Paleustalfs

01-03-06-12 Arenic Aridic Paleustalfs

01-03-06-13 Arenic Paleustalfs

01-03-06-14 Calcidic Paleustalfs

01-03-06-15 Aridic Paleustalfs

01-03-06-16 Kandic Paleustalfs

01-03-06-17 Rhodic Paleustalfs

01-03-06-18 Ultic Paleustalfs

01-03-06-19 Udic Paleustalfs

01-03-06-20 Typic Paleustalfs

01-03-07 -01 Rhodustalfs Lithic Rhodustalfs

01-03-07 -02 Kanhaplic Rhodustalfs

01-03-07 -03 Udic Rhodustalfs

01-03-07-04 Typic Rhodustalfs

01-03-08-01 Haplustalfs Lithic Haplustalfs

01-03-08-02 Aquertic Haplustalfs

01-03-08-03 Oxyaquic Vertic Haplustalfs

01-03-08-04 Torrertic Haplustalfs

01-03-08-05 Udertic Haplustalfs

01-03-08-06 Vertic Haplustalfs

01-03-08-07 Aquic Arenic Haplustalfs

01-03-08-08 Aquultic Haplustalfs

01-03-08-09 Aquic Haplustalfs

01-03-08-10 Oxyaquic Haplustalfs

01-03-08-11 Vitrandic Haplustalfs


46


01-03-08-12 Lamellic Haplustalfs

01-03-08-13 Psammentic Haplustalfs

01-03-08-14 Arenic Aridic Haplustalfs

01-03-08-15 Arenic Haplustalfs

01-03-08-16 Calcidic Haplustalfs

01-03-08-17 Aridic Haplustalfs

01-03-08-18 Kanhaplic Haplustalfs

01-03-08-19 Inceptic Haplustalfs

01-03-08-20 Calcic Udic Haplustalfs

01-03-08-21 Ultic Haplustalfs

01-03-08-22 Calcic Haplustalfs

01-03-08-23 Udic Haplustalfs

01-03-08-24 Typic Haplustalfs

01-04-01-01 Xeralfs Durixeralfs Natric Durixeralfs

01-04-01-02 Vertic Durixeralfs

01-04-01-03 Aquic Durixeralfs

01-04-01-04 Abruptic Haplic Durixeralfs

01-04-01-05 Abruptic Durixeralfs

01-04-01-06 Haplic Durixeralfs

01-04-01-07 Typic Durixeralfs

01-04-02-01 Natrixeralfs Vertic Natrixeralfs

01-04-02-02 Aquic Natrixeralfs

01-04-02-03 Typic Natrixeralfs

01-04-03-01 Fragixeralfs Andic Fragixeralfs

01-04-03-02 Vitrandic Fragixeralfs

01-04-03-03 Mollic Fragixeralfs

01-04-03-04 Aquic Fragixeralfs

01-04-03-05 Ochreptic Fragixeralfs

01-04-03-06 Typic Fragixeralfs

01-04-04-01 Plinthoxeralfs Typic Plinthoxeralfs

01-04-05-01 Rhodoxeralfs Lithic Rhodoxeralfs

01-04-05-02 Petrocalcic Rhodoxeralfs

01-04-05-03 Calcic Rhodoxeralfs

01-04-05-04 Inceptic Rhodoxeralfs

01-04-05-05 Vertic Rhodoxeralfs

01-04-05-06 Typic Rhodoxeralfs


47


01-04-06-01 Palexeralfs Vertic Palexeralfs

01-04-06-02 Aquandic Palexeralfs

01-04-06-03 Andic Palexeralfs

01-04-06-04 Vitrandic Palexeralfs

01-04-06-05 Aquic Palexeralfs

01-04-06-06 Fragiaquic Palexeralfs

01-04-06-07 Petrocalcic Palexeralfs

01-04-06-08 Lamellic Palexeralfs

01-04-06-09 Arenic Palexeralfs

01-04-06-11 Psammentic Palexeralfs

01-04-06-12 Natric Palexeralfs

01-04-06-13 Fragic Palexeralfs

01-04-06-14 Calcic Palexeralfs

01-04-06-15 Plinthic Palexeralfs

01-04-06-16 Ultic Palexeralfs

