Skip to main content
SpringerLink
Log in

Multitemporal Remote Sensing for Inland Water Bodies and Wetland Monitoring

  • Chapter
  • First Online:
Multitemporal Remote Sensing

Part of the book series: Remote Sensing and Digital Image Processing ((RDIP,volume 20))

Abstract

Remote sensing is critically important in monitoring inland water and wetlands for protecting the related environments and ecosystems. This chapter summarizes remote sensing applications in water and wetland monitoring, in particular in the subject areas of monitoring water quality, water surface areas and water fluctuation in wetland areas. The chapter then introduces two cases of monitoring studies in the Poyang Lake, the largest fresh water lake in China, in terms of monitoring of fluctuation and variation of water surface areas using MODIS data product, and monitoring of variation of natural wetlands corresponding to the changing water levels of Poyang Lake using Landsat data.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 229.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 299.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 299.99
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

  • Amitrano D, Martino D, Iodice A, Mitidieri F, Papa M-N, Riccio D, Ruello G (2014) Sentinel-1 for monitoring reservoirs: a performance analysis. Remote Sens 6:10676–10693

    Article  Google Scholar 

  • Awange JL, Sharifi MA, Ogonda G, Wickert J, Grafarend EW, Omulo MA (2008) The falling Lake Victoria water level: GRACE, TRIMM and CHAMP satellite analysis of the lake basin. Water Resour Manag 22(7):775–796

    Article  Google Scholar 

  • Costanza R, d’Arge R, De Groot R, Farber S, Grasso M, Hannon B, Limburg K, Naeem S, O’neill RV, Paruelo J (1998) The value of the world’s ecosystem services and natural capital. Ecol Econ 1(25):3–15

    Article  Google Scholar 

  • Dronova I, Gong P, Wang L (2011) Object-based analysis and change detection of major wet-land cover types and their classification uncertainty during the low water period at Poyang Lake, China. Remote Sens Environ 115(12):3220–3236

    Article  Google Scholar 

  • Duan H, Feng L, Ma R, Zhang Y, Loiselle SA (2014) Variability of particulate organic carbon in inland waters observed from MODIS Aqua imagery. Environ Res Lett 9(8):084011

    Article  Google Scholar 

  • Feng L, Hu C, Chen X, Li R, Tian L, Murch B (2011) MODIS observations of the bottom topography and its inter-annual variability of Poyang Lake. Remote Sens Environ 115(10):2729–2741

    Article  Google Scholar 

  • Feng L, Hu C, Chen X, Tian L, Chen L (2012a) Human induced turbidity changes in Poyang Lake between 2000 and 2010: Observations from MODIS. J Geophys Res 117. doi: 10.1029/2011JC007864

    Google Scholar 

  • Feng L, Hu C, Chen X, Cai X, Tian L, Gan W (2012b) Assessment of inundation changes of Poyang Lake using MODIS observations between 2000 and 2010. Remote Sens Environ 121:80–92

    Google Scholar 

  • Feng L, Hu C, Han X, Chen X, Qi L (2014) Long-term distribution patterns of chlorophyll-a concentration in China’s largest freshwater lake: MERIS full-resolution observations with a practical approach. Remote Sens 7(1):275–299

    Article  Google Scholar 

  • Gao JH, Jia J, Kettner AJ, Xing F, Wang YP, Xu XN, Yang Y, Zou XQ, Gao S, Qi S, Liao F (2014) Changes in water and sediment exchange between the Changjiang River and Poyang Lake under natural and anthropogenic conditions, China. Sci Total Environ 481:542–553

    Article  Google Scholar 

  • Gong P, Niu Z, Cheng X, Zhao K, Zhou D, Guo J, Liang L, Wang X, Li D, Huang H et al (2010) China’s wetland change (1990–2000) determined by remote sensing. Sci China Earth Sci 53(7):1036–1042

    Article  Google Scholar 

  • Guo Y, Li Y, Zhu L, Liu G, Wang S, Du C (2015) An improved unmixing-based fusion method: potential application to remote monitoring of inland waters. Remote Sens 7(2):1640–1666

    Article  Google Scholar 

  • Hui F, Xu B, Huang H, Yu Q, Gong P (2008) Modelling spatial-temporal change of Poyang Lake using multitemporal Landsat imagery. Int J Remote Sens 29(20):5767–5784

    Article  Google Scholar 

  • Jaelani LM, Matsushita B, Yang W, Fukushima T (2015) An improved atmospheric correction algorithm for applying MERIS data to very turbid inland waters. Int J Appl Earth Obs Geoinf 39:128–141

    Article  Google Scholar 

  • Jarihani AA, Callow JN, Johansen K, Gouweleeuw B (2013) Evaluation of multiple satellite al-timetry data for studying inland water bodies and river floods. J Hydrol 505:78–90

