Abstract
In this study an attempt has been made to delineate, map out, and generate database on soil resources for meeting challenges of land degradation in irrigated agro-ecosystem using geospatial tools of remote sensing (RS) and geographic information system (GIS). Gauriganj block, Amethi district (lies between 26° 7ʹ5ʺ N to 26° 19ʹ5ʺ N latitudes and 81° 36ʹ45ʺ E to 81° 45ʹ18ʺ E longitudes), Uttar Pradesh was selected for study. The space born multispectral Landsat 7 ETM+data of year, 2014 and corresponding survey of India Topographical sheets numbered 63 F/11, 63 F/12, and 63 F/16 were applied for soil survey. The satellite image of the study area was processed using standard visual image interpretation approach incorporating field check and attribute data in ERDAS imagine 9.1 and ARC view 3.2a software. Digital image processing techniques were also applied for generation ad-on-data for visual image interpretation. On the basis of satellite image analysis and information regarding soil surveys conducted earlier under Sharda Sahayak C.A.D project (1988) Lucknow (U.P.), entire study area was classified into 83 soil interpretation units. The database on both units was generated in GIS environment considering USDA soils classification system. The soils of the study area were grouped into two orders, four sub-orders, five great groups, six subgroups, five families, and seven series. The study reveals that the RS and GIS techniques can be used in an effective manner in soil resource investigation and mapping. This study may prove a better input in proper management of degraded lands in the study area.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bishop YMM, Fienberg SE, Holland PW (1975) Discrete multivariate analysis theory and practice. MIT Press, Carnbridge, MA, p 557
Biswas RR (1987) A soil map through landsat satellite imagery in part of the Auranga catchment in Ranchi and Palamon district of Bihar, India. Int J Remote Sens 4:541–543
Biswas et al (1999) Prioritization of sub watershed based on morphometric analysis of drainage basin. Photonirvachak 27(3):155
DAC (1994) Draft report on status of land degradation in India. Department of Agriculture and Co-operation
Epema GF (1986) Processing thematic mapper data for mapping in Tunisia. ITC J 30–34
Karale RL, Venugopal KR, Hilwig FW(1970) Reconnaissance soil survey in the Ganges alluvial plain in Meerut District, UP. Report submitted to IPI, Dehradun
Kudrat M, Tiwari AK, Saha SK (1997) Modelling sediment yield for prioritization of sub-watersheds using remote sensing and GIS techniques. Geocarto Int 12:31–38
Karale RL (1992) Remote sensing with IRS-1A in soil studies: development, status and prospects. In: Karale RL (ed) Natural resources management—a new perspective. NNRMS, Bangalore, pp 28–143
Kudrat M, Prabhakaran B, Sastry TRSVS, Tiwari AK, Sharma KP, Manchanda ML (1995) Quantative estimation of soil loss through remote sensing: a case study of part of Chotanagpur Plateau, India. In: Varma CVJ, Rao ARG (eds) Management of sediments: philosophy, aims and techniques. Central Board of Irrigation and Power, New Delhi, pp 37–44
Kudrat M, Saha SK, Tiwari AK (1990) Potential use of IRS LISS II digital data in soil land use mapping and productivity assessment. Asian Pacific Remote Sens J 2:73–78
Kudrat M, Tiwari AK, Saha SK, Bhan SK (1992) Soil resource mapping sing IRS-1A LISS II digital data—a case study of Kandi area adjacent to Chandigarh (India). Int J Remote Sens 13:3287–3302
Karale RL, Bali YP, Rao KV (1981) Soil mapping using remote sensing techniques. In: Proceedings Indian academy of science and engineering sciences 3:197–208
Korolyuk TV, Shcherbenko HV (1994) Compiling soil maps on the basis of remotely sensed data digital processing: soil interpretation. Int J Remote Sens 15:1379–1400
Lal R (1995) Global soil erosion by water and carban dynamics. In: Lal R, Kimble J, Levine E, Stewart BA (eds) Soil management and greenhouse effect. Soil Sci Soc Am 41:39–51 (Special Publication)
Lee KS, Lee GB, Tyler J (1988) Determination of soil characteristics from thematic mapper data of a cropped organic–inorganic soil landscape. Soil Sci Soc Am J 52:1100–1104
Landsat 7 Science Data Users Handbook (2004) NASA. http://landsat.gsfc.nasa.gov/wp-content/uploads/2016/08/Landsat7_Handbook.pdf
Mirajkar MA, Srinivasan TR (1975) Landsat photo interpretation for preparation of small scale maps through a multistage approach. Photonirvachak 3:87–98
Milind R, Wadodkar Ravisankar T (2011) Soil resource database at village level for development planning. J Indian Soc Remote Sens 39(4):529–536
Mandal C, Mandal DK (1996) Qualitative assessment of soil erosion from soil survey data: a case study of Nagpur district. Geogr Rev India 58(1):29–40
Myneni RB, Hall FG, Sellers PJ, Marshak AL (1995) The interpretation of spectral vegetation indexes. IEEE Trans Geosci Remote Sens 33:481–486
Mishra A, Sharma SD (2003) Leguminous trees for the restoration of degraded sodic wasteland in eastern Uttar Pradesh, India. Land Degrad Dev 14:245–261
