Applications of Remote Sensing in Land Resource Inventory and Mapping

  • Rajeev Srivastava
Part of the Geotechnologies and the Environment book series (GEOTECH, volume 21)


Comprehensive information on soil resources in terms of type, extent, physical and chemical properties and limitations/capabilities is required for optimal management of land resources and monitoring changes in land qualities. The technological advancements in the remote sensing have revolutionized the land resource inventory and mapping process. The advantage of remote sensing data is that it provides synoptic view of the terrain, which enables to understand the relief, land use and drainage conditions for better delineation of landform-soil units. Further, digital elevation models (DEMs) have facilitated surface parameterization by attributes such as elevation, slope, aspect, flow accumulation, plan and profile curvature to obtain relief or surface topography units. Hyperspectral remote sensing and soil spectroscopy data can be analysed using statistical and chemometric techniques to derive information about wide variety of soil attributes, which can be used for digital soil mapping.


Digital elevation models Digital soil mapping Land resource inventory Landform-soil mapping Remote sensing 


  1. Ballantine JAC, Okin GS, Prentiss DE, Roberts DA (2005) Mapping North African landforms using continental scale unmixing of MODIS imagery. Remote Sens Environ 97(4):470–483CrossRefGoogle Scholar
  2. Bartholomeus H, Epema G, Schaepman ME (2007) Determining iron content in Mediterranean soils in partly vegetated areas, using spectral reflectance and imaging spectroscopy. Int J Appl Earth Obs Geoinf 9(2):194–203CrossRefGoogle Scholar
  3. Ben-dor E, Banin A (1995) Near-infrared analysis as a rapid method to simultaneously evaluate several soil properties. Soil Sci Soc Am J 59:364–372CrossRefGoogle Scholar
  4. Ben-Dor E, Patkin K, Banin A, Karnieli A (2002) Mapping of several soil properties using DAIS-7915 hyperspectral scanner data — a case study over clayey soil in Israel. Int J Remote Sens 23(6):1043–1062CrossRefGoogle Scholar
  5. Ben-Dor E, Taylor RG, Hill J, Demattê JAM, Whiting ML, Chabrillat S, Sommer S (2008) Imaging spectrometry for soil applications. In: Sparks DL (ed) Advances in agronomy, vol 97. Academic Press, Elsevier, pp 321–392Google Scholar
  6. Carré F, McBratney AB, Mayr T, Montanarella L (2007) Digital soil assessments: beyond DSM. Geoderma 142(1–2):69–79CrossRefGoogle Scholar
  7. Chang CW, Laird DA (2002) Near-infrared reflectance spectroscopic analysis of soil C and N. Soil Sci 167(2):110–116CrossRefGoogle Scholar
  8. Chattaraj S, Srivastava R, Barthwal AK, Giri JD, Mohekar DS, Reddy GPO, Daripa A, Chatterji S, Singh SK (2017) Semi-automated object-based landform classification modelling in a part of the Deccan Plateau of Central India. Int J Remote Sens 38(17):4855–4867CrossRefGoogle Scholar
  9. Clark RN (1999) Spectroscopy of rocks & minerals, & principles of spectroscopy. In: Rencz AN (ed) Manual of remote sensing, volume 3, remote sensing for the earth sciences. Wiley, New York, pp 3–58Google Scholar
  10. Dalal RC, Henry RJ (1986) Simultaneous determination of moisture, organic carbon, & total nitrogen by near infrared reflectance spectrophotometry. Soil Sci Soc Am J 50:120–123CrossRefGoogle Scholar
  11. Dobos E, Micheli E, Baumgardner MF, Biehl L, Helt T (2000) Use of combined digital elevation model and satellite radiometric data for regional soil mapping. Geoderma 97(3–4):367–391CrossRefGoogle Scholar
