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Remote Sensing and GIS in Mapping and Monitoring of Land Degradation

  • G. P. Obi Reddy
  • Nirmal Kumar
  • S. K. Singh
Chapter
Part of the Geotechnologies and the Environment book series (GEOTECH, volume 21)

Abstract

The information on the extent and spatial distribution of various kinds of degraded lands is essential for strategic planning and development of degraded lands. Processes of land degradation can be broadly grouped into physical, chemical, and vegetal (biological) degradation. The physical processes include land degradation mainly due to water and wind erosion, compaction, crusting, and waterlogging. The chemical process includes salinization, alkalization, acidification, pollution, and nutrient depletion. The vegetal or biological processes on the other hand are reduction of organic matter content in the soils and degradation of vegetation. The use of remote sensing and geographic information system (GIS) techniques makes land degradation estimation and its spatial distribution feasible with reasonable costs and better accuracy in larger areas. The use of spaceborne multispectral data shown its potential in deriving information on the nature, extent, spatial distribution, and magnitude of various kinds of degraded lands. Assessment and monitoring of land degradation through remote sensing offer a series of advantages such as consistency of data, fairly near real-time reporting, and a source for having spatially explicit data. The integration of high-resolution remote sensing data and digital elevation models derived from satellites data like Cartosat-1 and Cartosat-2 and Light Detection and Ranging (LiDAR) with ground data has immense potential in assessment and monitoring of land degradation in local scales. In this chapter, application of remote sensing and GIS in assessment and mapping of physical, chemical, and vegetal degradation has been discussed. The study indicates that integrated remote sensing and GIS applications have immense potential in assessment, mapping and monitoring of land degradation with reasonable cost and better accuracy in larger areas that would otherwise require large inputs of human and material resources.

Keywords

Remote sensing Geographic information system Land degradation Physical degradation Chemical degradation Vegetal degradation 

References

  1. Abrol IP (1990) Problem soils in India. In: Problem soils of Asia and the Pacific. FAO/RAPA, Bangkok, pp 153–165Google Scholar
  2. Ahmad M, Kutcher GP (1992) Irrigation planning with environmental considerations: a case study of Pakistan’s Indus basin. World Bank Technical Paper 166. World Bank, Washington DC, 196 ppGoogle Scholar
  3. Ajai RR, Arya AS, Dhinwa PS et al (2007) Desertification/land degradation atlas of India. Space Applications Centre, Ahmedabad. ISBN No. 978-81-909978-2-9Google Scholar
  4. Ajai RR, Arya AS, Dhinwa PS, Pathan SK, Ganeshraj K (2009) Desertification/land degradation status mapping of India. Curr Sci 97(10):1478–1483Google Scholar
  5. Al Mahawili SMH (1983) Satellite interpretation and laboratory spectral reflectance measurements of saline and gypsiferous soils of West Baghdad, Iraq. M.S. Thesis, Purdue University, West Lafayatte, Indian, USAGoogle Scholar
  6. Anonymous (1976) Report of National Commission on Agriculture, part V, IX and abridged report, Ministry of Agriculture and Irrigation, Govt. of India, New DelhiGoogle Scholar
  7. Bai ZG, Dent DL, Olsson L, Schaepman ME (2008) Proxy global assessment of land degradation. Soil Use Manag 24:223–234CrossRefGoogle Scholar
  8. Bali JS (1985) Problems of gullied and ravinous area -Policy, programmes and progress. In: Proceedings national seminar on soil conservation and watershed management, New Delhi, 17–18 September 1985Google Scholar
