application of remote sensing techniques for land

Proc. Indian Acad. Sci. (Engg. Sci.), Vol. 6, Pt. 3, September 1983, pp. 177-188. �9 Printed in India.

Application of remote sensing techniques for land evaluation and classification for agriculture

R S M U R T H Y t , L V E N K A T A R A T N A M * and R K SAXENA National Bureau of Soil Survey and Land Use Planning, Seminary Hills, Nagpur 440006, Indi,a

*Soils Division, National Remote Sensing Agency, Balanagar, Hyderabad 500037, India

Abstract. Classification of agricultural land use is necessary to prepare the land use plans of a country, a district or a village. For this purpose, exploratory, reconnaissance, semi-detailed and detailed surveys are undertaken. Remote sensing techniques like aerial photographs and satellite imageries provide useful information on different scales and assist in monitoring the present land conditions. A case study of Nera watershed presented shows the utility of aerial photographs in the preparation of land husbandry units map on 1 : 50,000 scale.

LArqDSAT data have been used in the delineation and mapping of soil salinity. Two degrees of soil salinity can be differentiated using computer-aided multispectral data analysis system. A study of LANDSAT scene 158-040 shows the areas affected by the various soil degradation processes.

Keywords. Land evaluation; land classification; land husbandry; land degradation; remote sensing.

1. Introduction

Land is used for multifarious activities like agriculture, forestry, development o f grasses, recreation, industrialisation, urbanisation, mining, etc. Pressure on land in the last few decades has considerably increased. G o o d and productive agricultural land is often converted into urban land or used for purposes other than agriculture. Hence it is necessary to evaluate land for its productivity and suitability for various uses. Remote sensing techniques provide quick informat ion about the current status o f land use and the associated characteristics.

Land is a dynamic concept. It carries ecosystems, but by itself forms a part o f the ecosystems. One o f its main components , soil, is a complex ecosystem containing animals and plants o f different kinds and activities. The land, viewed as landscape, as observed today by both visual and other methods o f perception, is a result o f complex interactions o f a mult i tude o f phenomena and processes. We try to use this for our own ends and hope to induce those kinds o f near stability which will benefit us most on a long term basis (Chorley and Kennedy 1971).

2. Land evaluation surveys

Surveys in which land evaluation plays an impor tant role are commonly undertaken at four levels o f intensity: exploratory, reconnaissance, semi-detailed and detailed. The

t since deceased

(F, no0. Sci.)-- 1

177

178 R S Murthy, L Venkataratnam and R K Saxena

Table I . Land suitability surveys: Different levels of intensity and associated major components

Hierarchy of sub-systems

Survey type Objective Map scale & and level of remote land sensing suitability techniques classification

Climate Land units

World Example: ESCAP continent

Broad Broad 1 : 1000,000 Agro-ecol zones exploratory inventories, 1:10,000,000 general order of qualitative land Meteo satellite suitability evaluation LANDSAT, SEASAT

National Exploratory National 1 : 100,000 Agro-r zones example: General order of inventory of 1 : 5000,000 climatic hazards Philippines, suitability human and Meteo-satellite Indonesia, Brazil natural LANDSAT, side

resources, looking radar qualitative land (SLAR), in some evaluation, cases aerial general photographs economic assessment

Regional Reconnaissance Regional 1:I00,000 Agro-ecol zones example: suitability class inventory, 1 : 500,000 and climatic Large island, qualitative land Earth resources hazards Province, State evaluation, satellite small

general scale A.P. (e.g. economic 1 : 70,000 SLAR assessment

District Reconnaissance Quantitative 1 : 25,000 Climatic hazards semi-detailed land evaluation t: 100,000 (risks) suitability and economic Medium scale microclimatic subclass appraisal A.P. (e,g. zones, crop

feasibility 1 : 25,000) small suitability studies scale AP

(1 : 70,000) SLAt

Major landscape units General natural resources information

Major landscape units and natural resources information

Major landscape units and major landforms and relevant natural resource information

