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GIS applications in soil data analysis

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GIS applications in soil data analysis

S.S.Ramakrishnan1 and Prof.V.Guruswamy2
Sr. Lecturer in Civil Engg.1, Honorary professor2
Center for GIS Applications, Anna University,
Chennai 6000025, India

Abstract
Soil survey is an integral part of an effective agricultural research and advisory program. It provides complete information about soils and is an inventory of the soil resource of the area. It gives the information needed for planning landuse and soil management programs. In Tamil Nadu Soil survey is being conducted by “Soil Survey and Landuse Organization,” Coimbatore. The Soil survey reports are available for the users. This paper explains the use of GIS in storage, retrieval and visualization of soil data. If the soil information is available in GIS and maintained by an organization like” Soil Survey and Land use Organization,” then many professionals could access the information for development purposes.
Minjur and Panchetty area, part of Chennai basin, situated in the northern part of the Chennai City is taken for the present study. It lies within the Latitude of 13 ° 13′ 00″ N to 13° 25′ 00″ N and Longitude of 80° 05′ 00″ E. to 80° 20 ‘ 00″E and has a length of 28 km in the East West direction 26 km in the North South direction. The study area is 496 sq. km in extent.
A soil survey of the study area was conducted during 81-82, by the soil survey and land use organization, Coimbatore. The soil survey report (Report no.59 Soil survey and land use organization.1985) and field samples were used to create a database on soil characteristics. The soil survey report is based on low intensity survey however, it can be used for many planning purposes and hence, it is used to demonstrate the usefulness of GIS in analysis and interpretation of soil data.
GIS software Arc/info and Arcview are used to create the soil database. The attribute data of the soils are depth, texture, drainage, pH, salinity and alkalinity conditions, run off, erosion etc. The attribute data are linked with spatial data. Hence, linking spatial aspect of the soils with non-spatial characteristics forms the soil model. The necessary information and thematic maps could be easily generated using the model. Some applications are explained in this paper. The usefulness of the GIS will be enhanced if these capabilities are operated through the Internet.

Introduction

Soil survey is an integral part of an effective agricultural research and advisory program. It provides complete information about soils and is an inventory of the soil resource of the area. It gives the information needed for planning land use and soil management programs. In Tamil Nadu soil survey is being conducted by Soil Survey and Land use Organization, Coimbatore. The soil survey reports are available in for the users. This paper explains the use of GIS in accessing soil information and interpreted maps. If the soil information available in GIS and maintained by an organization then it could be accessed by many professionals who want to get the information for development purposes.

Figure 1: Study area and its location


Need for the study
Agriculture is the backbone of Indian economy. In order to produce food for increasing population the land and water resources have to be used more sustainable manner. Soil and water are the two main component of the agricultural system and they are undergoing degradation in many aspects. Soils are being degraded due to erosion, water logging, salinity etc. Hence, knowledge about the soils is important for any project planning in order to satisfy the environmental conditions. In this context many professionals may need the soil data and at present the details are available in publications of Soil and Land use organisations. Soil data is spatial in nature and they can be easily handled and analysed using GIS. Sharing and dissemination of information is easier when the information is stored in digital form. Also the data in GIS can be analysed with other type of data to get the desired information. Hence advantages in use of GIS in handling soil data are demonstrated in this paper.

Review of Literature
Fayer et al. (1995) carried out a study to estimate the recharge using GIS. It was used to identify all possible combinations of soil type and vegetation and to assign to each combination, an appropriate estimate of recharge. Procedures to assess erosion in a catchment in Northwest Iran were evaluated using GIS and Remote Sensing (Meijerink et al.1996). The spatial segmentation of the catchment and derivation of the physical parameters related to erosion in the cells are performed through a GIS technique using the Integrated Land and Water Information System (ILWIS) package (Kothyari 1997). Rahman et al (1997) evaluated an alternative methodology for producing soil maps through a process of model construction and projection into a map base using ARC/INFO geographical information system. Soil Salinization risk at regional level was assessed using geographical information system by Bui et al (1995). Assessment of the risk of regional salinization involves integration of hydrology, hydrogeology, soil, and land management issues. The article discusses an example of the use of soil survey data integrated with water resources and digital elevation data in GIS, to estimate the risk of salinization after tree clearing at upper Burdekin river basin in the wet /dry tropics of North Queensland.

Study area and methodology
The study area (fig.1) Minjur and Panchetty area, part of Chennai basin, situated in the northern part of the Chennai City is taken for the present study. It lies within the Latitude of 13 ° 13′ 00″ N to 13° 25′ 00″ N and Longitude of 80° 05′ 00″ E. to 80° 20 ‘ 00″E and has a length of 28 km in the East West direction 26 km in the North South direction. The study area is 496 sq. km in extent.

A soil survey of the study area was conducted during 81-82, by the soil survey and landuse organization, Coimbatore – 40. The soil survey report (Viswanathan et al 1985) and field samples were used to create a database on soil characteristics. The map is prepared by conducting low intensity survey however the interpretation is made to demonstrate the use of GIS in analysis and interpretation of soil data.

GIS applications in soil data analysis

Type of soil present in the study area
The distribution of different soil families and soil association is as follows.


