Skip to main content

Using Remote Sensing to Map and Monitor Water Resources in Arid and Semiarid Regions

  • Chapter
  • First Online:
Advances in Watershed Science and Assessment

Part of the book series: The Handbook of Environmental Chemistry ((HEC,volume 33))

Abstract

Life on Earth depends on water. Yet water resources are severely stressed by the rapid growth of the human population and activities. In arid environments the exploration and monitoring of water resources is a prerequisite for water accessibility and rational use and management. To survey large arid areas for water, conventional land-based techniques must be complemented by using satellite and airborne remote sensors. Surface water systems can be mapped using multispectral and radar sensors; soil moisture in the unsaturated zone can be remotely sensed with microwave radiometers using indirect indicators, such as microwave emissivity; freshwater wetlands can be mapped using multispectral cameras; and freshwater springs can be detected using thermal infrared radiometers. Satellite remote sensors and satellite gravitational surveys can be used in combination with ancillary data analysis to infer groundwater behavior from surface expressions and to estimate groundwater aquifer storage. This chapter provides an overview of satellite and airborne remote sensing techniques for managing water resources and monitoring drought in arid and semiarid regions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Asadi SS, Rani N, Vasantha Rao BVT, Raju MV (2012) Estimation of groundwater potential zones using remote sensing and GIS: a model study. Int J Adv Sci Res Tech 2:265–275

    Google Scholar 

  2. Sharma KD, Singh S, Singh N, Kalla AK (1989) Role of satellite remote sensing for monitoring of surface water resources in an arid environment. Hydrol Sci J 34:531–537

    Google Scholar 

  3. Yan E, Milewski A, Sultan M, Abdeldayem A, Soliman F, Abdel Gelil K (2010) Remote sensing based approach to improve regional estimation of renewable water resources for sustainable development. In: Proceedings of US-Egypt workshop on space technology and geo-information for sustainable development, Cairo, Egypt, 14–17 June 2010

    Google Scholar 

  4. Odum EP (1993) Ecology and our endangered life-support systems, 2nd edn. Sinauer, Sunderland, p 320

    Google Scholar 

  5. Krajewski WF, Smith JA (2002) Radar hydrology: rainfall estimation. Adv Water Resour 25:1387–1394

    Google Scholar 

  6. Jha MK, Chowdhury A, Chowdary VM, Peiffer S (2007) Groundwater management and development by integrated remote sensing and geographic information systems: prospects and constraints. Water Resour Manag 21:427–467

    Google Scholar 

  7. Sener E, Davraz A, Ozcelik M (2005) An integration of GIS and remote sensing in groundwater investigations: a case study in Burdur, Turkey. Hydrogeol J 13:826–834

    Google Scholar 

  8. Solomon S, Quiel F (2006) Groundwater study using remote sensing and geographic information systems (GIS) in the central highlands of Eritrea. Hydrogeol J 14:1029–1041

    CAS  Google Scholar 

  9. Becker MW (2006) Potential for satellite remote sensing of ground water. Ground Water 44:306–318

    CAS  Google Scholar 

  10. Brutsaert W (2005) Hydrology: an introduction. Cambridge University Press, Cambridge, p 605

    Google Scholar 

  11. Gamo M, Shinoda M, Maeda T (2013) Classification of arid lands, including soil degradation and irrigated areas, based on vegetation and aridity indices. Int J Remote Sens 34:6701–6722

    Google Scholar 

  12. Papa F, Prigent C, Aires F, Jimenez C, Rossow WB, Matthews E (2010) Interannual variability of surface water extent at the global scale, 1993–2004. J Geophys Res 115(D12):D12111

    Google Scholar 

  13. Prigent C, Papa F, Aires F, Rossow WB, Matthews E (2007) Global inundation dynamics inferred from multiple satellite observations, 1993–2000. J Geophys Res 112(D12):D12107

    Google Scholar 

  14. Frappart F, Papa F, Famiglietti JS, Prigent C, Rossow WB, Seyler F (2008) Interannual variations of river water storage from a multiple satellite approach: a case study for the Rio Negro River Basin. J Geophys Res 113:D21104. doi:10.1029/2007JD009438