    Article  Google Scholar 

  • Jensen JR, Rutchey K, Koch MS, Narumalani S (1995) Inland wetland change detection in the Everglades Water Conservation Area 2A using a time series of normalized remotely sensed data. Photogramm Eng Rem Sens 61(2):199–209

    Google Scholar 

  • Jiang F, Qi S, Liao F, Ding M, Wang Y (2014a) Vulnerability of Siberian crane habitat to water level in Poyang Lake wetland, China. GISci Remote Sens 51(6):662–676

    Article  Google Scholar 

  • Jiang G, Ma R, Duan H, Loiselle SA, Xu J, Liu D (2014b) Remote determination of chromophoric dissolved organic matter in lakes, China. Int J Digital Earth 7(11):897–915

    Article  Google Scholar 

  • Jiao L (2009) Scientists line up against dam that would alter protected wetlands. Science 326(5952):508–509

    Article  Google Scholar 

  • Korosov A, Pozdnyakov D, Pettersson L, Grassl H (2007) Satellite-data-based study of seasonal and spatial variations of water temperature and water quality parameters in Lake Ladoga. J Appl Remote Sens 1(1):011508–011517

    Article  Google Scholar 

  • Kropácek J, Braun A, Kang S, Feng C, Ye Q, Hochschild V (2012) Analysis of lake level changes in Nam Co in central Tibet utilizing synergistic satellite altimetry and optical imagery. Int J Appl Earth Obs Geoinf 17:3–11

    Article  Google Scholar 

  • Kutser T (2012) The possibility of using the Landsat image archive for monitoring long time trends in coloured dissolved organic matter concentration in lake waters. Remote Sens Environ 123:334–338

    Article  Google Scholar 

  • Kutser T, Arst H, Miller T, Käärmann L, Milius A (1995) Telespectrometrical estimation of water transparency, chlorophyll-a and total phosphorus concentration of Lake Peipsi. Int J Remote Sens 16(16):3069–3085

    Article  Google Scholar 

  • Kutser T, Pierson DC, Kallio KY, Reinart A, Sobek S (2005) Mapping lake CDOM by satellite remote sensing. Remote Sens Environ 94(4):535–540

    Article  Google Scholar 

  • Kutser T, Verpoorter C, Paavel B, Tranvik LJ (2015) Estimating lake carbon fractions from re-mote sensing data. Remote Sens Environ 157:138–146

    Article  Google Scholar 

  • Le C, Li Y, Zha Y, Sun D, Huang C, Zhang H (2011) Remote estimation of chlorophyll a in optically complex waters based on optical classification. Remote Sens Environ 115(2):725–737

    Article  Google Scholar 

  • Liao J, Gao L, Wang X (2014) Numerical simulation and forecasting of water level for Qinghai Lake using multi-altimeter data between 2002 and 2012. IEEE J Sel Top Appl Earth Obs Remote Sens 7(2):609–622

    Article  Google Scholar 

  • Ma R, Duan H, Hu C, Feng X, Li A, Ju W, Jiang J, Yang G (2010) A half‐century of changes in China’s lakes: global warming or human influence? Geophys Res Lett 37(24):1–6

    Article  Google Scholar 

  • Matthews MW (2014) Eutrophication and cyanobacterial blooms in South African inland waters: 10years of MERIS observations. Remote Sens Environ 155:161–177

    Article  Google Scholar 

  • Matthews MW, Odermatt D (2015) Improved algorithm for routine monitoring of cyanobacteria and eutrophication in inland and near-coastal waters. Remote Sens Environ 156:374–382

    Article  Google Scholar 

  • Min Q (1999) Evaluation of the effects of Poyang Lake reclamation on floods. Yangtze River 30(7):30–32

    Google Scholar 

  • Ogashawara I, Moreno-Madriñán MJ (2014) Improving inland water quality monitoring through remote sensing techniques. ISPRS Int J Geo-Inf 3(4):1234–1255

    Article  Google Scholar 

  • Ozesmi SL, Bauer ME (2002) Satellite remote sensing of wetlands. Wetl Ecol Manag 10(5):381–402

    Article  Google Scholar 

  • Palmer S, Kutser T, Hunter P (2015a) Remote sensing of inland waters: challenges, progress and future directions. Remote Sens Environ 157:1–8

    Article  Google Scholar 

  • Palmer S, Odermatt D, Hunter P, Brockmann C, Presing M, Balzter H, Tóth V (2015b) Satellite remote sensing of phytoplankton phenology in Lake Balaton using 10years of MERIS observations. Remote Sens Environ 158:441–452

    Article  Google Scholar 

  • Plug LJ, Walls C, Scott B (2008) Tundra lake changes from 1978 to 2001 on the Tuktoyaktuk Peninsula, western Canadian Arctic. Geophys Res Lett 35(3):1–5