Detailed landforms and specific natural resource information

Sub-district Scmidetailed Quantitative 1:25,000 Climatic hazards example: group Detailed land evaluation 1 : 100,000 (risks), crop of villages, suitability sub- and economic Medium scale suitability Block class appraisal AP (e.g.

feasibility 1 : 25,000) studies

Village or Detailed Quantitative 1:5,000 1:25,000 Climatic hazards municipality suitability unit land evaluation Medium to large (risks, crop

and economic scale AP ( e g . suitability) appraisal 1:25,000-1:50,000) feasibility studies

Farm Very detailed suitability units

Detailed landforms and specific natural resources information

Landform elements and specific natural resources information

1 : 1,000 Climatic hazards Landform 1 : 50,000 Large (risks) crop elements and scale AP (e .g . suitability very specific 1 : 5,000) natural resource

information

Land evaluation and classification for aoriculture 179

Land use Markets Infrastructure Population Economic aspects

Major kind of land use

Major kind of land use

General location Major patterns Ethnic groups, World economy pattern demand of communica- density analysis for S u p p l y tion/transpor- distribution prospective

ration sector 'planning'

National Communication, Ethnic groups, Analysis for location, transportation, tribes density perspective and demand/supply service centres, distribution mid term

schools, e t c . employment in national and sectors sector planning

Land utilisation type


Regional Communication, Tribes, density locat ion, transportation distribution demand/supply, service centres employment in nature of schools, etc. sectors merchandise

District Communication, Density location/demand/ transportation distribution, supply nature of service centres, employment merchandise, schools, etc. local prices

Land utilisation Location Communication, Density type commodities, transportation distribution

nature of service centres, groups of merchandise, schools, etc. farmers local prices community

structure

Land utilisation Location Communication Groups of type commodities transportation farmers,

Nature of service centres, community merchandise schools, e t c . structure local prices


Location Communication, Farmers commodities transportation, nature of service centres, merchandise, schools, etc. local prices

Regional economic structure and/or sector analysis, market prospects, rural planning

District economic structure, multisector analysis, rural and settlement planning, market prospects, cost benefit, analysis of development project

Land use and settlement, planning, employment

Farm and village planning, employment

Farm planning, family labour

(Engo. Sci.)-- 2


levels of intensity of the survey should be determined by the specific objects of the investigation and table 1 gives information on different levels of intensity and associated major components including map scales and remote sensing techniques to be used for each level of land suitability classification. Exploratory surveys are concerned with broad inventories of natural resources at the national or regional level resulting in qualitative land evaluation and generalised economic and social analysis. Reconnaissance surveys are generally concerned with broad inventories at regional or state level and determine the amount and quality of land available for different land uses. Exploratory and reconnaissance surveys form basis for prospective and medium term national and regional planning. They can be carried out on a low budget with minimum time and manpower especially by using data from space platforms, making use of already available information. An example is the satellite remote sensing survey of Haryana state where geomorphological, soil and land use maps were prepared with suitable recommendations to the state government which were useful for regional planning and development. Semi-detailed surveys mainly involve quantitative land evaluation and economic appraisal and are carried out as feasibility studies for development projects. Detailed surveys involve quantitative land evaluation and economic appraisal for project implementation.

3. Land evaluation and classification for agriculture

Evaluation of land for its suitability for various uses is a prime requisite for preparation of land use plans of a region. Young (1978) described six basic principles of land suitability and evaluation. They are (i) Land suitability assessed for specified kinds of use (ii) Comparative evaluation for benefits obtained with inputs needed (iii) A multidisciplinary approach (iv) Evaluation in terms relevant to local or national conditions (v) Suitability for use on a sustained basis i.e. the use not bringing about severe or progressive degradation (vi) Evaluation involving a comparison of two or more kinds of use, which are not exclusively agricultural.