    Google Scholar 

  15. Frappart F, Papa F, Güntner A, Werth S, Ramilien G, Prigent C, Rossow WB, Bonnet MP (2010) Interannual variations of the terrestrial water storage in the Lower Ob’ Basin from a multisatellite approach. Hydrol Earth Syst Sci 14(12):2443–2453

    Google Scholar 

  16. Smith LC, Pavelsky TM (2009) Remote sensing of volumetric storage changes in lakes. Earth Surf Proc Land 34:1353–1358

    Google Scholar 

  17. Alsdorf DE, Rodríguez E, Lettenmaier DP (2007) Measuring surface water from space. Rev Geophys 45:RG2002. doi:10.1029/2006RG000197

    Google Scholar 

  18. Combal B, Haas E, Andigue J, Nonguierma A, Bartholome E (2009) Operational monitoring of water bodies in arid and semi-arid regions with SPOT-VEGETATION satellite: contribution of Eumetcast and recent research projects. Secheresse 20:48–56

    Google Scholar 

  19. Smith LC (1997) Satellite remote sensing of river inundation area, stage, and discharge: a review. Hydrol Process 11:1427–1439

    Google Scholar 

  20. Hess L, Melack J, Simonett D (1990) Radar detection of flooding beneath the forest canopy: a review. Int J Remote Sens 11:1313–1325

    Google Scholar 

  21. Calmant S, Seyler F, Cretaux JF (2008) Monitoring continental surface waters by satellite altimetry. Surv Geophys 29(4–5):247–269. doi:10.1007/s10712-008-9051-1

    Google Scholar 

  22. Cazenave A, Bonnefond P, Dominh K, Schaeffer P (1997) Caspian sea level from TOPEX-POSEIDON altimetry: level now falling. Geophys Res Lett 24:881–884

    Google Scholar 

  23. Kostianoy AG, Lebedev SA, Solovyov AM (2011) Satellite monitoring of water resources in Turkmenistan. In: Fifteenth international water technology conference, IWTC-15, Alexandria, Egypt, 31 March–02 April 2011

    Google Scholar 

  24. Hofle B, Vetter M, Pfeiffer N, Mandlburger G, Stotter J (2009) Water surface mapping from airborne laser scanning using signal intensity and elevation data. Earth Surf Proc Land 34:1635–1649

    Google Scholar 

  25. Paine JG, Andrews JR, Saylam K, Tremblay TA, Averett AR, Caudle TL, Meyer T, Young MH (2013) Airborne lidar on the Alaskan North Slope: wetlands mapping, lake volumes, and permafrost features. Lead Edge 32:798–805

    Google Scholar 

  26. Schultz C (2014) Spatial resolution key to properly forecasting arid-region drought. Eos 95(13):116

    Google Scholar 

  27. Calvet JC, Wigneron JP, Walker JP, Karbou F, Chanzy A, Albergel C (2011) Sensitivity of passive microwave observations to soil moisture and vegetation water content: L-band to W-band. IEEE Trans Geosci Remote Sens 49:1190–1199

    Google Scholar 

  28. Choudhury BJ, Schmugge TJ, Chang A, Newton RW (1979) Effect of surface roughness on the microwave emission from soils. J Geophys Res 81:3660–3666

    Google Scholar 

  29. Chanzy A, Schmugge TJ, Calvet JC, Kerr Y, van Oevelen P, Grosjean O, Wang JR (1997) Airborne microwave radiometry on a semi-arid area during HAPEX-Sahel. J Hydrol 188–189:285–309

    Google Scholar 

  30. Jackson TJ, LeVine DM, Hsu AY, Oldak A, Starks PJ, Isham JD, Haken M (1999) Soil moisture mapping at regional scales using microwave radiometry: the Southern Great Plains Hydrology Experiment. IEEE Trans Geosci Remote Sens 37:2136–2150

    Google Scholar 

  31. John B (1992) Soil moisture detection with airborne passive and active microwave sensors. Int J Remote Sens 13:481–491