  12. Farifteh J, Farshad A, George RJ (2006) Assessing salt-affected soils using remote sensing, solute modelling, and geophysics. Geoderma 130(3–4):191–206CrossRefGoogle Scholar
  13. Farr TG (2000) The shuttle radar topography mission. In: IEEE aerospace conference proceedings, p 63Google Scholar
  14. Genú AM, Demattê JAM (2006) Determination of soil attribute contents by means of reflected electromagnetic energy. Int J Remote Sens 27(21):4807–4818CrossRefGoogle Scholar
  15. Giri JD, Nagaraju MSS, Srivastava R, Singh DS, Nasre RA, Barthwal AK, Mohekar DS (2016) Accuracy assessment of large-scale soil map prepared by remote sensing approach. Int J Agric Stat Sci 12(1):229–237Google Scholar
  16. Gomez C, Viscarra Rossel RA, McBratney AB (2008) Soil organic carbon prediction by hyperspectral remote sensing and field vis-NIR spectroscopy: an Australian case study. Geoderma 146(3–4):403–411CrossRefGoogle Scholar
  17. Hahn C, Gloaguen R (2008) Estimation of soil types by non linear analysis of remote sensing data. Nonlinear Process Geophys 15(1):115–126CrossRefGoogle Scholar
  18. Hewitt AE (1993) Predictive modelling in soil survey. Soils Fertilizers 56(3):10Google Scholar
  19. Hudson BD (1992) The soil survey as paradigm-based science. Soil Sci Soc Am J 56(3):836–841CrossRefGoogle Scholar
  20. Huete AR (1988) A soil-adjusted vegetation index (SAVI). Remote Sens Environ 25(3):295–309CrossRefGoogle Scholar
  21. ICAR-NBSS&LUP (2005) Reflectance libraries for development of soil sensor for periodic assessment of state of soil resources. NATP Project Report (NBSS No. 835), National Bureau of Soil Survey & Land Use Planning, NagpurGoogle Scholar
  22. Jenny H (1941) Factors of soil formation, a system of quantitative pedology. McGraw-Hill, New-YorkGoogle Scholar
  23. Kriebel KT (1978) Average variability of the radiation reflected by vegetated surfaces due to differing irradiations. Remote Sens Environ 7(1):81–83CrossRefGoogle Scholar
  24. Lagacherie P, McBratney AB, Voltz M (2007) Digital soil mapping: an introductory perspective. Developments in soil science, 31. Elsevier, AmsterdamGoogle Scholar
  25. Lozano-Garcia DF, Fernandez RN, Johannsen CJ (1991) Assessment of regional biomass–soil relationships using vegetation indexes. IEEE Trans Geosci Remote Sens 29(2):331–339CrossRefGoogle Scholar
  26. Manchanda ML, Kudrat M, Tiwari AK (2002) Soil survey and mapping using remote sensing. Trop Ecol 43(1):61–74Google Scholar
  27. McBratney AB, Santos ML, Minasny B (2003) On digital soil mapping. Geoderma 117(1–2):3–52CrossRefGoogle Scholar
  28. McKenzie NJ, Ryan PJ (1999) Spatial prediction of soil properties using environmental correlation. Geoderma 89(1–2):67–94CrossRefGoogle Scholar
  29. Moore ID, Gessler PE, Nielsen GA, Peterson GA (1993) Soil attribute prediction using terrain analysis. Soil Sci Soc Am J 57(2):443–452CrossRefGoogle Scholar
  30. Nagaraju MSS, Kumar N, Srivastava R, Das SN (2014) Cadastral-level soil mapping in basaltic terrain using Cartosat-1-derived products. Int J Remote Sens 35:3764–3781CrossRefGoogle Scholar
  31. Nanni MR, Demattê JAM (2006) Spectral reflectance methodology in comparison to traditional soil analysis. Soil Sci Soc Am J 70(2):393–407CrossRefGoogle Scholar
  32. Qi J, Chehbouni A, Huete AR, Kerr YH, Sorooshian S (1994) A modified soil adjusted vegetation index. Remote Sens Environ 48(2):119–126CrossRefGoogle Scholar
  33. Ravisankar T, Srivastava R (2009) Satellite imagery- their interpretation and applications in soil survey and mapping. In: Bhattacharyya, T. Sarkar, D. & Pal, D.K. (Eds), Soil Survey Manual, NBSS Pub 146, ICAR-National Bureau of Soil Survey & Land Use Planning, Nagpur, India, pp 59–71Google Scholar