Kellogg (1961) described 'soil productivity' as that quality of a soil which summarises its potential for producing specified plants or sequences of plants under defined sets of management practices. It is measured in terms of outputs in relation to inputs for a specific kind of soil under physically defined systems of management.

Agricultural Iand use includes cropping systems, horticulture, grazing and forestry. This is a very diversified activity. The kind of land use is governed by social, socio- economic and characteristics of soil. Requirement of types of soil/land differs from the type of crop/vegetation, viz. paddy needs poorly-drained soils while groundnut needs well-drained soils; forest trees need very deep soils while pasture needs shallow soils.

In India, the land capability classification has been widely used to regionalise an area of land into units with similar kinds and degrees of limitations. Land capability classification is an interpretative grouping of soils mainly based on (i) the inherent soil characteristics, (ii) external land features and (iii) environmental factors that limit the use of land. Information on (ii) i.e. external land features is quickly provided by remote sensing techniques and with proper field checks, it also provides information about the inherent soil characteristics.

Numerous parametric methods have been evolved to assess soil suitability (Storie 1950, 1954; Riquier & Bramao 1964; Riquier et al 1970; Riquier 1971; FAO

Land evaluation and classification for agricuhure 181

1976). The main advantage of parametric methods is that they provide figures, which can be used by economists in their calculations (Brinkman & Smyth 1973).

4. Case study

For land evaluation which requires interpretation of landscape and the process by which it has been formed, photo-interpretation has been used to establish relationship between landform and parent material and soil provides necessary inputs for proper evaluation of land characteristics. In the present study, Nera watershed, a tributary of river Tons in Sirmaur district of Himachal Pradesh has been selected. The area lies between 30~ ' and 30~ latitudes and 770-32 ' to 77~ E longitudes. The drainage system of the watershed is presented in figure 1.

In the Himalayas, aspect and altitude play an important rote in the growth of vegetation. Southern aspect is warmer than the north, as it receives more solar radiation and consequently less moisture. The steep slopes of the northern aspect are generally under good forest cover, whereas the steep slopes of southern aspect are under open forests or barren land and under grass cover with thin vegetation. It is indicative of variation in micro climate on both the aspects. Soil moisture regime on northern aspect is udic, whereas it is udic to ustic on southern aspect. Effect of altitude and aspect on land use has been demonstrated by Saxena & Singh (1978) and Saxena & Barthwal (1980). Figure 2 shows the aspects viz northern and southern.

The study area has been demarcated into three altitudinal zones viz A = < 1000 m, B = 1000-2000 m and C = 2000-3000 m (figure 3). Present land use showing cul- tivated land, forest land and open scrub and grass land is illustrated in figure 4. These maps were superimposed and a map showing land husbandry units (LUU) is given in figure 5. The LHU consists of aspect, altitude and present land use, LHtJ is very important for practical management of the land. The associated characteristics of each LHU'S viz slope and erosion are also studied using aerial photographs.

The map presented in figure 6 shows geological formations of the area. The main formations (Rupke 1974) are Chandpur, Nagthat, Blani/Infrakrol, Krol (A, B, C, D and

5O

" l " -1 "~ "l'"

Figure I. Drainage system of NERA watershed.


Figure 2. Aspect. 1. Northern. 2. Southern

Figure 3. Altitudinal zones. A. 1000 m. B. 1000-2000 m. C. 2000-3000 m.

cult ivated Land

fo res t

open scrub/grasses

Figure 4. Present land use

Land evaluation and classification for agriculture 183

I + +'~+~ ""

I~A~c ~Azc ~ s t c ~Bzc ~c~c I~czc

~A1F ,~A2F ~~ B 1F ~B2F ~~ C1F ~C2F

m~A~o I~AZ0 ~B~0 ~BZ0 ~C~0 ~C20

Figure 5. Land husbandry units

( Rupke 1974 -F)

Figure 6. Geological map. A--Upper Tal: qutze, calc, grit. B---Lower Tal: Sh, black Sh, congl. C--Krol CDE, List Sh. D--Krol B---red/green sh list. E--Krol sst. + Krol A: S. St, shale, list. F--Blani/InfraKrol: list, silt, G--Nagthat quartzite, grits, slates, shale. H - - Chandput shale, slate, list, qutze, black shale.

