Home > Geospatial Application Papers > Agriculture & Soil > Overview

Overview | Crop Production | Crop Pattern | Crop Yield | Irrigation | Soil Management | Precision Farming | Relevant Products | Relevant Links




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.
Page 2 of 2
| Previous |