  9. Bangladesh (1992) Land degradation. Paper presented to FAO 21st regional conference for Asia and the Pacific, New DelhiGoogle Scholar
  10. Barrett EC, Curtis LF (1976) Introduction to environmental remote sensing. Chapman and Hall, London, p 336Google Scholar
  11. Bartsch KP, van Miegroet H, Boettinger J, Dobrwolski JP (2002) Using empirical erosion models and GIS to determine erosion risk at Camp Williams. J Soil Water Conserv 57:29–37Google Scholar
  12. Beasley DB, Huggins LF, Monke EJ (1980) ANSWERS: a model for watershed planning. Trans Am Soc Agric Eng 23(4):938–944CrossRefGoogle Scholar
  13. Biswas A, Tewatia RK (1991) Nutrient balance in agro-climatic regions of India – an overview. Fert News 36(6):13–18Google Scholar
  14. Blanco PD, Metternicht GI, del Valle HF (2009) Improving the discrimination of vegetation and landforms patterns in sandy rangelands: a synergistic approach. Int J Remote Sens 30:2579–2605CrossRefGoogle Scholar
  15. Bowonder B (1981) The myth and reality of high yield varieties in Indian agriculture. Dev Chang 12(2):293–313CrossRefGoogle Scholar
  16. Bridges EM, Oldeman LR (1999) Global assessment of human-induced soil degradation. J Arid Soil and Rehabil 13(4):319–325CrossRefGoogle Scholar
  17. Carneiro FA, Zinck JA (1994) Mapping paleo-aeolian sand cover formations in the northern Amazon basin from TM images. ITC J 3:270–282Google Scholar
  18. Chaudhary MK, Aneja DR (1991) Impact of green revolution on long-term sustainability of land and water resources in Haryana. Indian J Agric Econ 45:428–432Google Scholar
  19. Chen Z, Elvidge CD, Groenveld DP (1998) Monitoring of seasonal dynamics of arid land vegetation using AVIRIS data. Remote Sens Environ 65:255–266CrossRefGoogle Scholar
  20. Choubey VK (1997) Detection and delineation of waterlogging by remote sensing techniques. J Indian Soc Remote Sens 25(2):123–135CrossRefGoogle Scholar
  21. Choubey VK (1998) Assessment of waterlogging in Sriram Sagar command area, India, by remote sensing. Water Resour Manag 12(5):343–357CrossRefGoogle Scholar
  22. Collado AD (2000) Spatio-temporal dynamics of dune patterns in semiarid Argentina: a neural network analysis. Edaphomatics Bull. no. 20. AICET-INTA, Buenos Aires, ArgentinaGoogle Scholar
  23. CSSRI (2007) Annual report 2006–07. Central Soil Salinity Research Institute, Karnal, IndiaGoogle Scholar
  24. Das DC (1985) Problem of soil erosion and land degradation in India. Proceedings of the national seminar on the soil conservation and watershed management held on 17–18 September New DelhiGoogle Scholar
  25. De Ploey J (1989) A soil erosion map for Western Europe. Catena VerlagGoogle Scholar
  26. del Valle HF, Rostagno CM, Coronato FR, Bouza PJ, Blanco PD (2008) Sand dune activity in north-eastern Patagonia. J Arid Environ 72:411–422CrossRefGoogle Scholar
  27. Dhar BB, Jamal A, Ratan S (1991) Air pollution problem in an Indian open cast coal mining complex: a case study. Int J Surf Min Reclam Environ 5(2):83–88CrossRefGoogle Scholar
  28. Dhuruvanarayana VV, Ram Babu NP (1983) Estimation of soil erosion in India. J Irrig Drain Eng 109:419–434CrossRefGoogle Scholar
  29. Dregne HE, Chou NT (1994) Global desertification dimensions and costs. In: Dregne HE (ed) Degradation and restoration of arid lands. Texas Technical University, LubbockGoogle Scholar
  30. Dwivedi R (1992) Monitoring and the study of the effects of image scale on delineation of salt-affected soils in the Indo-Gangetic plains. Int J Remote Sens 13(8):1527–1536CrossRefGoogle Scholar