E) and Tal (Upper and Lower). These formations mainly comprise limestone, shale, grit, quartzite, conglomerate of orthoquartzite, slate and silt stone. They have affected the soils and land use of the region.

Soil map showing distribution of soils in the watershed is presented in figure 7. The mapping unit consists of association of soil series. Twelve soil series are identified viz. Simog, Rohru, Hatkoti, Dhar, Kharapathar, Anu, Chandi, Kansar, Sheriya, Dino, Daduwa and Lokhandi. The soil series have been classified according to soil taxonomy. Soils are grouped into Udorthent, Fluvaquent, Eutrochrept, Dystrochrept, Hapludalf, Argiudoll and Hapludoll. Soils are moderately deep to very deep, dominantly loamy skeletal and acidic. The mineralogy is mixed and temperature regime is hyperthermic.


Figure 7. Soil map. l-Simog-Anu. 2-Sheriya-Daduwa-Simog. 3-Sheriya-Daduwa- Shimog-rock outcrops (33 %). 4-Rohru-Chandi-Simog. 5-Sheriya-Kharapat har. 6-Dino-Daduwa-Dhar. %Rohur-Dhar-rock outcrops (33-50%). 8-Chandi-Kharapathar- Dhar. 9-Lokhandi-Kharapathar-rock outcrops (33-50 %).

5. Land evaluation

In the present investigation, soils were interpreted for productivity potential of soils for crops, pasture and forest and non-forest tree crops according to Riquier et al (1970). The following factors have been considered for land evaluation, moisture (M), drainage (D), effective soil depth (P), texture and structure (T), base saturation (N), soluble salts (S), organic matter (O), mineral exchange capacity and nature of clay (A) and mineral resources (M). Productivity is the product of all these factors.

P = H x D x P x T x N x S x O x A x M .

Potentiality (P') has been calculated taking into consideration the possible improvement that can be brought about over existing practices. Coefficient of improvement is P' /P. Productivity and potentiality of the soil series is presented in table 2. It is observed that Sheriya Kansar, Chandi and Rohru are best suited for agriculture, while all the soils are suited for pasture. Suitability of soils for forest and non-forest tree crops is extremely poor to average. The poor productivity rating for forest and non-forest tree crops is due to the low rating of drainage class. Saxena et al (1982) have suggested change in the drainage ratings of Riquier et al (1970).

Table 2. Soil series--their classification, productivity and potentiality

Soil Soil classification Crop Pasture Forest Series P P' P P' P P'

Simog Rohru Hatkoti Dhar Kharapathar Anu Chandi Kansar Sheriya Dino Daduwa Lokhandi

Typic Udorthent, loamy-skeletal 7 54 22 68 6 25 Typic Udorthent, loamy-skeletal 33 75 50 75 30 33 Typic Fluvaquent, loamy-skeletal 6 30 23 64 5 7 Dystric Eutrochrept, loamy-skeletal 16 75 56 85 24 33 Typic Dystrochrept, loamy-skeletal 18 68 50 76 7 23 Typic Hapludalf, loamy-skeletal 10 38 25 60 5 20 Typic Hapludalf, fine loamy 33 75 50 75 30 33 Udic Hapludalf, fine silty 38 67 49 76 27 38 Typic Argiudoll, fine loamy 41 75 69 85 23 25 Typic Argiudoll, loamy-skeletal 19 76 31 86 22 30 Typic Hapludoll, loamy-skeletal 15 67 28 76 18 25 Typic Hapludoll, loamy-skeletal 16 60 40 68 6 20


In the present ratings aspect and altitude have not been considered which are essential in the Himalayan region. At present information on moisture regime on different aspects and altitude is not available, which may possibly be inferred by the sequential aerial photography spread over a few years span in different seasons with sufficient ground check.