  1. Typic ustipsamments (TUSMP)
  2. Coarse loamy, Typic Ustorthents (CLTUT)
  3. Fine loamy, Fluventic ustochrepts (FLFUC)
  4. Fine loamy, Udic Ustochrepts (FLUUC)
  5. Fine loamy Udic Haplustalfs (FLUHLT)
  6. Fine, Vertic Haplustalfs (FVHLT)
  7. Fine loamy Udic Paleustalfs (FLUPUT)
  8. Fine, Entic Chromusterts (FECM)
  9. Loamy skeletal, Udic Ustochrepts (LSUUC)

Soil associations
The following soil associations are found in the study area.
  1. Typic ustipsamments- Fine loamy, Fluventic ustochrepts (1-3)
  2. Fine, Vertic Haplustalfs- Fine, Entic Chromusterts- Fine loamy, Fluventic ustochrepts (6-8-3)
  3. Typic ustipsamments-Fine, Entic Chromusterts- Fine loamy, Fluventic ustochrepts (1-8-4)
  4. Fine, Entic Chromusterts, Fine loamy, Fluventic ustochrepts (8-3)
  5. Fine loamy Udic Haplustalfs, Typic ustipsamments (5-1)
  6. Fine loamy, Fluventic ustochrepts- Fine,Vertic Haplustalfs- Typic ustipsamments (3-6-1)
  7. Fine loamy,Udic Haplustalfs – Fine,Vertic Haplustalfs (5-6)
  8. Fine loamy,Udic Ustochrepts- Fine loamy Udic Paleustalfs (4-7)
  9. Fine loamy,Udic Haplustalfs -Fine loamy, Fluventic ustochrepts (6-9)
  10. Fine loamy, Fluventic ustochrepts – Typic ustipsamments (6-1)

Figure 2: Soil Map of the study area
Soil survey interpretation
Soil survey interpretation comprises the organization and presentation of knowledge about characteristics, qualities and behavior of soils, as they are classified and outlined on soil maps. A well-prepared soil map, based on a sound classification system is useful as a base for different forms of interpretation. Soil survey data can be made use of in the development of agriculture, irrigation purposes, forestry, several engineering purposes, and so on. Land capability, soil irrigability and soil suitability classifications are made based on the soil survey interpretation. Based on the interpretation the potentialities and limitation of the soils can be obtained and such information are used to construct database using GIS. The soil map that is obtained from soil survey report is (1:50 000 scale) digitized. A database using Arc/info is formed. Each polygon in the digitized map represents the classes of soil family and soil associations. The attribute data of the soils are depth, texture, drainage, pH, and susceptibility to water logging, salinity and alkalinity, erosion, field capacity, nutrient-holding capacity respectively. Hence linking spatial aspect of the soils with non-spatial characteristics forms the soil model. The soil map of the study area is shown in the fig.2. The necessary information and thematic maps can be easily generated using the model. Some applications are explained in this paper as follows.


Figure 3: Soil salinity risk area


Results and discussion
Using the soil model it is possible to get desired thematic map like the crop suitability map, land irrigability map etc. In this paper application on assessing salinity and water logging problem is demonstrated one by using with soil model. Potentialities and limitation of soils of the first seven types of soil except sixth (1-5 and 7) are free from salinity, alkalinity, and water logging problem. The soil six Fine loamy Udic Haplustalfs is moderately drained and potential to become the alkaline soil as per the soil survey interpretation. The soil type Fine, Entic Chromusterts FECM (8) is very deep, fine texture, high water holding capacity, poor drainage, slow permeability. Hence, water logging and salinity problem is higher in this type of soil. This family of soil will cause problem to sustainable agriculture. Using GIS soil types are ranked according to the salinity or water logging risk. Then by analysis thematic maps were prepared. The areas prone to water logging and soil salinity are shown in the fig. 3.


From above illustrations it is clear that use of GIS in soil data handling makes decision-making process easier for planners. Incidentally, it is felt that the data collection process will be easier and comfortable if data owning department puts the information in Internet.



References


  • Viswanathan.R et al (1985), “Soil survey report of Ponneri taluk, Chengalpattu District TamilNadu,” Report No.59, Soil Survey and Land use Organization, Coimbatore, 641040.
  • Fayer M.J. et al (1995), “Estimating recharge rates for a groundwater model using GIS,” Journal of Environmental quality V 25 n 3 May-June 1996. pp 510-518.
  • Kothyari et al (1997), “Sediment yield estimation using GIS,” Hydrological science journal V 42 n 6 Dec. 1997.pp 833-843.
  • Meijerink et al (1996), “Comparison of approaches for erosion modeling using flow accumulation with GIS,” Application of GIS system in Hydrology and water resource management. IAHS Publication n 235. IAHS press, Wallingford, Engl. pp 437-444.
  • Rahman et al. (1997),”Wyoming rocky mountain forest soils. Mapping using an ARC/INFO Geographical Information System,” Soil science society of America journal V 61 n 6 Nov-Dec. pp1730-1737.
  • Bui et al. (1995), “Use of soil survey information to assess regional salinization risk using Geographical information system,” Journal of Environmental quality V 25 n 3 May-June. pp 433-439.