  31. Dwivedi RS, Sreenivas K (1998) Delineation of salt-affected soils and waterlogged areas in the indo-Gangetic plains using IRS-1C LISS-III data. Int J Remote Sens 19:2739–2751CrossRefGoogle Scholar
  32. Dwivedi RS, Kumar AB, Tewari AN (1997a) The utility of multi-sensor data for mapping eroded lands. Int J Remote Sens 18:2303–2318CrossRefGoogle Scholar
  33. Dwivedi RS, Ravi Sankar T, Venkataratnam L, Karale RL, Gawande SP, Rao KVS, Senchuandhary S, Bhaumik KR, Mukherjee KK (1997b) The inventory and monitoring of eroded lands using remote sensing data. Int J Remote Sens 18:107–119CrossRefGoogle Scholar
  34. Dwivedi RS, Kothapalli RV, Singh AN (2008) Generation of farm-level information on salt-affected soils using IKONOS-II multispectral data. In: Metternicht G, Zinck J (eds) Remote sensing of soil salinization: impact on land management. CRC Press, Boca RatonGoogle Scholar
  35. Eswaran H, Lal R, Reich PF (2001) Land degradation: an overview. In: Bridges EM, Hannam ID, Oldeman LR, Pening de Vries FWT, Scherr SJ, Sompatpanit S (eds) Responses to land degradation. Proceedings of. 2nd international conference on land degradation and desertification, Khon Kaen, Thailand. Oxford Press, New DelhiGoogle Scholar
  36. FAO (1986) Status report on plant nutrition in fertilizer programmes countries in Asia and Pacific region. AGL/MISC/86/7. FAO, RomeGoogle Scholar
  37. FAO (2008a) Land degradation on the rise – one fourth of the world’s population affected says new study. Report by Food and Agricultural Organization. http://www.fao.org/newsroom/en/news/2008/1000874/index.html
  38. FAO (2008b) LADA project documents FAO, internet website: http://www.fao.org/ ag/agl/agll/lada/ladaprojectdoc.pdf. Accessed 10 July 2017
  39. FAO/RAPA (1992) Environmental issues in land and water development. FAO/RAPA, Bangkok. 488 pp (Includes country papers on Bangladesh, India, Nepal, Pakistan and Sri Lanka)Google Scholar
  40. Fernandez C, Wu JQ, McCool DK, Stockle CO (2003) Estimating water erosion and sediment yield with GIS, RUSLE, and SEDD. J Soil Water Conserv 58:128–136Google Scholar
  41. Franke J, Navratil P, Keuck V, Peterson K, Siegert F (2012) Monitoring fire and selective logging activities in tropical peat swamp forests. IEEE J Select Top Appl Earth Observ Remote Sens 5(6):1811–1820CrossRefGoogle Scholar
  42. Fu BJ, Zhao WW, Chen LD, Zhang QJ, Lu YH, Gulinck H, Poesen J (2005) Assessment of soil erosion at large watershed scale using RUSLE and GIS: a case study in the loess plateau of China. Land Degrad Dev 16:73–85CrossRefGoogle Scholar
  43. Gautam NC, Narayan LRA (1988) Wastelands in India. Pink Publishing House, Mathura, p 96Google Scholar
  44. Gautam AP, Webb EL, Shivakoti GP, Zoebisch MA (2003) Land use dynamics and landscape change pattern in a mountain watershed in Nepal. Agric Ecosyst Environ 99:83–96CrossRefGoogle Scholar
  45. Ghassemi F, Jakeman AJ, Nix HA (1995) Salinisation of land and water resources: human causes, extent, management and case studies. CABI, WallingfordGoogle Scholar
  46. Goossens R, Van Ranst E (1996) The use of remote sensing and GIS to detect gypsiferous soils in the Ismailia Province (Egypt). In the international conference on soils with gypsum, Lleida, Spain, 15–21. Accessed 15 Oct 2017Google Scholar
  47. Goossens R, Van Ranst E (1998) The use of remote sensing to map gypsiferous soils in the Ismailia Province (Egypt). Geoderma 87(1–2):47–56CrossRefGoogle Scholar
  48. Gupta SK, Ahmed H, Hussain M, Pandey AS, Singh S, Saini KM, Das SN (1998) Inventory of degraded lands of Palamau district, Bihar: a remote sensing approach. J Indian Soc Remote Sens 26:161–168CrossRefGoogle Scholar
  49. Hillel D (2000) Salinity management for sustainable irrigation: integrating science, environment, and economics. World Bank Publications, Washington, DCCrossRefGoogle Scholar