6. Satellite remote sensing for agricultural land and soil surveys

For soil scientists, the LANDSAT data has two important formats:

(i) Picture-like images (false colour composites: black and white positive or negative in each of the four spectral bands) that appear as aerial photographs, each depicting 185 x 185 km area of the earth surface.

(ii) Digital output of the intensity and wavelength of light reflected from any 80 x 60 m portion of the earth surface (computer compatible tape).

There are two approaches of interpretation of both airborne and satellite multispectral dat~/viz, image interpretation and computer-aided approach. Visual interpretation techniques were used in India to delineate the soil associations in several regions e.g. Bundelkhand region of Uttar Pradesh (NRSA 1980). The irrigability of various soil associations has also been interpreted for drought-prone areas of Karnataka (NRSA 1978b). Physiographic and soil boundaries delineated on aerial photos under stereoscope could be correlated with the boundaries on the satellite images. However, due to the effect of vegetation, moisture and other factors including the resolution of the satellite data, perfect correlation for all the soil units may not be possible but the boundaries on these images may give the association of the units observed on the aerial photos.

The computer-aided techniques utilise the spectral variations as fundamental to the analysis, later adding the use of spatial and temporal information as circumstances require and permit (Landgrebe 1973). LANDSAT digital data were used for soil mapping for parts of Andhra Pradesh (NRSA 1978a), and southern part of Tamil Nadu (NRSA 1979a) with limited ground truth. Delineation upto association of sub-groups was possible using LANDSAT data but using aerial scanner data, even higher intensity soil maps could be prepared with sufficient ground truth. Multispectral data could be expected to augment the soil survey efforts but of course cannot replace the traditional soil surveying especially for preparing semi-detailed/detailed soil maps. However soil maps prepared using satellite data would undoubtedly form a map base for further detailed soil surveying.

7. Land degradation and land suitability

Land evaluation considers the economics of the proposed enterprises, the social benefits for the people of the area and the country concerned and the consequences, beneficial or adverse, for the environment. Therefore, environmental degradation is also taken into account when assessing the suitability of the soil for agriculture. Since soil degradation is widespread in many countries, there is an urgent need to conserve the remaining productive soil, and to prevent the speed of degradation to areas not yet affected. Among other methods, the use of remote sensing techniques has been


recommended for the assessment of soil degradation by Food and Agricultural Organisation (FAO). Table 3 shows that at all scales, remotely sensed data are advantageous (rAo, 1979) as data source for soil salinity/alkalinity.

LANDSAT data are used in India in delineation and mapping of soil salinity (NASA 1979b and Venkataratnam 1980) wherein two degrees of soil salinity can be differentiated using computer-aided multispectral data analysis system (M-DAS). Table 4

Table 3. Data sources for salinity/alkalinity and methodology (FAO 1979)

�9 Methodology Scale Mapping factor Data source references

General level Soil orders and great smaller than groups, dominant soil 1 : 1,000,000 + s0il phases

Regional level Great soil groups and 1 : 100,000 to soil phases 1 : 1,000,000

Detailed level Soil family + distribution 1 : 20,000 to of salinity within the 1 : 100,000 profile

Very detailed level Soil series, changes in larger than E.c and ESP in the soil 1 : 20,000 profile for each crop and

crop rotation

FAO/UNESCO soil map of the world land system maps, satellite imagery

National soil maps, national soil survey reports, land system maps, satellite imagery

Country level soil surveys, soil survey district reports, new soil surveys where appropriate, aerial photo-interpretation

Field measurements, detailed soil maps

FAO/U/qESCO 1974, soil survey staff, 1975

as mentioned above

As mentioned above and International Commission on Irrigation and Drainage, 1966, FAO/ONESCO, 1973

