Loading...

Remote Sensing Applications in Mapping Salt Affected Soils

DOI: 10.18805/ag.R-2008    | Article Id: R-2008 | Page : 257-266
Citation :- Remote Sensing Applications in Mapping Salt Affected Soils.Agricultural Reviews.2021.(42):257-266
Nirmal Kumar, S.K. Singh, G.P. Obi Reddy, V.N. Mishra, R.K. Bajpai urwithnirmal@gmail.com
Address : Division of Remote Sensing Applications, ICAR-National Bureau of Soil Survey and Land Use Planning, Nagpur-440 033, Maharashtra, India.
Submitted Date : 23-04-2020
Accepted Date : 2-11-2020

Abstract

The aim of this review paper is to provide a comprehensive overview of remote sensing-based mapping of salt affected soils. By providing multispectral and multi-temporal low cost data at various resolutions, remote sensing plays an important role for identifying and mapping the distribution of salt affected soils. Different bands of the multispectral data and the indices and transforms derived from them have been found useful in delineating salt affected soils. The various approaches to map salt affected soils involving remote sensing data, from visual interpretation to supervised and unsupervised classifications have been discussed. Quantitative mapping of soil salinity with remote sensing and other environmental variables have also been discussed. 

Keywords

Remote sensing Salinity indicies Salt affected soils Visual interpretation

References

  1. Abbas, A. and Khan, S. (2007). Using remote sensing techniques for appraisal of irrigated soil salinity,” In: Oxley, L. and Kulasiri, D. (Eds.), Int. Congress on Modelling and Simulation (MODSIM), Modelling and Simulation Society of Australia and New Zealand, Brighton, :2632-2638.
  2. Abbas, A., Khan, S., Hussain, N., Hanjra, M.A. and Akbar, S. (2013). Characterizing soil salinity in irrigated agriculture using a remote sensing approach. Physics and Chemistry of the Earth. 55-57: 43-52.
  3. Abrol, I.P., Bronson, K., Duxbury, J.M. and Gupta, R.K. (2000). Long-Term fertility experiments in South Asia. Rice Wheat Consortium, Paper Series 6. RWC, New Delhi, p171.
  4. Afrasinei, G.M., Melis, M.T., Buttau, C., Bradd, J.M., Arras, C. and Ghiglieri, G. (2017). Assessment of remote sensing-based classification methods for change detection of salt-affected areas (Biskra area, Algeria). Journal of Applied Remote Sensing. 11: 1-28.
  5. Ajai, Arya, A.S., Dhinwa, P.S., Pathan, S.K. and Raj, K.G. (2009). Desertification and land degradation status mapping of India. Current Science. 97: 1478-1483.
  6. Aldakheel, Y.Y. (2011). Assessing NDVI Spatial pattern as related to irrigation and soil salinity management in Al-Hassa Oasis, Saudi Arabia. Journal of the Indian Society of Remote Sensing. 39: 171- 180.
  7. Allbed, A. and Kumar L. (2013). Soil salinity mapping and monitoring in arid and semi-arid regions using remote sensing technology: a Review. Advances in Remote Sensing. 2: 373-385.
  8. Asfaw, E., Suryabhagavan, K.V. and Argaw, M. (2018). Soil salinity modeling and mapping using remote sensing and GIS: The case of Wonji sugar cane irrigation farm, Ethiopia. Journal of Saudi Society of Agricultural Sciences. 17: 250-258.
  9. Azabdaftari, A. and Sunar, F. (2016). Soil salinity mapping using multitemporal Landsat data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B7, (2016). XXIII ISPRS Congress, 12-19 July 2016, Prague, Czech Republic.
  10. Bai, Z.G., Dent, D.L., Olsson, L. and Schaepman, M.E. (2008). Proxy global assessment of land degradation. Soil Use and Management. 24: 223-234.
  11. Bhargava, G.P. (1989). Salt-aff ected soils of India. Oxford and IBH Publication, New Delhi, India.
  12. Bhumbla, D.R. and A. Khare. (1984). Estimates of wastelands in India. Society for Promotion of Wastelands Development (SPWD), New Delhi, India.
  13. Bridges, E.M. and Oldeman, L.R. (1999). Global assessment of human-induced soil degradation. Arid Soil Research and Rehabilitation. 13: 319­ 325.