  50. Hirschmugl M, Steinegger M, Gallaun H, Schardt M (2014) Mapping forest degradation due to selective logging by means of time series analysis: case studies in central Africa. Remote Sens 6:756–775CrossRefGoogle Scholar
  51. IPCC (2014) Synthesis report. Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change [Core Writing Team, Pachauri RK, Meyer LA (eds)]. IPCC, Geneva, Switzerland, 151 ppGoogle Scholar
  52. Jafari R, Lewis MM, Ostendorf B (2008) An image-based diversity for assessing land degradation in an arid environment in South Australia. J Arid Environ 72:1282–1293CrossRefGoogle Scholar
  53. Jha CS, Dutt CBS, Bawa KS (2000) Deforestation and land use changes in Western Ghats, India. Curr Sci 79:231–238Google Scholar
  54. Johnston RM, Barson MM (1993) Remote sensing of Australian wetlands: an evaluation of Landsat TM data for inventory and classification. Mar Freshw Res 44(2):235–252CrossRefGoogle Scholar
  55. Joshi MD, Sahai B (1993) Mapping of salt-affected land in Saurashtra coast using Landsat satellite data. Int J Remote Sens 14(10):1919–1929CrossRefGoogle Scholar
  56. Joshi PK, Tyagi NK (1991a) Sustainability of existing farming system in Punjab and Haryana – some issues in groundwater use. Indian J Agric Econ 46(3):412–421Google Scholar
  57. Joshi PK, Tyagi NK (1991b) Sustainability of existing farming system in Punjab and Haryana some issues on groundwater use. Indian J Agric Econ 46:412–421Google Scholar
  58. Kapalanga TS (2008) A review of land degradation assessment methods. Land restoration training programme Keldnaholt, 112 Reykjavík, Iceland, pp 17–68Google Scholar
  59. Karale RL, Saini KM, Narula KK (1987) Mapping and monitoring ravines using remotely sensed data. J Soil Water Conserv (India) 32(1–2):75–82Google Scholar
  60. Kessler CA, Stroosnijder L (2006) Land degradation assessment by farmers in Bolivian mountain valleys. Land Degrad Dev 17:235–248CrossRefGoogle Scholar
  61. Khan NM, Rastoskuev VV, Elrna VS, Yohei S (2001) Mapping salt affected soils using remote sensing indicators. In: 22nd Asian conference on remote sensing, Singapore, 5–9 November 2001Google Scholar
  62. Kissinger G, Herold M, De Sy V (2012) Drivers of deforestation and forest degradation: a synthesis report for REDD+ policymakers. Lexeme Consult, VancouverGoogle Scholar
  63. Koofhafkan AP, Lantieri D, Nachtergaele F (2003) Land Degradation in Drylands (LADA): guidelines for a methodological approach. FAO, RomeGoogle Scholar
  64. Koohafkan P, Stewart BA (2012) Water and cereals in drylands, the food and agriculture. Organization of the United Nations and Earthscan, RomeGoogle Scholar
  65. Koshal AK (2010) Indices based salinity areas detection through remote sensing and GIS. In parts of south waste Punjab. In: 13th annual international conference and exhibition on geospatial information technology and applications, Gurgaon, IndiaGoogle Scholar
  66. LADA (2009) Guidelines for the identification, selection and description of nationally based indicators of land degradation and improvement, land degradation assessment in drylands. UNEP, RomeGoogle Scholar
  67. Lal R (2003) Soil erosion and the global carbon budget. Environ Int 29:437–450CrossRefGoogle Scholar
  68. Lu D, Batistella M, Mausel P, Moran E (2007) Mapping and monitoring land degradation risks in the Western Brazilian Amazon using multitemporal Landsat TM/ETM+ images. Land Degrad Dev 18:41–54CrossRefGoogle Scholar
  69. Ma JW, Xue Y, Ma CF, Wang ZG (2003) A data fusion approach for soil erosion monitoring in the upper Yangtze river basin of China based on Universal Soil Loss Equation (USLE) model. Int J Remote Sens 24:4777–4789CrossRefGoogle Scholar