    Google Scholar 

  32. Barre HMJ, Duesmann B, Kerr YH (2008) SMOS: the mission and the system. IEEE Trans Geosci Remote Sens 46:587–593

    Google Scholar 

  33. Kerr YH, Waldteufel P, Wigneron JP, Martinuzzi JM, Font J, Berger M (2001) Soil moisture retrieval from space: the Soil Moisture and Ocean Salinity (SMOS) mission. IEEE Trans Geosci Remote Sens 39:1729–1735

    Google Scholar 

  34. Prigent C, Aires F, Rossow WB (2006) Land surface microwave emissivities over the globe for a decade. Bull Am Meteorol Soc 87:1573–1584

    Google Scholar 

  35. Kerr YH (2007) Soil moisture from space: where are we? Hydrogeol J 15:117–120

    CAS  Google Scholar 

  36. Kerr YH, Waldteufel P, Wigneron JP, Delwart S, Cabot F, Boutin J, Escorihuela MJ, Font J, Reul N, Gruhier C, Juglea SE, Drinkwater MR, Hahne A, Martin-Neira M, Mecklenburg S (2010) The SMOS mission: new tool for monitoring key elements of the global water cycle. Proc IEEE 98:666–687

    Google Scholar 

  37. Font J, Camps AJ, Borges A, Martin-Neira M, Boutin J, Reul N, Kerr YH, Hahne A (2010) SMOS: the challenging sea surface salinity measurement from space. Proc IEEE 98:649–665

    CAS  Google Scholar 

  38. McMullan KD, Brown MA, Martin-Neira M, Rits W, Ekholm S, Marti J, Lemanczyk J (2008) SMOS: the payload. IEEE Trans Geosci Remote Sens 46:594–605

    Google Scholar 

  39. Merlin O, Walker JP, Chehbouni A, Kerr Y (2008) Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil evaporation efficiency. Remote Sens Environ 112:3935–3946

    Google Scholar 

  40. Jackson TJ, Schmugge TJ (1991) Vegetation effects on the microwave emission of soils. Remote Sens Environ 36:203–212

    Google Scholar 

  41. Njoku EG, Entekhabi D (1996) Passive microwave remote sensing of soil moisture. J Hydrol 184:101–129

    CAS  Google Scholar 

  42. Aires F, Papa F, Prigent C (2013) A long-term, high-resolution wetland data set over the Amazon Basin, downscaled from a multi-wavelength retrieval using SAR data. J Hydrometeorol 14(2):594–607

    Google Scholar 

  43. Aires F, Papa F, Prigent C, Crétaux JF, Berge-Nguyen M (2013) Characterization and space/time downscaling of the inundation extent over the Inner Niger Delta using GIEMS and MODIS data. J Hydrometeorol 15(1):171–192. doi:10.1175/JHM-D-13-032.1

    Google Scholar 

  44. Entekhabi D, Njoku EG, O’Neill PE, Kellogg KH, Crow WT, Edelstein WN, Entin JK, Goodman SD, Jackson TJ, Johnson J, Kimball J, Piepmeier JR, Koster RD, Martin N, McDonald KC, Moghaddam M, Moran S, Reichle R, Shi JC, Spencer MW, Thurman SW, Tsang L, Van Ziel J (2010) The Soil Moisture Active Passive (SMAP) mission. Proc IEEE 98:704–716

    Google Scholar 

  45. Piles M, Entekhabi D, Camps A (2009) A change detection algorithm for retrieving high-resolution soil moisture from SMAP radar and radiometer observations. IEEE Trans Geosci Remote Sens 47:4125–4131

    Google Scholar 

  46. Anderson MP (2007) Introducing groundwater physics. Phys Today 60:42–47

    Google Scholar 

  47. Younger PL (2007) Groundwater in the environment: an introduction. Blackwell, Oxford, p 318

    Google Scholar 

  48. Hutti B, Nijagunappa R (2011) Application of geoinformatics in water resources management of semi-arid regions, North Karnataka, India. Int J Geomatics Geosci 2:373–382