  14. Cai, S., Zhang, R., Liu, L. and Zhou, De. (2010). A method of salt-affected soil information extraction based on a support vector machine with texture features. Mathematical and Computer Modelling. 51: 1319-1325.
  15. Chauhan, H.S. (1996). Management of problem area in irrigation commands through conjunctive use and other methods. In Proc. National Workshop Reclamation of Waterlogged Saline and Alkali Lands and Prevention, New Delhi. Ministry Water Resources, New Delhi, India. p. 79-86.
  16. Chen, S. and Rao, P. (2008). Land degradation monitoring using multi-temporal Landsat TM/ETM data in a transition zone between grassland and cropland of northeast China. International Journal of Remote Sensing. 29: 2055-2073.
  17. Csillag, F., Pasztor, L. and Biehl, L.L. (1993). Spectral band selection for the characterization of salinity status of soils. Remote Sensing of Environment. 43: 231-242.
  18. CSSRI. (1971). Annual Report 1971, ICAR-Central Soil Salinity Research Institute, Karnal, Haryana, India. http://krishikosh.    egranth.ac.in.
  19. Dehni, A. and Lounis, M. (2012). Remote Sensing techniques for salt affected soil mapping: application to the Oran region of Algeria. Procedia Engineering. 33: 188-198
  20. Dent, F.J., Y.S. Rao and K. Takeuchi. (1992). Regional strategies for arresting land degradation (Womb of the Earth). FAO/RAPA, Bangkok, Thailand.
  21. Ding, J., Wu, M. and Tiyip, T. (2011). Study on soil salinization information in arid region using remote sensing technique. Agricultural Sciences in China. 10: 404-411
  22. Dogan, H.M. and Kilic, O.M. (2013). Modelling and mapping some soil surface properties of Central Kelkit Basin in Turkey by using Landsat-7 ETM+ images. International Journal of Remote Sensing. 34: 5623-5640.
  23. Douaoui, A.E.K., Nicolas, H. and Walter, C. (2006). Detecting salinity hazards within a semiarid context by means of combining soil and remote-sensing data. Geoderma. 134: 217-230.
  24. Dwivedi, R.S. (1994). Study of salinity and waterlogging in Uttar Pradesh (India) using remote sensing data, Land Degradation and Rehabilitation. 5: 191-199.
  25. Dwivedi, R.S. (1996). Monitoring of salt-affected soils of the Indo-Gangetic alluvial plains using principal component analysis. International Journal of Remote Sensing. 17: 1907-1914.
  26. Dwivedi, R.S. (2001). Soil Resources Mapping: A Remote Sensing Perspective, Remote Sensing Reviews. 20: 89-122.
  27. Dwivedi, R.S. and Rao, B.R.M. (1992). The selection of the best possible Landsat-TM band combinations for delineating salt-affected soils. International Journal of Remote Sensing. 13: 2051-2058.
  28. Dwivedi, R.S. and Sreenivas, K. (1998a). Image transforms as a tool for the study of soil salinity and alkalinity dynamics. International Journal of Remote Sensing. 19: 605- 619.
  29. Dwivedi, R.S. and Sreenivas, K. (1998b). Delineation of salt-affected soils and waterlogged areas in the Indo-Gangetic plains using IRS-1C LISS-111 data. International Journal of Remote Sensing. 19: 2739-2751.
  30. Dwivedi, R.S., Ramana, K.V., Thammappa, S.S. and Singh A.N. (2001). The Utility of IRS-1C LISS-Ill and PAN-Merged Data for Mapping Salt-Affected Soils. Photogrammetric Engineering and Remote Sensing. 67: 1167-1175.
  31. Dwivedi, R.S., Sreenivas, K. and Ramana, K.V. (1999). Inventory of salt-affected soils and waterlogged areas: a remote sensing approach. International Journal of Remote Sensing. 20: 1589-1599.
  32. Dwivedi, RS. (1992). Monitoring and the study of the effects of image scale on delineation of salt-affected soils in the Indo-Gangetic plains. International Journal of Remote Sensing. 13: 1527-1536.