  70. Maji AK (2007) Assessment of degraded and wastelands of India. J Indian Soc Soil Sci 55:427–435Google Scholar
  71. Maji AK, Reddy GPO, Sarkar D (2010) Degraded and wastelands of India, status and spatial distribution. ICAR and NAAS Publication, New Delhi, pp 1–158Google Scholar
  72. Maji AK, Reddy GPO, Sarkar D (eds) (2012). Acid soils of India – their extent and spatial variability, NBSS Publ. No.145, NBSS&LUP, Nagpur, 147 pGoogle Scholar
  73. Mandal D, Sharda VN (2011) Assessment of permissible soil loss in India employing a quantitative bio-physical model. Curr Sci 100(3):383–390Google Scholar
  74. Metternicht G (2006) UN-Zambia-ESA regional workshop on the applications of GNSS in sub-Saharan AfricaGoogle Scholar
  75. Metternicht GI, Zinck JA (1996) Modelling salinity-sodicity classes for mapping salt affected top soils in the semi-arid valleys of Cochabamba (Bolivia). ITC J 11:125–135Google Scholar
  76. Metternicht GI, Zinck JA (1997) Spatial discrimination of salt- and sodium-aff ected soil surfaces. Int J Remote Sens 18:2571–2586CrossRefGoogle Scholar
  77. Metternicht GI, Zinck JA (1998) Evaluating de information content of JERS-1 SAR and Landsat TM data for discrimination of soil erosion features. ISPRS J Photogramm Remote Sens 53:143–153CrossRefGoogle Scholar
  78. Metternicht GI, Zinck JA (eds) (2008) Remote sensing of soil salinization: impact on land management. CRC Press/Taylor & Francis, Boca RatonGoogle Scholar
  79. Metternicht G, Zinck JA, Blanco PD, del Valle HF (2009) Remote sensing of land degradation: experiences from Latin America and the Caribbean. J Environ Qual 39:42–61CrossRefGoogle Scholar
  80. Miettinen J, Stibig H-J, Achard F (2014) Remote sensing of forest degradation in Southeast Asia-aiming for a regional view through 5–30 m satellite data. Glob Ecol Conserv 2:24–36CrossRefGoogle Scholar
  81. Millward AA, Mersey JE (1999) Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. Catena 38:109–129CrossRefGoogle Scholar
  82. Mitasova H, Hofierka J, Zlocha M, Iverson LR (1996) Modelling topographic potential for erosion and deposition using GIS. Int J Geogr Inf Sci 10:629–641CrossRefGoogle Scholar
  83. Molnar DK, Julien PY (1998) Estimation of upland erosion using GIS. Comput Geosci 24:183–192CrossRefGoogle Scholar
  84. Morgan RPC, Morgan DDV, Finney HJ (1984) A predictive model for the assessment of soil erosion risk. J Agric Eng Res 30(1):245–253CrossRefGoogle Scholar
  85. National Commission on Agriculture (1976) Report of the National Commission on Agriculture: part V, IX and abridged. Ministry of Agriculture and Irrigation, New DelhiGoogle Scholar
  86. Navalgund RR, Jayaraman V, Roy PS (2007) Remote sensing applications: an overview. Curr Sci 93:1747–1766Google Scholar
  87. Nawar S, Buddenbaum H, Hill J, Kozak J (2014) Modeling and mapping of soil salinity with reflectance spectroscopy and Landsat data using two quantitative methods (PLSR and MARS). Remote Sens 6:10813–10834CrossRefGoogle Scholar
  88. Noomen M (2007) Groundwater monitoring using GRACE and ERS satellite image. In: Proceeding of the 28th Asian conference on remote sensing, MalaysiaGoogle Scholar
  89. NRSA. (1996). Mapping salt-affected soils of India on 1:250,000. NRSA, HyderabadGoogle Scholar
  90. NRSA (2005) Wasteland atlas of India. Ministry of Rural Development and NRSA Publ., NRSA, HyderabadGoogle Scholar
  91. NRSA (2008) National wide mapping of land degradation on 1:50,000 scale using multi-temporal satellite data. NRSA, HyderabadGoogle Scholar
  92. NSERL (1995) WEPP user summary. National Soil Erosion Research Laboratory, US Department of Agriculture. Accessed 10 September 2017Google Scholar