01-04-06-17 Haplic Palexeralfs

01-04-06-18 Mollic Palexeralfs

01-04-06-19 Typic Palexeralfs

01-04-07-01 Haploxeralfs Lithic Mollic Haploxeralfs

01-04-07-02 Lithic Ruptic

01-04-07 -03 Lithic Haploxeralfs

01-04-07 -04 Vertic Haploxeralfs

01-04-07-05 Aquandic Haploxeralfs

01-04-07-06 Andic Haploxeralfs

01-04-07-07 Vitrandic Haploxeralfs

01-04-07-08 Aquultic Haploxeralfs

01-04-07-09 Aquic Haploxeralfs

01-04-07-10 Natric Haploxeralfs

01-04-07-11 Psammentic Haploxeralfs

01-04-07-12 Plinthic Haploxeralfs

01-04-07-13 Calcic Haploxeralfs

01-04-07-14 Ultic Haploxeralfs

01-04-07-15 Mollic Haploxeralfs

01-04-07-16 Typic Haploxeralfs

01-05-01-01 Udalfs Natrudalfs Vertic Natrudalfs

01-05-01-02 Glossic Natrudalfs


48


01-05-01-03 Mollic Natrudalfs

01-05-01-04 Typic Natrudalfs

01-05-02-01 Ferrudalfs Aquic Ferrudalfs

01-05-02-02 Typic Ferrudalfs

01-05-03-01 Glossudalfs Fragic Glossudalfs

01-05-03-02 Aquandic Glossudalfs

01-05-03-03 Andic Glossudalfs

01-05-03-04 Vitrandic Glossudalfs

01-05-03-05 Oxyaquic Glossudalfs

01-05-03-06 Arenic Glossudalfs

01-05-03-07 Haplic Glossudalfs

01-05-03-08 Typic Glossudalfs

01-05-04-01 Fraglossudalfs Aquic Fraglossudalfs

01-05-04-02 Oxyaquic Fraglossudalfs

01-05-04-03 Typic Fraglossudalfs

01-05-05-01 Fragiudalfs Umbreptic Fragiudalfs

01-05-05-02 Mollic Fragiudalfs

01-05-05-03 Glossaquic Fragiudalfs

01-05-05-04 Aqueptic Fragiudalfs

01-05-05-05 Albaquic Fragiudalfs

01-05-05-06 Aquic Fragiudalfs

01-05-05-07 Oxyaquic Fragiudalfs

01-05-05-08 Glossic Fragiudalfs

01-05-05-09 Ochreptic Fragiudalfs

01-05-05-10 Typic Fragiudalfs

01-05-06-01 Kandiudalfs Plinthaquic Kandiudalfs

01-05-06 -02 Aquic Kandiudalfs

01-05-06 -03 Oxyaquic Kandiudalfs

01-05-06 -04 Arenic Plinthic Kandiudalfs

01-05-06 -05 Grossarenic Plinthic

Kandiudalfs

01-05-06 -06 Arenic Kandiudalfs

01-05-06 -07 Grossarenic Kandiudalfs

01-05-06 -08 Plinthic Kandiudalfs

01-05-06 -09 Rhodic Kandiudalfs

01-05-06-10 Mollic Kandiudalfs


49


01-05-06-11 Typic Kandiudalfs

01-05-07-01 Kanhapludalfs Lithic Kanhapludalfs

01-05-07-02 Aquic Kanhapludalfs

01-05-07-03 Oxyaquic Kanhapludalfs

01-05-07-04 Rhodic Kanhapludalfs

01-05-07-05 Typic Kanhapludalfs

01-05-08-01 Paleudalfs Vertic Paleudalfs

01-05-08-02 Anthraquic Paleudalfs

01-05-08-03 Plinthquic Paleudalfs

01-05-08-04 Glossaquic Paleudalfs

01-05-08-05 Albaquic Paleudalfs

01-05-08-06 Aquic Paleudalfs

01-05-08-07 Oxyaquic Paleudalfs

01-05-08-08 Arenic Plinthic Paleudalfs

01-05-08-09 Grossarenic Plinthic

Paleudalfs

01-05-08-10 Psammentic Paleudalfs

01-05-08-11 Arenic Paleudalfs

01-05-08-12 Grossarenic Paleudalfs