  33. Elhag, M. (2016). Evaluation of different soil salinity mapping using remote sensing techniques in arid ecosystems, Saudi Arabia. Journal of Sensors. 2016, p8. doi.org/10.1155/2016/7596175.
  34. Elnaggar, A.A. and Noller, J.S. (2009). Application of remote- sensing data and decision-tree analysis to mapping salt- affected soils over large areas. Remote Sensing. 2: 151-165. 
  35. Ferna´ndez-Buces, N., Siebe, C., Cram, S. and Palacio, J.L. (2006). Mapping soil salinity using a combined spectral response index for bare soil and vegetation: A case study in the former lake Texcoco, Mexico. Journal of Arid Environments. 65: 644-667.
  36. Flowers, T.J. (1999). Salinization and horticultural production. Scientia Hortic. 78: 1-4.
  37. Friedl, M.A. and Brodley, C.E. (1997). Decision tree classification of land cover from remotely sensed data. Remote Sensing of the Environment. 61: 399-409.
  38. Friedl, M.A., Brodley, C.E., and Strahler, A.H. (1999). Maximizing land cover classification accuracies produced by decision trees at continental to global scales. IEEE Transactions on Geoscience and Remote Sensing. 37:969-977.
  39. Gao, J. (2008). Detection of changes in land degradation in northeast china from Landsat TM and ASTER data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 37: 1533-1538.
  40. Ghassemi, F., Jakeman, A.J. and H.A. Nix. (1995). Salinization of land and water resources: Human causes, extent, management and case studies. CAB International, Wallingford, UK.
  41. Goosen, D. (1967). Aerial photo-interpretation in soil surveys. Soils Bull. 6. F.A.O., Rome.
  42. Gutierrez, C. (2002). A comparison of false color composites in mapping and discriminating between salt-affected soils in Kings county, California. Masters thesis. Oregon State University. p 42.
  43. Hansen, M., Dubayah, R. and Defries, R. (1996). Decision trees: an alternative to traditional land cover classifiers. International Journal of Remote Sensing. 17: 1075-1081.
  44. Harti, A.E., Lhissou, R., Chokmani, K., Ouzemou, J., Hassouna, M., Bachaoui, E.M. and Ghmari, A.E. (2016). Spatiotemporal monitoring of soil salinization in irrigated Tadla Plain (Morocco) using satellite spectral indices. International Journal of Applied Earth Observation and Geoinformation. 50: 64-73.
  45. Huang, C., Davis, L.S. and Townshend, J.R.G. (2002). An assessment of support vector machines for land cover classification. Int. J. of Remote Sensing. 23: 725-749.
  46. Huete, A. (1988). A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment. 25: 295-309.
  47. Huete, A.J. (1999). Modis Vegetation Index (MOD13) Algorithm Theoretical Basis Document. Version 3.
  48. IDNP. (2002). Indo-Dutch Network Project: A methodology for identification of water-logging and soil salinity conditions using remote sensing. Central Soil Salinity Research Institute, Karnal, p 78.
  49. Kalra, N.K. and Joshi, D.C. (1996). Potentiality of Landsat, SPOT and IRS satellite imagery, for recognition of salt affected soils in Indian Arid Zone, International Journal of Remote Sensing. 17: 3001-3014.
  50. Kauth, R.J. and Thomas, G.S. (1976). The Tasselled Cap - A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat. LARS Symposia. Paper 159.
  51. Kertesz, M. and Toth, T. (1994). Soil survey based on sampling scheme adjusted to local hydrology. Agrokemia Es Talajtan Tom. 43: 113-132.
  52. Khan, N.M., Rastoskuev, V.V., Sato, Y. and Shiozawa, S. (2005). Assessment of hydrosaline land degradation by using a simple approach of remote sensing indicators. Agricultural Water Management. 77: 96-109. 
  53. Kumar, N. (2018). Study on identification, characterization and mapping of degraded lands using time series MODIS NDVI and LANDSAT data. A dissertation for doctoral degree award in Indira Gandhi Krishi Vishvavidyala Raipur, P.256.
  54. Kumar, N. and Singh, S.K. (2018). Land degradation assessment using MODIS NDVI time series data. In: Singh, S.K., Chatterji, S., Chattaraj, S., Butte, P.S. and Sharma, R.P. (eds) ICAR-NBSS and LUP Technologies, NBSSLUP Publ No. 176, ICAR-NBSS and LUP, Nagpur. p. 102.