    Google Scholar 

  49. Purkis S, Klemas V (2011) Remote sensing and global environmental change. Wiley-Blackwell, Oxford, p 367

    Google Scholar 

  50. Pool DR, Eychaner JH (1995) Measurements of aquifer storage change and specific yield using gravity surveys. Ground Water 33:425–432

    Google Scholar 

  51. Ramillien G, Frappart F, Cazenave A, Güntner A (2005) Time variations of the land water storage from an inversion of 2 years of GRACE geoids. Earth Planet Sci Lett 235:283–301

    CAS  Google Scholar 

  52. Swenson S, Wahr J, Milly PCD (2003) Estimated accuracies of regional water storage variations inferred from the Gravity Recovery and Climate Experiment (GRACE). Water Resour Res 39:12–23

    Google Scholar 

  53. Schmidt R, Schwinzer P, Flechtner F, Reigber C, Guntner A, Doll P, Ramillien P, Cazenave A, Petrovic S, Jochmann H, Wunsch J (2006) GRACE observations of changes in continental water storage. Global Planet Change 50:112–126

    Google Scholar 

  54. Rodell M, Famiglietti JS (2002) The potential for satellite-based monitoring of groundwater storage changes using GRACE: the High Plains aquifer, Central US. J Hydrol 263:245–256

    Google Scholar 

  55. Yirdaw SC, Snelgrove KR, Agboma CO (2008) GRACE satellite observations of terrestrial moisture changes for drought characterization in the Canadian Prairie. J Hydrol 356:84–92

    Google Scholar 

  56. Li B, Rodell M, Zaitchick BM, Reichle RH, Koster RD, Van Dam TM (2012) Assimilation of GRACE terrestrial water storage into a land surface model: evaluation and potential value for drought monitoring in western and central Europe. J Hydrol 446–447:103–115

    Google Scholar 

  57. Watkins MM (2004) Bowie lecture: time variable gravity measurements come of age. Eos 85(47): Fall Meeting Supplement, Abstract G24A-01

    Google Scholar 

  58. Machiwal D, Jha MK, Mal BC (2011) Assessment of groundwater potential in a semi-arid region of India using remote sensing, GIS and MCDM techniques. Water Resour Manag 25:1359–1386

    Google Scholar 

  59. Gramling C (2013) Kenyan find heralds new era in water prospecting. Science 341:1327

    Google Scholar 

  60. Fetter CW (2001) Applied hydrogeology, 4th edn. Prentice-Hall, Upper Saddle River, p 598

    Google Scholar 

  61. Klemas V (2011) Remote sensing of sea surface salinity: an overview with case studies. J Coastal Res 27:830–838

    Google Scholar 

  62. Klemas V (2012) Remote sensing of coastal plumes and ocean fronts: overview and case study. J Coastal Res 28:1–7

    Google Scholar 

  63. Kolokoussis P, Karathanassi V, Rokos D, Argialas D, Karageorgis AP, Georgopoulos D (2011) Integrating thermal and hyperspectral remote sensing for the detection of coastal springs and submarine groundwater discharges. Int J Remote Sens 32:8231–8251

    Google Scholar 

  64. Loheide S (2009) A thermal remote sensing tool for mapping spring and diffuse groundwater discharge to streams. U.S. Geological survey report. http://water.usgs.gov/wrri/o8grants/2008WI192B.html. Accessed 15 Oct 2014

  65. Thomson KPB, Nielsen G (1980) Groundwater discharge detection along the coasts of the Arabian Gulf and the Gulf of Oman using thermal infrared imagery. In: Proceedings of the 14th international symposium on remote sensing of environment, San Jose, Costa Rica, 23–30 Apr 1980, pp 835–843

    Google Scholar 

  66. Klemas V (2013) Airborne remote sensing of coastal features and processes: an overview. J Coastal Res 29:239–255

    Google Scholar 

  67. Di Martino G, Tonielli R (2010) Freshwater runoff effects on shallow-water multibeam surveys: using multibeam data processing to characterize submarine freshwater springs. Sea Technology, May 2010, pp 10–13