01-05-08-13 Plinthic Paleudalfs

01-05-08-14 Glossic Paleudalfs

01-05-08-15 Rhodic Paleudalfs

01-05-08-16 Mollic Paleudalfs

01-05-08-17 Typic Paleudalfs

01-05-09-01 Rhodudalfs Typic Rhodudalfs

01-05-10-01 Hapludalfs Lithic Hapludalfs

01-05-10-02 Aquic Fragic Hapludalfs

01-05-10-03 Aquertic Chromic

Hapludalfs

01-05-10-04 Aquertic Hapludalfs

01-05-10-05 Oxyaquic Vertic Hapludalfs

01-05-10-06 Chromic Vertic Hapludalfs

01-05-10-07 Vertic Hapludalfs

01-05-10-08 Andic Hapludalfs

01-05-10-09 Vitrandic Hapludalfs

01-05-10-10 Lamellic Hapludalfs


50


01-05-10-11 Psammentic Hapludalfs

01-05-10-12 Aquic Arenic Hapludalfs

01-05-10-13 Arenic Hapludalfs

01-05-10-14 Anthraquic Hapludalfs

01-05-10-15 Albaquultic Hapludalfs

01-05-10-16 Albaquic Hapludalfs

01-05-10-17 Glossaquic Hapludalfs

01-05-10-18 Aquultic Hapludalfs

01-05-10-19 Aquollic Hapludalfs

01-05-10-20 Aquic Hapludalfs

01-05-10-21 Fragic Aquic Hapludalfs

01-05-10-22 Oxyaquic Hapludalfs

01-05-10-23 Fragic Hapludalfs

01-05-10-24 Glossic Hapludalfs

01-05-10-25 Inceptic Hapludalfs

01-05-10-26 Ultic Hapludalfs

01-05-10-27 Mollic Hapludalfs

01-05-10-28 Typic Hapludalfs

02-01-01-01 Andisols Aquands Cryaquands Lithic Cryaquands

02-01-01-02 Pergelic Cryaquands

02-01-01-03 Histic Cryaquands

02-01-01-04 Thaptic Cryaquands

02-01-01-05 Typic Cryaquands

02-01-02-01 Placaquands Lithic Placaquands

02-01-02-02 Duric Histic Placaquands

02-01-02-03 Duric Placaquands

02-01-02-04 Histic Placaquands

02-01-02-05 Thaptic Placaquands

02-01-02-06 Typic Placaquands

02-01-03-01 Duraquands Histic Duraquands

02-01-03-02 Acraquoxic Duraquands

02-01-03-03 Thaptic Duraquands

02-01-03-04 Typic Duraquands

02-01-04-01 Vitraquands Lithic Vitraquands

02-01-04-02 Duric Vitraquands

02-01-04-03 Histic Vitraquands

02-01-04-04 Thaptic Vitraquands


51


02-01-05-01 Melanaquands Lithic Melanaquands

02-01-05-02 Acraquoxic Melanaquands

02-01-05-03 Hydric Pachic

Melanaquands

02-01-05-04 Hydric Melanaquands

02-01-05-05 Thaptic Melanaquands

02-01-05-06 Typic Melanaquands

02-01-06-01 Epiaquands Petroferric Epiaquands

02-01-06-02 Duric Epiaquands

02-01-06-03 Histic Epiaquands

02-01-06-04 Alic Epiaquands

02-01-06-05 Hydric Epiaquands

02-01-06-06 Thaptic Epiaquands

02-01-06-07 Typic Epiaquands

02-01-07-01 Endoaquands Lithic Endoaquands

02-01-07-02 Petroferric Endoaquands

02-01-07-03 Duric Endoaquands

02-01-07-04 Histic Endoaquands

02-01-07-05 Alic Endoaquands

02-01-07-06 Hydric Endoaquands

02-01-07-07 Thaptic Endoaquands

02-01-07-08 Typic Endoaquands

02-02-01-01 Cryands Duricryands Typic Duricryands

02-02-01-02 Aquic Duricryands