  55. Kumar, N., Singh, S.K., Mishra, V.N., Reddy, G.P.O. and Bajpai, R.K. (2018). Open-Source Satellite Data and GIS for Land Resource Mapping. In: Reddy G.P.O., Singh S.K. (eds) Geospatial Technologies in Land Resources Mapping, Monitoring and Management. Geotechnologies and the Environment, vol 21. Springer, Cham.
  56. Kumar, N., Singh, S.K., Reddy, G.P.O., Mishra, V.N. and Bajpai, R.K. (2020). Remote sensing and geographic information system in water erosion assessment. Agricultural Reviews. 41: 116-123.
  57. Kumar, N., Singh, S.K., Reddy, G.P.O. and Naitam, R.K. (2019). Developing logistic regression models to identify salt-affected soils using optical remote sensing. In: Mukherjee, A.B. and Krishna, A.P. (eds) Interdisciplinary Approaches to Information Systems and Software Engineering. IGI Global, USA.
  58. Kumar, U., Mishra, V.N., Kumar, N. and Rathiya, G.R. (2018). Methods of soil analysis. Kalyani Publishers, Ludhiana, pp-172.
  59. Lobell, D.B., Leschb, S.M., Corwinc, D.L., Ulmerd, M.G., Andersone, K.A., Pottsf, D.J., Doolittleg, J.A., Matosh M.R. and Baltes, M.J. (2010). Regional-scale assessment of soil salinity in the Red River valley using multi-year MODIS EVI and NDVI. Journal of Environmental Quality. 39: 35-41. 
  60. Lynden, G.W.J. and Oldeman, L.R. (1997). Soil degradation in South and Southeast Asia. United Nations Environment Programme (UNEP), Food and Agriculture Organisation of the United Nations (FAO), International Soil Reference and Information Centre (ISRIC), Wageningen. Netherlands.
  61. Maji, A.K., Reddy, G.P.O. and Sarkar, D. (2010). Degraded and wastelands of India, status and spatial distribution. Indian Council of Agricultural Research and National Academy of Agricultural Science, New Delhi, 158 p. 
  62. Major, D., Baret, F. and Guyot, G. (1990). A Ratio vegetation index adjusted for soil brightness. International Journal of Remote Sensing. 11: 727-740. 
  63. Mandal, A.K. and Sharma, R.C. (2001). Mapping of waterlogged and salt affected soils in the IGNP command area. Journal of the Indian Society of Remote Sensing. 29: 229-235.
  64. Mandal, A.K. and Sharma, R.C. (2008). Computerized database of salt affected soils in the Western and Central India using GIS. Geocarto International. 23: 373-391.
  65. Mandal, A.K. and Sharma, R.C. (2011). Delineation and characterization of waterlogged salt affected soils in IGNP using remote sensing and GIS. Journal of Indian Society of Remote Sensing. 39: 39-50.
  66. Mandal, A.K. Sharma, R.C. and Singh G. (2009). Assessment of salt affected soils in India using GIS. Geocarto International. 24: 437-456.
  67. Massoud, F.I. (1974). Salinity and alkalinity as soil degradation hazards. FAO/ UNDP Expert Consultation on Soil Degradation, FAO, Rome, Italy.
  68. Massoud, F.I. (1981). Salt affected soils at a global scale for control. FAO Land and Water Development Division Technical Paper, Rome, Italy, 21 pp.
  69. Massoud, F.I. and Koike, K. (2006). Arid land salinization detected by remotely sensed landcover changes: A case study in the Siwa region, NW Egypt. Journal of Arid Environments. 66: 151-167.
  70. Mehrjardi, R.T., Mahmoodi, S., Taze, M. and Sahebjalal, E. (2008). Accuracy Assessment of Soil Salinity Map in Yazd-Ardakan Plain, Central Iran, Based on Landsat ETM+ Imagery, American-Eurasian Journal of Agriculture and Environment Science. 3(5): 708-712.
  71. Metternicht, G.I. and Zinck, J.A. (1996). Modelling salinity–alkalinity classes for mapping salt-affected topsoils in the semiarid valleys of Cochabamba (Bolivia). ITC J. 1996: 125-135.