  93. NWDB (1985) Description, classification, identification and monitoring of wastelands. National Wastelands Development Board, Ministry of Environment and Forests. Govt. of India, New DelhiGoogle Scholar
  94. Oldeman LR (ed) (1988) Global Assessment of Soil Degradation (GLASOD). Guidelines for general assessment of status of human-induced soil degradation. ISRIC, Wageningen. Working paper and reprint no. 88 (4), pp 12Google Scholar
  95. Oldeman LR (1994) The global extent of land degradation. In: Greenland DJ, Szabolcs I (eds) Land resilience and sustainable land use. CABI, Wallingford, pp 99–118Google Scholar
  96. Oldeman RL, Hakkeling RTA, Sombroek WG (1990) World map of the status of human induced soil degradation. International soil reference and information Centre, WageningenGoogle Scholar
  97. Oldeman LR, Hakkeling RTA, Sombroek WG (1991) World map of the status of Human Induced soil degradation: an explanatory note. ISRIC (International Soil Reference and Information Center), WageningenGoogle Scholar
  98. Panagos P, Borrelli P, Poesen J, Ballabio C, Lugato E, Meusburger K, MOntanarella L, Alewell C (2015) The new assessment of soil loss by water erosion in Europe. Environ Sci Pol 54:438–447CrossRefGoogle Scholar
  99. Pandey PC, Rani M, Srivastava PK, Sharma LK, Nathawat MS (2013) Land degradation severity assessment with sand encroachment in an ecologically fragile arid environment: a geospatial perspective. Q Sci Connect 43:17Google Scholar
  100. Paningbatan EP (2001) Geographic information system assisted dynamic modeling of soil erosion and hydrologic processes at a watershed scale. Philippine Agric Sci 84(4):388–393Google Scholar
  101. Panta M, Kim K, Joshi C (2008) Temporal mapping of deforestation and forest degradation in Nepal: applications to forest conservation. For Ecol Manag 256:1587–1595CrossRefGoogle Scholar
  102. Pickup G, Chewings VH (1986) A grazing gradient approach to land degradation assessment in arid areas from remotely-sensed data. Int J Remote Sens 15:597–617CrossRefGoogle Scholar
  103. Pohl C, van Genderen JL (1998) Review article. Multisensor image fusion in remote sensing: concepts, methods and applications. Int J Remote Sens 19(5):823–854CrossRefGoogle Scholar
  104. Raina P, Joshi DC, Kolarkar AS (1991) Land degradation mapping by remote sensing in the arid region of India. Soil Use Manag 7(1):47–51CrossRefGoogle Scholar
  105. Rao BRM, Venkataratnam L (1991) Monitoring of salt-affected soils- a case study using aerial photographs, Salyut-7 space photographs and Landsat-TM data. Geocarto Int 6(1):5–11CrossRefGoogle Scholar
  106. Rao BRM, Dwivedi RS, Venkataratnam L, Ravishankar TSS, Bhargawa GP, Singh AN (1991) Mapping the magnitude of sodicity in part of the indo-Gangetic plains of Uttar Pradesh, northern India using Landsat-TM data. Int J Remote Sens 12(3):419–425CrossRefGoogle Scholar
  107. Reddy GPO, Maji AK, Srinivas CV, Velayutham M (2002) Geomorphological analysis for inventory of degraded lands in a river basin of basaltic terrain, using remote sensing data and geographical information systems. J Indian Soc Remote Sens 30(1&2):15–31CrossRefGoogle Scholar
  108. Reddy GPO, Maji AK, Chary GR, Srinivas CV, Tiwary P, Gajbhiye KS (2004) GIS and remote sensing applications in prioritization of river sub basins using morphometric and USLE parameters – a case study. Asian J Geoinform 4(4):35–49Google Scholar
  109. Reddy GPO, Kurothe RS, Sena DR, Harindranath CS, Naidu LGK, Sarkar D, Sharda VN (2013). Soil erosion of Goa. NBSS Publ. 155. NBSS&LUP (ICAR), Nagpur, p 54Google Scholar
  110. Reddy GPO, Kurothe RS, Sena DR, Harindranath CS, Niranjana KV, Naidu LGK, Singh SK, Sarkar D, Mishra PK, Sharda VN (2016) Assessment of soil erosion in tropical ecosystem of Goa, India using universal soil loss equation, geostatistics and GIS. Indian J Soil Conserv 44(1):1–7Google Scholar