02-02-02-01 Melanocryands Lithic Melanocryands

02-02-02-02 Alic Melanocryands

02-02-02-03 Vertic Melanocryands

02-02-02-04 Typic Melanocryands

02-02-03-01 Fluvicryands Lithic Fluvicryands

02-02-03-02 Vitric Fluvicryands

02-02-03-03 Typic Fluvicryands

02-02-04-01 Hydrocryands Lithic Hydrocryands

02-02-04-02 Placic Hydrocryands

02-02-04-03 Aquic Hydrocryands

02-02-04-04 Thaptic Hydrocryands

02-02-04-05 Typic Hydrocryands

02-02-05-01 Vitricryands Lithic Vitricryands


52


02-02-05-02 Aquic Vitricryands

02-02-05-03 Taptic Vitricryands

02-02-05-05 Humic Xeric Vitricryands

02-02-05-06 Xeric Vitricryands

02-02-05-07 Ultic Vitricryands

02-02-05-08 Alfic Vitricryands

02-02-05-09 Humic Vitricryands

02-02-05-10 Typic Vitricryands

02-02-06-01 Haplocryands Lithic Haplocryands

02-02-06-02 Alic Haplocryands

02-02-06-03 Aquic Haplocryands

02-02-06-04 Acrudoxic Haplocryands

02-02-06-05 Vitric Haplocryands

02-02-06-06 Thaptic Haplocryands

02-02-06-07 Xeric Haplocryands

02-02-06-08 Typic Haplocryands

02-03-01-01 Torrands Vitritorrands Lithic Vitritorrands

02-03-01-02 Petrocalcic Vitritorrands

02-03-01-03 Duric Vitritorrands

02-03-01-04 Aquic Vitritorrands

02-03-01-05 Calcic Vitritorrands

02-03-01-06 Typic Vitritorrands

02-04-01-01 Xerands Vitrixerands Lithic Vitrixerands

02-04-01-02 Aquic Vitrixerands

02-04-01-03 Thaptic Vitrixerands

02-04-01-04 Alfic Humic Vitrixerands

02-04-01-05 Alfic Vitrixerands

02-04-01-06 Ultic Vitrixerands

02-04-01-07 Humic Vitrixerands

02-04-01-08 Typic Vitrixerands

02-04-02-01 Melanoxerands Pachic Melanoxerands

02-04-02-02 Typic Melanoxerands

02-04-03-01 Haploxerands Lithic Haploxerands

02-04-03-02 Aquic Haploxerands

02-04-03-03 Thaptic Haploxerands

02-04-03-04 Calcic Haploxerands

02-04-03-05 Ultic Haploxerands


53


02-04-03-06 Alfic Humic Haploxerands

02-04-03-07 Alfic Haploxerands

02-04-03-08 Humic Haploxerands

02-04-03-09 Typic Haploxerands

02-05-01-01 Vitrands Ustivitrands Lithic Ustivitrands

02-05-01-02 Aquic Ustivitrands

02-05-01-03 Thaptic Ustivitrands

02-05-01-04 Calcic Ustivitrands

02-05-01-05 Humic Ustivitrands

02-05-01-06 Typic Ustivitrands

02-05-02-01 Udivitrands Lithic Udivitrands

02-05-02-02 Aquic Udivitrands

02-05-02-03 Thaptic Udivitrands

02-05-02-04 Ultic Udivitrands

02-05-02-05 Alfic Udivitrands

02-05-02-06 Humic Udivitrands

02-05-02-07 Typic Udivitrands

02-06-01-01 Ustands Durustands Aquic Durustands

02-06-01-02 Thaptic Durustands

02-06-01-03 Humic Durustands

02-06-01-04 Typic Durustands

02-06-02-01 Haplustands Lithic Haplustands

02-06-02-02 Aquic Haplustands

02-06-02-03 Dystric Vitric Haplustands