  72. Ministry of Agriculture. (1980). Status of land degradation in India. Directorate of Economics and Statistics. Ministry of Agriculture. New Delhi, India.
  73. Ministry of Agriculture. (1985). Status of land degradation in India. Directorate of Economics and Statistics. Ministry of Agriculture. New Delhi, India.
  74. Ministry of Agriculture. (1990). Status of land degradation in India. Directorate of Economics and Statistics. Ministry of Agriculture. New Delhi, India.
  75. Ministry of Agriculture. (1995). Status of land degradation in India. Directoratenof Economics and Statistics. Ministry of Agriculture. New Delhi, India.
  76. Mitchell, D.E. (2014). Dentifying salinization through multispectral band analysis: lake Urmia, Iran, Masters thesis, Ryerson University, Toronto, Ontario, Canada. p 58.
  77. MoA (2000). Status of land degradation in India. Directoraten of Economics and Statistics. Ministry of Agriculture. New Delhi, India.
  78. Narayan, L.R.A., Rao, D.P. and Gautam, N.C., (1989). Wasteland identification in India using satellite remote sensing. International Journal of Remote Sensing. 10: 93-106.
  79. Naseri, M.Y. (1998). Characterization of salt-affected soils for modeling sustainable land management in semi-arid environment: a case study in the Gorgan region, Northeast Iran. PhD thesis, Ghent University, Belgium.
  80. NCA. (1976). Report of the National Commission on Agriculture: Part V, IX and Abridged. Ministry of Agriculture and Irrigation, New Delhi.
  81. NRSA (2000). Wasteland Atlas of India.Ministry of Rural Development and NRSC Publ., NRSC, Hyderabad.
  82. NRSA, (1997). Salt-Affected Soils of India. National Remote Sensing Agency, Hyderabad.
  83. NRSC (2005). Wasteland Atlas of India.Ministry of Rural Development and NRSC Publ., NRSC, Hyderabad.
  84. NRSC, (2011). Wasteland Atlas of India.Ministry of Rural Development and NRSC Publ., NRSC, Hyderabad.
  85. NRSC, (2012). Land Degradation Atlas of India. NRSC Publ., NRSC, Hyderabad.
  86. Oldeman, L.R., Hakkeling, R.T.A. and Sombroek, W.G. (1991). World map of the status of human-induced soil degradation: An explanatory note, second revised edition ISRIC, Wageningen.
  87. Oldeman, L.R., Hakkeling, R.U. and Sombroek, W.G. (1990). World map of the status of human-induced soil degradation: An explanatory note. Wageningen: International Soil Reference and Information Centre.
  88. Pal, M. and Mather, P.M. (2003). An assessment of the effectiveness of decision tree methods for land cover classification. Remote Sensing of Environment. 86: 554-565. 
  89. Pattanaaik, S.K., Singh, O.P., Sahoo, R.N. and Singh, D.K. (2008). Irrigation induced soil salinity mapping through principal component analysis of remote sensing data. Journal of Agricultural Physics. 8: 29-36
  90. Patterson, M.W. and Stephen, R.Y. (1998). Mapping fire-induced vegetation mortality using Landsat Thematic Mapper data: a comparison of linear transformation techniques. Remote Sensing of Environment. 65: 132-142.
  91. Peng, W. (1998). Synthetic Analysis for Extracting Information on Soil Salinity Using Remote Sensing and GIS: A Case Study of Yanggao Basin in China. Environmental Management. 22: 153-159.
  92. Phua, M. and Saito, H. (2003). Estimating of biomass of a mountainous tropical forest using Landsat TM data. Canadian Journal of Remote Sensing. 29: 429-440.
  93. Ponnamperuma, F.N. and Bandhopadhyay, A.K. (1980). Soil salinity as a constraint on food production in the humid tropics. In Priorities for alleviating soil reated constraints to food production in the tropics, IRRI, Los Banos, Philippines. 
  94. Quinlan, J.R. (1993). C4.5: Programs for machine learning, San Mateo, California: Morgan Kauffmann Publishers.
  95. Rao, B.R.M. and Venkataratnam, L. (1991). Monitoring of salt-    affected soils-A case study using aerial photographs, Salut-7 space photographs and Landsat-TM data, Geocarto International, 1: 5-11.