  34. Richter R, Schläpfer D (2002) Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: atmospheric/topographic correction. Int J Remote Sens 23(13):2631–2649CrossRefGoogle Scholar
  35. Rondeaux G, Steven M, Baret F (1996) Optimization of soil-adjusted vegetation indices. Remote Sens Environ 55(2):95–107CrossRefGoogle Scholar
  36. Rossel RAV, McBratney AB (1998) Laboratory evaluation of a proximal sensing technique for simultaneous measurement of soil clay and water content. Geoderma 85:19–39CrossRefGoogle Scholar
  37. Salisbury JW, D’Aria DM (1992) Infrared (8–14 μm) remote sensing of soil particle size. Remote Sens Environ 42(2):157–165CrossRefGoogle Scholar
  38. Saxena RK, Verma KS, Chary GR, Srivastava R, Barthwal AK (2000) IRS-1C data application in watershed characterization and management. Int J Remote Sens 21(17):3197–3208CrossRefGoogle Scholar
  39. Shepherd KD, Walsh MG (2002) Development of reflectance spectral libraries for characterization of soil properties. Soil Sci Soc Am J 66:988–998CrossRefGoogle Scholar
  40. Singh D, Herlin I, Berroir JP, Silva EF, Simoes MM (2004) An approach to correlate NDVI with soil colour for erosion process using NOAA/AVHRR data. Adv Space Res 33(3):328–332CrossRefGoogle Scholar
  41. Sommer M, Wehrhan M, Zipprich M, Weller U, Castell W z, Ehrich S, Tandler B, Selige T (2003) Hierarchical data fusion for mapping soil units at field scale. Geoderma 112(3–4):179–196CrossRefGoogle Scholar
  42. Srivastava R, Saxena RK (2004) Technique of large-scale soil mapping in basaltic terrain using satellite remote sensing. Int J Remote Sens 25(4):679–688CrossRefGoogle Scholar
  43. Srivastava R, Sarkar D, Mukhopadhayay SS, Sood A, Singh M, Nasre RA, Dhale SA (2015) Development of hyperspectral model for rapid monitoring of soil organic carbon under precision farming in the indo-gangetic plains of Punjab, India. J Indian Soc Remote Sens 43(4):751–759CrossRefGoogle Scholar
  44. Srivastava R, Sethi M, Yadav RK, Bundela DS, Singh M, Chattaraj S, Singh SK, Nasre RA, Bishnoi SR, Dhale S, Mohekar DS, Barthwal AK (2017) Visible-near infrared reflectance spectroscopy for rapid characterization of salt-affected soil in the indo-Gangetic Plains of Haryana, India. J Indian Soc Remote Sens 45(2):307–315CrossRefGoogle Scholar
  45. Stoner ER, Baumgardner MF (1981) Characteristic variations in reflectance of surface soils. Soil Sci Soc Am J 45(6):5CrossRefGoogle Scholar
  46. Sumfleth K, Duttmann R (2008) Prediction of soil property distribution in paddy soil landscapes using terrain data and satellite information as indicators. Ecol Indic 8(5):485–501CrossRefGoogle Scholar
  47. Tucker CJ, Vanpraet CL, Sharman MJ, van Ittersum G (1985) Satellite remote sensing of total herbaceous biomass production in the Senegalese Sahel: 1980–1984. Remote Sens Environ 17(3):233–249CrossRefGoogle Scholar
  48. Verma KS, Saxena RK, Barthwal AK, Deshmukh SN (1994) Remote sensing technique for mapping salt affected soils. Int J Remote Sens 9:1901–1914CrossRefGoogle Scholar
  49. Wang X, Xie H, Guan H, Zhou X (2007) Different responses of MODIS-derived NDVI to root-zone soil moisture in semi-arid and humid regions. J Hydrol 340(1–2):12–24CrossRefGoogle Scholar
  50. Wilson JP, Gallant JC (2000) Digital terrain analysis. In: Wilson JP, Gallant JC (eds) Terrain analysis: principles and applications. Wiley, New York, pp 1–27Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Rajeev Srivastava
    • 1
  1. 1.ICAR-National Bureau of Soil Survey & Land Use PlanningNagpurIndia

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