  111. Renard KG, Foster GR, Weesies GA et al (1997) Predicting soil erosion by water – a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE), Agricultural Handbook No. 703, US Government Printing Office, Washington, DCGoogle Scholar
  112. Reusing M, Schneider T, Ammer U (2000) Modeling soil erosion rates in the Ethiopian highlands by integration of high resolution MOMS-02/D2-stereo-data in a GIS. Int J Remote Sens 21:1885–1896CrossRefGoogle Scholar
  113. Rhoades JD (1990) Soil salinity-causes and controls. In: Goudie AS (ed) Techniques for desert reclamation. Wiley, Chichester, pp 109–134Google Scholar
  114. Riksen M, Brouwer F, De Graaf J (2003) Soil conservation policy measures to control wind erosion in north-western Europe. Catena 52:309–326CrossRefGoogle Scholar
  115. Rodell M, Velicogna I, Famiglietti JS (2009) Satellite-based estimates of groundwater depletion in India. Nature 460:999–1002CrossRefGoogle Scholar
  116. Roy PS, Kushwaha SPS, Murthy MSR, Roy A, Kushwaha D, Reddy CS, Behera MD, Mathur VB, Padalia H, Saran S, Singh S, Jha CS, Porwal MC (2012) Biodiversity characterization at landscape level: national assessment 2012. Indian Institute of Remote Sensing, Dehradun, India, p 140Google Scholar
  117. Saini KM, Deb TK, Mitra PP, Ghatol SG (1999) Assessment of degraded lands of Puruliya district, West Bengal using remotely sensed data. J Indian Soc Remote Sens 27:23–30CrossRefGoogle Scholar
  118. Seghal JL, Saxena RK, Verma KS (1988) Soil resource inventory of India using image interpretation techniques, remote sensing is a tool for soil scientists. In the 5th symposium of the working group remote sensing ISSS, Budapest, pp 17–31Google Scholar
  119. Sehgal J, Abrol IP (1992) Land degradation statue: India. Desertification Bull 21:24–31Google Scholar
  120. Sehgal J, Abrol IP (1994) Soil degradation in India: status and impact. Oxford/IBH, New DelhiGoogle Scholar
  121. Sharma RC, Bhargawa GP (1988) Landsat imagery for mapping saline soils and wetlands in north-west India. Int J Remote Sens 9:69–84CrossRefGoogle Scholar
  122. Sharma KD, Walling DE, Probst JL (1997) Assessing the impact of overgrazing on soil erosion in arid regions at a range of spatial scales. Human impact on erosion and sedimentation. Proceedings of an international symposium of the fifth scientific assembly of the International Association of Hydrological Sci. (IAHS), Rabat, Morocco, pp 119–123Google Scholar
  123. Singh B (1992) Groundwater resources and agricultural development strategy: Punjab experience. Indian J Agric Econ 47:105–113Google Scholar
  124. Singh AN, Dwivedi RS (1989) Delineation of salt affected soils through digital analysis of Landsat- MSS data. Int J Remote Sens 10:83–92CrossRefGoogle Scholar
  125. Singh D, Meirelles MSP, Costa GA, Herlin I, Berroir JP, Silva EF (2006) Environmental degradation analysis using NOAA/AVHRR data. Adv Space Res 37(4):720–727CrossRefGoogle Scholar
  126. Sommerfeldt TG, Thompson MD, Pront NA (1985) Delineation and mapping of soil-salinity in southern Alberta from Landsat data. Can J Remote Sens 10(104–1):18Google Scholar
  127. Sonneveld BGJS, Dent DL (2009) How good is GLASOD? J Environ Manag 90:274–283CrossRefGoogle Scholar
  128. Srinivas CV, Maji AK, Reddy GPO, Chary GR (2002) Assessment of soil erosion using remote sensing and GIS in Nagpur district, Maharashtra, for prioritization and delineation of conservation units. J Indian Soc Remote Sens 30(4):197–211CrossRefGoogle Scholar
  129. Steffens M, Koebl A, Giese M, Kogel-Knabner I (2009) Spatial variability of top soils and vegetation in a grazed steppe ecosystem in inner Mongolia (PR China). J Plant Nutr Soil Sci 172:78–90CrossRefGoogle Scholar