  96. Rao, P., Chen, S. and Sun, K. (2006). Improved classification of soil salinity by decision tree on remotely sensed images. Proceedings of SPIE-Int. Society for Optical Engineering, 6027, 20th Congress of the International Commission for Optics.
  97. Raychaudhuri, S.P. (1966). Land and soil. National Book Trust, New Delhi, India.
  98. Reddy, G.P.O., Kumar, N. and Singh, S.K. (2018). Remote sensing and GIS in mapping and monitoring of land degradation. In: Reddy G.P.O., Singh S. K. (eds) Geospatial Technologies in Land Resources Mapping, Monitoring and Management. Geotechnologies and the Environment, vol 21. Springer, Cham.
  99. Rouse, J.W., Haas, R.H., Schell, J.A. and Deering, D.W. (1974). Monitoring vegetation systems in the Great Plains with ERTS. In: Fraden S.C., Marcanti, E.P. and Becker, M.A. (eds.), Third ERTS-1 Symposium, 10–14 Dec. 1973, NASA SP-351, Washington D.C. NASA, p. 309–317.
  100. Rowan, L.C., Goetz, A.F.H. and Ashley, R.P. (1977). Discrimination of hydrothermally altered and unaltered rocks in the visible and near infrared multispectral images. Geophysics. 42: 522-535. 
  101. SAC (2005). Desertification & Land Degradation Atlas of India. Space Applications Centre, Ahmedabad.
  102. SAC, (2007). Desertification & Land Degradation Atlas of India. Space Applications Centre, Ahmedabad.
  103. SAC, (2016). Desertification and Land Degradation Atlas of India (Based on IRS AWiFS data of 2011-13 and 2003-05), Space Applications Centre, ISRO, Ahmedabad, India, 219pages.
  104. Saha, S.K., Kudrat, M. and Bhan, S.K. (1990). Digital processing of Landsat TM data for wasteland mapping in parts of Aligarh District, Uttar Pradesh, India. International Journal of Remote Sensing.11: 485-492.
  105. Sahu, N., Reddy, G.P.O., Kumar, N. and Nagaraju, M.S.S. (2015). High resolution remote sensing, GPS and GIS in soil resource mapping and characterization. Agricultural Reviews. 36: 14-25. 
  106. Scudiero, E., Skaggs, T.H. and Corwin, D.L. (2014). Regional scale soil salinity evaluation using Landsat 7, western SanJoaquin Valley, California, USA, Geoderma Regional. 2-3: 82-90
  107. Scudiero, E., Skaggs, T.H. and Corwin, D.L. (2014). Regional-scale soil salinity assessment using Landsat ETM+ canopy reflectance, Remote Sensing of Environment. 169: 335-343.
  108. Sehgal, J.L. and Abrol, I.P. (1994). Soil degradation in India: Status and impact with a coloured map on 1:5 M scale. Oxford and IBH Publishing Co. Pvt. Ltd., New Delhi: 1-80.
  109. Sethi, M., Dasog, G.S., Van Lieshoutc, A. and Salimathd, S.B. (2006). Salinity appraisal using IRS images in Shorapur taluka, Upper Krishna Irrigation Project, Phase I, Gulbarga District, Karnataka, India. International Journal of Remote Sensing. 27: 2917-2926. 
  110. Shahid, S.A. (2013). Irrigation induced soil salinity under different irrigation systems- Assessment and management: Short technical note, Climate Change Outlook and Adaptation. 1: 19-24.
  111. Sharma, P.K., Sehgal, J.L. and Sharma, K.R. (1976). Mapping salt-    affected soils in Sangrur district (Punjab) using aerial photo-interpretation technique, Journal of Indian Society of Remote Sensing. 1-2: 43-54.
  112. Sharma, R.C. and Bhargava, G.P. (1988). Landsat imagery for mapping saline soils and wet lands in north-west India. International Journal of Remote Sensing. 9: 39-44.
  113. Sharma, R.C., Mandal, A.K. and Singh, R. (2011). Delineation and characterization of waterlogged and salt-affected soils in Gandak Command Area of Bihar for reclamation and management. Journal of the Indian Society of Soil Science. 59: 315-320.