    Google Scholar 

  68. Jensen JR (2007) Remote sensing of the environment: an earth resource perspective. Prentice-Hall, Englewood Cliffs, p 608

    Google Scholar 

  69. Klemas V (2013) Remote sensing of wetland biomass: an overview. J Coastal Res 29:1016–1028

    Google Scholar 

  70. Cihlar J, St. Laurent A, Dyer JA (1991) Relation between the normalized difference vegetation index and ecological variables. Remote Sens Environ 35:279–298

    Google Scholar 

  71. Goward SN, Markham B, Dye DG, Dulaney W, Yang J (1991) Normalized difference vegetation index measurements from the advanced very high resolution radiometer. Remote Sens Environ 35:257–277

    Google Scholar 

  72. Young SS, Wang CY (2001) Land-cover change analysis of China using global-scale Pathfinder AVHRR Landcover (PAL) data, 1982–92. Int J Remote Sens 22:1457–1477

    Google Scholar 

  73. Yuan D, Elvidge CD, Lunetta RS (1998) Survey of multispectral methods for land cover change analysis. In: Lunetta RS, Elvidge CD (eds) Remote sensing change detection: environmental monitoring methods and applications. Ann Arbor, Chelsea, pp 21–40

    Google Scholar 

  74. Dong J, Kaufmann RK, Myneni RB, Tucker CJ, Kauppi PE, Liski J, Buermann W, Alexeyev V, Hughes MK (2003) Remote sensing estimates of boreal and temperate forest woody biomass: carbon pools, sources, and sinks. Remote Sens Environ 84:393–410

    Google Scholar 

  75. Gower ST, Kucharik CJ, Norman JM (1999) Direct and indirect estimation of leaf area index, fAPAR and net primary production of terrestrial ecosystems. Remote Sens Environ 70:29–51

    Google Scholar 

  76. Ku NW, Popescu SC, Ansley RJ, Perotto-Baldivieso HL, Fillippi AN (2012) Assessment of available rangeland woody plant biomass with a terrestrial lidar system. Photogramm Eng Remote Sens 78:349–361

    Google Scholar 

  77. Peregon A, Maksyutov S, Kosykh NP, Mironycheva-Tokareva NP (2008) Map-based inventory of wetland biomass and net primary production in Western Siberia. J Geophys Res 113:1–12

    Google Scholar 

  78. Riegel B (2012) A comparison of remote sensing methods for estimating above-ground carbon biomass at a wetland restoration area in the southeastern coastal plain. http://dukespace.lib.duke.edu/dspace/handle/10161/5164. Accessed 15 Oct 2012

  79. Running SW, Nemani RR, Heinsch FA, Zhao M, Reeves M, Hashimoto H (2004) A continuous satellite-derived measure of global terrestrial primary production. Bioscience 54:547–560

    Google Scholar 

  80. Lucas R, Armston J, Fairfax J, Fensham R, Dwyer J, Bowen M, Eyre T, Laidlaw M, Shimada M (2010) An evaluation of the ALOS PALSAR L-band backscatter- above ground biomass relationship over Queensland, Australia. IEEE J Sel Top Earth Obs Remote Sens 3:576–593

    Google Scholar 

  81. Graham S (2000) Drought: the creeping disaster. NASA Earth Observatory, August 28, 2000. http://earthobservatory.nasa.gov/Features/DroughtFacts/. Accessed 11 Apr 2014

  82. Weier J, Herring D (2000) Measuring Vegetation (NDVI & EVI). NASA Earth Observatory, August 30, 2000. http://earthobservatory.nasa.gov/Features/MeasuringVegetation/. Accessed 11 Apr 2014

  83. Hao Z, AghaKouchak A (2014) A nonparametric multivariate multi-index drought monitoring framework. J Hydrometeorol 15:89–101