NRSA(1976) An application of satellite remote sensing techniques for integrated pilot survey of natural resources in parts of Punjab and Haryana—an abstract report. National Remote Sensing Agency, Secunderabad, India
NRSA (1978) Satellite remote sensing survey of natural resources of Andhra Pradesh. Project report. National Remote Sensing Agency, Secunderabad, India
NRSA(1979) Satellite remote sensing survey of natural resources of Haryana. Project report. National Remote Sensing Agency, Secunderabad, India
NRSA (1981) Satellite remote sensing survey for soil and land use in part of Uttar Pradesh. Project report. National Remote Sensing Agency, Hyderabad, India
Narayan V, Dhurua V, Babu R (1983) Estimation of soil erosion in India. J Irrig Drain Eng 109(4):419–433
Prakash A, Gupta RP (1998) Land-use mapping and change detection in a coal mining area—a case study in the Jharia Coalfield, India. Int J Remote Sens 19:391–410
Patil J (2003) Sustainable agricultural development: issues and programs. Financ Agric 35(1):35–38
Ravisankar T, Thamappa SS (2004) Satellite data interpretation and analysis for soil mapping. In: Venkatratnam L, Ravisankar T, Sudarshana R (eds) Soils and crops. NRSA Publication, Hyderabad
Rao BR, Fyzee M, Wadodkar MR (2004) Utility of remote sensing data for mapping soils at various scales and levels. In: Venkatratnam L, Ravisankar T, Sudarshana R (eds) Soils and crops. NRSA Publication, Hyderabad
Rawashdeh SA, Saleh B (2006) Satellite monitoring of urban spatial growth in the Amman Area, Jordan. J Urban Plan Dev 132.4(211):0733–9488
Sharma SD, Khan GH, Prasad KG (2001) Selection of suitable provenances of Dalbergia sissoo for sodic lands. Indian J For 24:58–64
Singer MJ, Ewing S (2000) Soil quality. In: Sumner ME (ed) Handbook of soil science. CRC Press, Boca Raton, FL
Saha SK, Kudrat M, Bhan SK(1991) Erosional soil loss prediction using digital satellite data and universal soil loss prediction-soil loss mapping in Siwalik Hills in India. In: Murai S (ed) Applications of remote sensing in Asia and Oceania. Asian association on remote sensing. Tokyo, pp 369–372
Soil Survey Staff (1975) Soil taxonomy. A basic system of soil classification for making and interpreting soil surveys. USDA/SCS. Agricultural Handbook, 436. U.S. Government Printing Office, Washington, DC, p 396
Soil Survey Staff (1994) Key to soil texonomy. USDA Soil conservation service, Washington DC, USA
Soil Survey Staff (1999) Soil taxonomy. A basic system of soil classification for making and interpreting soil surveys. In: Agricultural handbook 436. Natural resources conservation service, 2nd ed. USDA, Washington DC, USA, p 869
Soil Survey Staff (2004) R Burt (ed.). Soil survey laboratory methods manual. Ver. 4.0. USDA/NRCS. Soil survey investigations report no. 42. U.S. Government Printing Office, Washington, DC. http://soils.usda.gov/technical/lmm/. Accessed 24 Jan 2011
Soil Survey Staff (2009) R Burt (ed.) Soil survey field and laboratory methods manual. Ver. 1.0. USDA/NRCS. Soil survey investigations report no. 51. http://www.soils.usda.gov/technical/. Accessed 24 Jan 2011
Soil Survey Staff (2010) Keys to soil taxonomy, 11th ed. USDA/NRCS. U.S. Government Printing Office, Washington, DC. http://ftpfc.sc.egov.usda.gov/NSSC/Soil_Taxonomy/keys/2010_Keys_to_Soil_Taxonomy.pdf. Accessed 24 Jan 2011
Sellers PJ (1985) Canopy reflectance, photosynthesis, and transpiration. Int J Remote Sens 6:1335–1372
Sehgal JL, Abrol IP (1994) Soil degradation in India: status and impact. Oxford and IBH Publishing, New Delhi, India
Venkataratnam L, Rao KR (1977) Computer aided classification and mapping soils and soil limitations using landsat multispectral data. In: Proceedings of symposium on Remote sensing for hydrology, agriculture and mineral resources. Space Applications Centre, Ahmedabad, India, pp 101–104
Venkataratnam L (1980) Use of remotely sensed data for soil mapping. Photonirvachak 8:19–26
Acknowledgements
The Author thankfully acknowledged to Indian Council of Social Science Research (ICSSR), New Delhi which provided financial assistance to conduct this study. The author is also grateful to Scientist In-charge, NRDMS centre Sultanpur and teaching staff of the Agriculture Science Faculty, Kamla Nehru Institute of Physical & Social Sciences, Sultanpur (UP) for constant suggestions during the course of the study.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Tripathi, D.K. (2020). Soil Resource Inventory for Meeting Challenges of Land Degradation: A Remote Sensing Approach. In: Sahdev, S., Singh, R., Kumar, M. (eds) Geoecology of Landscape Dynamics. Advances in Geographical and Environmental Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-15-2097-6_7
Download citation
DOI: https://doi.org/10.1007/978-981-15-2097-6_7
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-2096-9
Online ISBN: 978-981-15-2097-6
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)