  114. Sharma, R.C., Mandal, A.K., Saxena, R.K. and Verma, K.S. (2004). Characteristics, formation and reclamability of sodic soils under different geomorphic plains of Ganga basin. Proceedings of the International Conference on Sustainable Management of Sodic Lands. Feb 9-14, 2004, Lucknow, India, pp. 168-169.
  115. Sharma,R.C., Saxena, R.K. and Verma, K.S. (2000). Reconnaissance mapping and management of salt affected soils using satellite images. International Journal of Remote Sensing. 21: 3209-3218.
  116. Shreshtha, R.P. (2006). Relating soil electrical conductivity to remote sensing and other soil properties for assessing soil salinity in Northeast Thailand. Land Degradation and Development. 17: 777-689.
  117. Singh, A.K., Singh, P.K., Lal, B., Singh, A.N. and Mathur, A. (2008). Distribution analysis of salt affected soils under canal and non-canal command area in a part of Etah District, U. P., using Remote Sensing Technique. Journal of Indian Society of Remote Sensing. 36: 183-188.
  118. Singh, A.N. and Dwivedi, R.S. (1989). Delineation of Salt-affected Soils through Digital Analysis of Landsat MSS Data. International Journal of Remote Sensing. 10: 83-92.
  119. Singh, N.T. and A.K. Bandyopadhya. (1996). Chemical degradation leading to salt-affected soils and their management for agriculture and alternate uses. p. 89–101. In T.D Biswas and G. Narayanasamy (ed.) Soil management in relation to land degradation and environment. Indian Society of Soil Science Bulletin. 17, New Delhi, India.
  120. Sujatha, G. Dwivedi, R.S., Sreenivas, K., and Venkataratnam, L. (2000). Mapping and monitoring of degraded lands in part of Jaunpur district of Uttar Pradesh using temporal spaceborne multispectral data. International Journal of Remote Sensing. 21: 519-531.
  121. Szabolcs, I., (1992), Salinization of soil and water and its relation to desertification. Desertification Control Bulletin. No. 21, pp. 32-37.
  122. Tajgardan, T., Shataee, S. and Ayoubi, S., (2007). In spatial prediction of soil salinity in the arid zones using ASTER data, case study: north of Ag Ghala, Golestan Province, Iran. In: Proceedings of Asian Conference on Remote Sensing (ACRS), Kuala Lumpur, Malaysia.
  123. Toomey, M. and Vierling, LA. (2005). Multispectral remote sensing of landscape level foliar moisture: Techniques and applications for forest ecosystem monitoring. Canadian Journal of Forest Research. 35: 1087-1097.
  124. Tripathi, N.K., Rai, B.K. and Dwivedi, P. (1997). Proceedings. In, 18th Asian Conference in Remote Sensing (pp. A-8-1-A-8-6). Kuala Lumpur, Malaysia.
  125. Venables, W.N. and Ripley, B.D. (1994). Modern Applied Statistics with S-PLUS; Springer-Verlag: New York, NY, USA.
  126. Verma, K., Saxena, R.K., Barthwal, A.K. and Deshmukh, S.N. (1994) Remote Sensing Technique for Mapping Salt Affected Soils. International Journal of Remote Sensing. 15: 1901-1914.
  127. Wang, J., Ding, J., Yu, D., Ma, X., Zhang, Z., Ge, X., Teng, D., Li, X., Liang, J., Lizaga, I., Chen, X. and Yuan, L. (2019). Capability of Sentinel-2 MSI data for monitoring and mapping of soil salinity in dry and wet seasons in the Ebinur Lake region, Xinjiang, China, Geoderma. 353: 172-187.
  128. Wu, J., Vincent, B., Yang, J., Bouarfa, S. and Vidal, A. (2008). Remote Sensing Monitoring of Changes in Soil Salinity: A Case Study in Inner Mongolia, China. Sensors. 8: 7035-7049.
  129. Wu, W., Mhaimeed, A.S., Al-Shafie, W.M., Ziadat, F., Dhehibi, B., Nangia, V. and De Pauw, E. (2014). Mapping soil salinity changes using remote sensing in Central Iraq. Geoderma Regional. 2-3: 21-31.

Global Footprints