As mentioned under detailed level

Table 4. Area of soils affected lay various limitations/hazards in scene 1584)40

Category Area affected % of Degradation/ (km 2) Total hazard

Highly saline/alkaline Saline/alkaline soils

Lowlying areas (water-logging)

492'87 1 - 4 4 Salinity/alkalinity 1,800-54 5.25 -do-

1,196.00 3.49 High water table, bad drainage

4,762'43 13.89 Wind erosion, low fertility, excessive permeability

12,868-68 37-52 -do-

Active sand dunes and barren sandy areas

Sandy areas and partially/fully stabilised areas

Total areas under the above 21,120.52 61.59

Total area for the whole scene 34,298.80 10ff00


gives the areas affected by various soil degradation processes and limitations for the LANDSAT scene having path-row number 158-040 pertaining to the Indo-Gangetic plains of Northern India.

Part ofcolour-coded soil map showing the salt-affected areas prepared using M-DAS is further enlarged on printer-plotter system (Venkataratnam 1980) as seen in figure 8. The small scale colour-coded soil maps prepared using LANDSAT data at 1:250,000 scale showing various soil hazards like soil salinity/alkalinity, water-logging and desertifi- cation would help the officials of the State Agriculture Departments for planning the reclamation and other correction measures to improve the productivity of these lands.

References

AIS&LUS 1970 Soil survey manual (New Delhi: IARI) Brinkman R & Smyth A J (eds) 1973 Land evaluation for rural purposes. (Wageningen: Int. Inst. Land Reclam.

and Improvement (ICR1)) Chorley R J & Kennedy B A 1971 Physical geooraphy, a system approach (London: Prentice Hall) FAO 1976 Bulletin 32 FAO 1979 A provisional methodology for soil degradation assessment, FAO, Rome Kellogg Ch E 1961 Soil interpretation in the soil survey. Soil Conservation Service, Washington (D.C.)

US Dept. Agric. Klingebiel A A & Montgomery P H 1966 USDA Soil Conserv. Serv. Agr. Handbook 210 Landgrebe D A 1973 An evaluation of machine processing techniques of ERTS- 1 data for user applications,

Proc Third ERTS-1 Syrup. Goddard Space Centre, Vol. 1 p. 41 NRSA 1978a Satellite remote sensing survey of natural resources of Andhra Pradesh, NRSA project report,

Secunderabad, India NRSA 1978b Satellite remote sensing survey, Drought prone area, part of Karnataka, NRSA project,

Secunderabad, India NRSA 1979a Satellite remote sensing survey of the Southern Part of Tamil Nadu, NRSA project, Secunderabad,

India NRSA 1979b Satellite remote sensing survey of Haryana, NRSA project report, Secunderabad, India NRSA 1980 Satellite remote sensing survey: Bundelkhand and adjoining areas, U.P., NRSA project report for

CST, U.P. Riquier J 1971 Mimeograph ACL: Misc/71/12 Rome FAO. Riquier J & Bramao D L 1964 Soil resources of Nigeria 1965-1980, p. 386, Rome, FAO Riquier J, Bramao D L & Cornet J P 1970 Mimeograph AGL: TESR/70/6 Rome, FAO Rupke Jan 1974 Sediment. Geol. 11 81 Saxena R K & Barthwal A K i980 Photonirvachak J. Photo int. 6. Saxena R K & Singh B M 1978 Photonirvachak J. Ind. Soc. Photo-int. 6. Saxena R K, Murthy R S, Kumar R & Saxena P B 1982 Soil suitability for agriculture and other uses in Tons

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Storie R E 1950 Trans. 1V Amsterdam Int. Con~. Soil Sci. 1 p. 33 Storie R E 1954 Trans. V Int. Congr. Soil Sci. 6 Storie R E 1978 Spec. Publ., Div. Agric. Sci. Univ. Calif., No. 3203 Venkataratnam L 1980 Delineation and mapping of agricultural soil limitations/hazards in arid and semi-

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application of remote sensing techniques for land

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