    Google Scholar 

  84. Momtaz F, Nakhjiri N, AghaKouchak A (2014) Toward a drought cyber infrastructure system. Eos 95(22):182–183

    Google Scholar 

  85. Leibowitz SG (2003) Isolated wetlands and their functions: an ecological perspective. Wetlands 23:517–531

    Google Scholar 

  86. Semlitsch RD, Bodie JR (1998) Are small, isolated wetlands expendable? Conserv Biol 12:1129–1133

    Google Scholar 

  87. Winter TC, Labaugh JW (2003) Hydrologic considerations in defining isolated wetlands. Wetlands 23:532–540

    Google Scholar 

  88. Dahl TE (2006) Status and trends of wetlands in the conterminous United States 1998 to 2004. U.S. Department of the Interior, Fish and Wildlife Service, Washington, DC, p 112

    Google Scholar 

  89. Kelly M, Tuxen K (2009) Remote sensing support for tidal wetland vegetation research and management. In: Yang X (ed) Remote sensing and geospatial technologies for coastal ecosystem assessment and management. Springer, Berlin, pp 341–363

    Google Scholar 

  90. Ozesmi SL, Bauer ME (2002) Satellite remote sensing of wetlands. Wetlands Ecol Manag 10:381–402

    Google Scholar 

  91. Prigent C, Matthews E, Aires F, Rossow WB (2001) Remote sensing of global wetland dynamics with multiple satellite data sets. Geophys Res Lett 28:4631–4634

    Google Scholar 

  92. Tiner RW (1996) Wetlands. In: Manual of photographic interpretation, 2nd edn. American Society for Photogrammetry and Remote Sensing, Falls Church, Virginia, p 2440

    Google Scholar 

  93. Lunetta RS, Balogh ME (1999) Application of multi-temporal Landsat 5 TM imagery for wetland identification. Photogramm Eng Remote Sens 65:1303–1310

    Google Scholar 

  94. Baker C, Lawrence R, Montagne C, Patten D (2006) Mapping wetlands and riparian areas using Landsat ETM+ imagery and decision-based models. Wetlands 27:465–474

    Google Scholar 

  95. De Roeck ER, Verhoest NEC, Miya MH, Lievens H, Batelaan O, Thomas A, Brendonck L (2008) Remote sensing and wetland ecology: a South African case study. Sensors 8:3542–3556

    Google Scholar 

  96. Frohn RC, Reif M, Lane C, Autrey B (2009) Satellite remote sensing of isolated wetlands using object-oriented classification of Landsat-7 data. Wetlands 29:931–941

    Google Scholar 

  97. Tiner RW (2003) Geographically isolated wetlands of the United States. Wetlands 23:494–516

    Google Scholar 

  98. Klemas V (2013) Remote sensing of emergent and submerged wetlands: an overview. Int J Remote Sens 34:6286–6320

    Google Scholar 

  99. Wulder MA, Hall RJ, Coops NC, Franklin SE (2004) High spatial resolution remotely sensed data for ecosystem characterization. Bioscience 54:511–521

    Google Scholar 

  100. McCoy R (2005) Field methods in remote sensing. Guilford, New York, p 161

    Google Scholar 

  101. Ellis JM, Dodd HS (2000) Applications and lessons learned with airborne multispectral imaging. In: Fourteenth international conference on applied geological remote sensing, Las Vegas, Nevada, 6–8 Nov 2000

    Google Scholar 

  102. Lyon JG, McCarthy J (1995) Wetland and environmental applications of GIS. Lewis, New York, p 400

    Google Scholar 

  103. Hays RL (2009) Vegetation patterns and nutrient cycling in Delaware Bay salt marshes, Great Marsh (Lewes) and Webbs Marsh (South Bowers), Delaware. PhD Dissertation, University of Delaware, Lewes, p 384

    Google Scholar 

  104. Jensen RR, Mausel P, Dias N, Gonser R, Yang C, Everitt J, Fletcher R (2007) Spectral analysis of coastal vegetation and land cover using AISA+ hyperspectral data. Geocarto Int 22:17–28

    Google Scholar 

  105. Schmid T, Koch M, Gumuzzio J (2005) Multisensor approach to determine changes of wetland characteristics in semiarid environments in central Sapin. IEEE Trans Geosci Remote Sens 43:2516–2525