02-06-02-04 Vitric Haplustands

02-06-02-05 Pachic Haplustands

02-06-02-06 Thaptic Haplustands

02-06-02-07 Calcic Haplustands

02-06-02-08 Dystric Haplustands

02-06-02-09 Oxic Haplustands

02-06-02-10 Ultic Haplustands

02-06-02-11 Alfic Haplustands

02-06-02-12 Humic Haplustands

02-06-02-13 Typic Haplustands

02-07-01-01 Udands Placudands Lithic Placudands

02-07 -01-02 Aquic Placudands


54


02-07 -01-03 Acrudoxic Hydric Placudands

02-07 -01-04 Acrudoxic Placudands

02-07 -01-05 Eutric Vitric Placudands

02-07 -01-06 Vitric Placudands

02-07 -01-07 Hydric Pachic Placudands

02-07 -01-08 Pachic Placudands

02-07 -01-09 Hydric Placudands

02-07-01-10 Thaptic Placudands

02-07-01-11 Eutric Placudands

02-07-01-12 Typic Placudands

02-07-02-01 Durudands Aquic Durudands

02-07-02-02 Acrudoxic Durudands

02-07-02-03 Hydric Pachic Durudands

02-07-02-04 Thaptic Durudands

02-07-02-05 Typic Durudands

02-07-03-01 Melanudands Lithic Melanudands

02-07-03-02 Anthraquic Melanudands

02-07-03-03 Alic Aquic Melanudands

02-07-03-04 Alic Pachic Melanudands

02-07-03-05 Alic Thaptic Melanudands

02-07-03-06 Alic Melanudands

02-07-03-07 Aquic Melanudands

02-07-03-08 Acrudoxic Vitric Melanudands

02-07-03-09 Acrudoxic Hydric elanudands

02-07-03-10 Acrudoxic Melanudands

02-07-03-11 Pachic Vitric Melanudands

02-07-03-12 Eutric Vitric Melanudands

02-07-03-13 Vitric Melanudands

02-07-03-14 Hydric Pachic Melanudands

02-07-03-15 Pachic Melanudands

02-07-03-16 Eutric Hydric Melanudands

02-07-03-17 Hydric Melanudands

02-07-03-18 Thaptic Melanudands

02-07-03-19 Ultic Melanudands

02-07-03-20 Typic Melanudands

02-07-04-01 Fulvudands Hydric Lithic Fulvudands

02-07-04-02 Lithic Fulvudands


55


02-07-04-03 Alic Fulvudands

02-07-04-04 Aquic Fulvudands

02-07-04-05 Acrudoxic Hydric Fulvudands

02-07-04-06 Acrudoxic Ultic Fulvudands

02-07-04-07 Acrudoxic Fulvudands

02-07-04-08 Hydric Pachic Fulvudands

02-07-04-09 Eutric Pachic Fulvudands

02-07-04-10 Pachic Fulvudands

02-07-04-11 Hydric Thaptic Fulvudands

02-07-04-12 Hydric Fulvudands

02-07-04-13 Thaptic Fulvudands

02-07-04-14 Eutric Fulvudands

02-07-04-15 Typic Fulvudands

02-07-05-01 Hydrudands Lithic Hydrudands

02-07-05-02 Aquic Hydrudands

02-07-05-03 Acrudoxic Thaptic

Hydrudands

02-07-05-04 Acrudoxic Hydrudands

02-07-05-05 Thaptic Hydrudands

02-07-05-06 Eutric Hydrudands

02-07-05-07 Ultic Hydrudands

02-07-05-08 Typic Hydrudands

02-07-06-01 Hapludands Lithic Hapludands

02-07-06-02 Petroferric Hapludands

02-07-06-03 Anthraquic Hapludands

02-07-06-04 Aquic Duric Hapludands

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