  130. Suphan S, Honda K, Gupta AD, Eiumnoh A, Chen X (2004) Estimation of subsurface water level change from satellite data. In: Proceeding of 25th Asia conference remote sensing, Thailand, 1, pp 512–516Google Scholar
  131. Tandon HLS (1992) Assessment of soil nutrient depletion. Paper presented to FADINAP seminar, Fertilization and the environment, Chiang Mai, ThailandGoogle Scholar
  132. Tucker CJ, Newcomb WW, Dregne HE (1994) AVHRR data sets for determination of desert spatial extent. Int J Remote Sens 15:3547–3565CrossRefGoogle Scholar
  133. Twyford I (1994) Fertilizer use and crop yields. Paper presented to 4th National Congress of the Soil Science Society of Pakistan, Islamabad. 1992Google Scholar
  134. UNCCD (2015) Land matters for climate reducing the gap and approaching the target. Available from: http://www.unccd.int/Lists/SiteDocumentLibrary/Publications/2015Nov_Land_matters_For_Climate_ENG.pdf 2015
  135. UNEP (1992) Desertification, land degradation [definitions]. Desertification Control Bull 21Google Scholar
  136. Vågen TG, Winowiecki LA, Abegaz A, Hadgu KM (2013) Landsat-based approaches for mapping of land degradation prevalence and soil functional properties in Ethiopia. Remote Sens Environ 134:266–275CrossRefGoogle Scholar
  137. Van Lynden GWJ, Oldeman LR (1997) The assessment of the status of human-induced soil degradation in south and South East Asia. UNEP/FAO and ISRIC, WageningenGoogle Scholar
  138. Venkatratnam L (1983) Monitoring of soil salinity in indo-Gangetic plain of NW India using multi-date Landsat data. In: Proceedings of 17th international symposium on remote sensing of environment. Ann. Arbor, Michigan, USA 1, pp 369–377Google Scholar
  139. Verma KS, Saxena RK, Barthwal AK, Deshmukh SN (1994) Remote sensing technique for mapping salt affected soils. Int J Remote Sens 15(9):1901–1914CrossRefGoogle Scholar
  140. Vrieling A (2006) Satellite remote sensing for water erosion assessment: a review. Catena 65:2–18CrossRefGoogle Scholar
  141. Vrieling A, de Jong SM, Sterk G, Rodrigues SC (2008) Timing of erosion and satellite data: a multi-resolution approach to soil erosion risk mapping. Int J Appl Earth Obs Geoinf 10:267–281CrossRefGoogle Scholar
  142. Wang G, Gertner G, Fang S, Anderson AB (2003) Mapping multiple variables for predicting soil loss by geostatistical methods with TM images and a slope map. Photogramm Eng Remote Sens 69:889–898CrossRefGoogle Scholar
  143. Warren A, Khogali M (1992) Assessment of desertification and drought in the Sudano-Sahelian region IW−/99/. United Nations Sudano-Sahelian OfficeGoogle Scholar
  144. Wessels KJ, Prince SD, Frost PE, VanZyl D (2004) Assessing the effects of human-induced land degradation in the former homelands of northern South Africa with a 1 km AVHRR NDVI time-series. Remote Sens Environ 91:47–67CrossRefGoogle Scholar
  145. Wiersma JL, Horton M (1976) Remote sensing applications for detection of saline seep. Report no. OWRD-44, South Dakota State University, Brookings, South Dakota, USAGoogle Scholar
  146. Wilson JP, Lorang MS (2000) Spatial models of soil erosion and GIS. In: Fotheringham AS, Wegener M (eds) Spatial models and GIS: new potential and new models. Taylor & Francis, Philadelphia, pp 83–108Google Scholar
  147. Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses – a guide to conservation planning, USDA agricultural handbook no 587Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • G. P. Obi Reddy
    • 1
  • Nirmal Kumar
    • 1
  • S. K. Singh
    • 1
  1. 1.ICAR-National Bureau of Soil Survey & Land Use PlanningNagpurIndia

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