    Google Scholar 

  106. Schmidt KS, Skidmore AK, Kloosterman EH, Van Oosten H, Kumar L, Janssen JAM (2004) Mapping coastal vegetation using an expert system and hyperspectral imagery. Photogramm Eng Remote Sens 70:703–716

    Google Scholar 

  107. Yang C, Everitt JH, Fletcher RS, Jensen JR, Mausel PW (2009) Mapping black mangrove along the south Texas gulf coast using AISA+ hyperspectral imagery. Photogramm Eng Remote Sens 75:425–436

    Google Scholar 

  108. Yang J, Artigas FJ (2009) Mapping salt marsh vegetation by integrating hyperspectral and LiDAR remote sensing. In: Wang J (ed) Remote sensing of coastal environments. CRC, Boca Raton, pp 173–187

    Google Scholar 

  109. Gilmore MS, Civco DL, Wilson EH, Barrett N, Prisloe S, Hurd JD, Chadwick C (2009) Remote sensing and in situ measurements for delineation and assessment of coastal marshes and their constituent species. In: Wang J (ed) Remote sensing of coastal environments. CRC, Boca Raton, pp 261–280

    Google Scholar 

  110. Adam E, Mutanga O, Rugege D (2010) Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review. Wetlands Ecol Manag 18:281–296

    Google Scholar 

  111. Simard M, Fatoyinbo LE, Pinto N (2009) Mangrove canopy 3D structure and ecosystem productivity using active remote sensing. In: Wang J (ed) Remote sensing of coastal environments. CRC, Boca Raton, pp 61–78

    Google Scholar 

  112. Wang Y (2009) Remote sensing of coastal environments: an overview. In: Wang J (ed) Remote sensing of coastal environments. CRC, Boca Raton, pp 1–24

    Google Scholar 

  113. Baghdadi N, Bernier M, Gauthier R, Neeson I (2001) Evaluation of C-band SAR data for wetlands mapping. Int J Remote Sens 22:71–88

    Google Scholar 

  114. Lang MW, McCarty GW (2008) Remote sensing data for regional wetland mapping in the United States: trends and future prospects. In: Russo RE (ed) Wetlands: ecology, conservation and restoration. Nova Science, Hauppauge, pp 73–112

    Google Scholar 

  115. Novo EMLM, Costa MPF, Mantovani JE, Lima IBT (2002) Relationship between macrophyte stand variables and radar backscatter at L and C band, Tucurui reservoir, Brasil. Int J Remote Sens 23:1241–1260

    Google Scholar 

  116. Rosenqvist A, Finlayson CM, Lowry J, Taylor D (2007) The potential of long-wavelength satellite-borne radar to support implementation of the Ramsar Wetland Convention. Aquat Conserv Mar Freshw Ecosyst 17:229–244

    Google Scholar 

  117. Townsend PA (2000) A quantitative fuzzy approach to assess mapped vegetation classifications for ecological applications. Remote Sens Environ 72:253–267

    Google Scholar 

  118. Townsend PA (2002) Relationships between forest structure and the detection of flood inundation in forested wetlands using C-band SAR. Int J Remote Sens 23:443–460

    Google Scholar 

  119. Hall DK (1996) Remote sensing applications to hydrology: imaging radar. Hydrol Sci J 41:609–624

    CAS  Google Scholar 

  120. Kasischke E, Melack J, Dobson M (1997) The use of imaging radars for ecological applications: a review. Remote Sens Environ 59:141–156

    Google Scholar 

  121. Kasischke E, Bourgeau-Chavez L (1997) Monitoring South Florida wetlands using ERS-1 SAR imagery. Photogramm Eng Remote Sens 63:281–291

    Google Scholar 

  122. Lang MW, Kasischke ES (2008) Using C-band synthetic aperture radar data to monitor forested wetland hydrology in Maryland’s Coastal Plain, USA. IEEE Trans Geosci Remote Sens 46:535–546

    Google Scholar 

  123. Phinn SR, Stow DA, Van Mouwerik D (1999) Remotely sensed estimates of vegetation structural characteristics in restored wetlands, Southern California. Photogramm Eng Remote Sens 65:485–493

    Google Scholar 

  124. Rao BRM, Dwivedi RS, Kushwaha SPS, Bhattacharya SN, Anand JB, Dasgupta S (1999) Monitoring the spatial extent of coastal wetlands using ERS-1 SAR data. Int J Remote Sens 20:2509–2517

    Google Scholar 

  125. Wilson BA, Rashid H (2005) Monitoring the 1997 flood in the Red River Valley using hydrologic regimes and RADARSAT imagery. Can Geogr 49:100–109

    Google Scholar 

  126. Toyra JA, Pietroniro A, Martz W, Prowse TD (2002) A multi-sensor approach to wetland flood monitoring. Hydrol Process 16:1569–1581

    Google Scholar 

  127. Costa MPF, Telmer KH (2007) Mapping and monitoring lakes in the Brazilian Pantanal wetland using synthetic aperture radar imagery. Aquat Conserv Mar Freshw Ecosyst 17:277–288

    Google Scholar 

  128. Dwivedi R, Rao B, Bhattacharya S (1999) Mapping wetlands of the Sundarban delta and its environs using ERS-1 SAR data. Int J Remote Sens 20:2235–2247

    Google Scholar 

  129. Kasischke ES, Smith KB, Bourgeau-Chavez LL, Romanowicz EA, Brunzell S, Richardson CJ (2003) Effects of seasonal hydrologic patterns in south Florida wetlands on radar backscatter measured from ERS-2 SAR imagery. Remote Sens Environ 88:423–441

    Google Scholar 

  130. Harris J, Digby-Argus S (1986) The detection of wetlands on Radar imagery. In: Proceedings of the tenth Canadian symposium on remote sensing, Edmonton, Alberta, May 1986

    Google Scholar 

  131. Wdowinski S, Hong SH (2014) Wetland InSAR. In: Tiner R, Klemas V, Lang M (eds) Advances in wetland mapping. CRC, Boca Raton

    Google Scholar 

  132. Wdowinski S, Amelung F, Miralles-Wilhelm F, Dixon TH, Carande R (2004) Space-based measurements of sheet-flow characteristics in the Everglades wetland, Florida. Geophys Res Lett 31:L15503

    Google Scholar 

  133. Wdowinski S, Kim SW, Amelung F, Dixon TH, Miralles-Wilhelm F, Sonenshein R (2008) Space-based detection of wetlands’ surface water level changes from L-band SAR interferometry. Remote Sens Environ 112:681–696

    Google Scholar 

  134. Deng M, Di L, Han W, Yagci AL, Peng C, Heo G (2013) Web-service-based monitoring and analysis of global agricultural drought. Photogramm Eng Remote Sens 79:926–943

    Google Scholar 

  135. Mu Q, Zhao M, Kimball JS, McDowell MG, Running S (2013) A remotely sensed global terrestrial drought index. Bull Am Meteorol Soc 94:83–98

    Google Scholar 

  136. Narasimhan B, Srinivasan R (2005) Development and evaluation of soil moisture deficit index (SMDI) and evapotranspiration deficit index (ETDI) for agricultural drought monitoring. Agr Forest Meteorol 133:69–88

    Google Scholar 

  137. Dutta D, Kundu A, Patel NR (2013) Predicting agricultural drought in eastern Rajasthan of India using NDVI and standardized precipitation index. Geocarto Int 28:192–209

    Google Scholar 

  138. NOAA/CPC (2014) Drought: the creeping disaster. NASA earth observatory feature article, http://earthobservatory.nasa.gov/Features/DroughtFacts/drought_facts_4.php. Accessed 28 July 2014

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Victor Klemas .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Klemas, V., Pieterse, A. (2015). Using Remote Sensing to Map and Monitor Water Resources in Arid and Semiarid Regions. In: Younos, T., Parece, T. (eds) Advances in Watershed Science and Assessment. The Handbook of Environmental Chemistry, vol 33. Springer, Cham. https://doi.org/10.1007/978-3-319-14212-8_2

Download citation

Publish with us

Policies and ethics