    Article  Google Scholar 

  • Qi S, Brown DG, Tian Q, Jiang L, Zhao T, Bergen KM (2009) Inundation extent and flood fre-quency mapping using LANDSAT imagery and digital elevation models. GISci Remote Sens 46(1):101–127

    Article  Google Scholar 

  • Shankman D, Liang Q (2003) Landscape changes and increasing flood frequency in China’s Poyang Lake region. Prof Geogr 55(4):434–445

    Article  Google Scholar 

  • Shankman D, Keim BD, Song J (2006) Flood frequency in China’s Poyang Lake region: trends and teleconnections. Int J Climatol 26(9):1255–1266

    Article  Google Scholar 

  • Sheng Y, Li J (2011) Satellite-observed endorheic lake dynamics across the Tibetan Plateau between circa 1976 and 2000. In: Wang Y (ed) Remote sensing of protected lands. CRC, New York, pp 305–319

    Chapter  Google Scholar 

  • Shi K, Zhang Y, Zhu G, Liu X, Zhou Y, Xu H, Qin B, Liu G, Li Y (2015) Long-term remote monitoring of total suspended matter concentration in Lake Taihu using 250m MODIS-Aqua data. Remote Sens Environ 164:43–56

    Article  Google Scholar 

  • Smith LC, Beilman D, Kremenetski KV, Sheng Y, MacDonald GM, Lammers RB, Shiklomanov AI, Lapshina ED (2012) Influence of permafrost on water storage in West Siberian peatlands revealed from a new database of soil properties. Permafr Periglac 23(1):69–79

    Article  Google Scholar 

  • Song K, Li L, Tedesco L, Clercin N, Hall B, Li S, Shi K, Liu D, Sun Y (2013) Remote estima-tion of phycocyanin (PC) for inland waters coupled with YSI PC fluorescence probe. Environ Sci Pollut R 20(8):5330–5340

    Article  Google Scholar 

  • Wang Y (2009) Remote sensing of coastal environments (Editor). CRC Press, Boca Raton/London/New York, 457 p

    Book  Google Scholar 

  • Wang Y (2012) Remote sensing of protected lands (Editor). CRC Press, Boca Raton/London/New York, 604 p

    Google Scholar 

  • Wang M, Shi W (2008) Satellite-observed algae blooms in China’s Lake Taihu. Eos, Trans Am Geophys Union 89(22):201–202

    Article  Google Scholar 

  • Wang M, Shi W, Tang J (2011) Water property monitoring and assessment for China’s inland Lake Taihu from MODIS-Aqua measurements. Remote Sens Environ 115(3):841–854

    Article  Google Scholar 

  • Wang J, Sheng Y, Hinkel KM, Lyons EA (2012) Drained thaw lake basin recovery on the western Arctic Coastal Plain of Alaska using high-resolution digital elevation models and remote sensing imagery. Remote Sens Environ 119:325–336

    Article  Google Scholar 

  • Wu G, Liu Y (2015) Capturing variations in inundation with satellite remote sensing in a mor-phologically complex, large lake. J Hydrol 523:14–23

    Article  Google Scholar 

  • Wu J-L, Ho C-R, Huang C-C, Srivastav AL, Tzeng J-H, Lin Y-T (2014) Hyperspectral sensing for turbid water quality monitoring in freshwater rivers: empirical relationship between re-flectance and turbidity and total solids. Sensors 14(12):22670–22688

    Article  Google Scholar 

  • Xu G, Qin Z (1998) Flood estimation methods for Poyang lake area. J Lake Sci 10(1):51–56

    Google Scholar 

  • Yang X, Lu X (2014) Drastic change in China’s lakes and reservoirs over the past decades. Sci Rep 4. doi:10.1038/srep06041

  • Yésou H, Huber C, Lai X et al (2011) Nine years of water resources monitoring over the middle reaches of the Yangtze River, with ENVISAT, MODIS, Beijing-1 time se-ries, Altimetric data and field measurements. Lakes Reserv Res Manag 16(3):231–247

    Article  Google Scholar 

  • Yu Z, Chen X, Zhou B, Tian L, Yuan X, Feng L (2012) Assessment of total suspended sediment concentrations in Poyang Lake using HJ-1A/1B CCD imagery. Chin J Oceanol Limnol 30:295–304

    Article  Google Scholar 

  • Zhang Q, Ye X, Werner AD, Li Y, Yao J, Li X, Xu C (2014) An investigation of enhanced re-cessions in Poyang Lake: comparison of Yangtze River and local catchment impacts. J Hydrol 517:425–434

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Natural Resources Science, University of Rhode Island, 1 Greenhouse Road, Kingston, RI, USA

    Yeqiao Wang

  2. Ministry of Education’s Key Laboratory of Poyang Lake Wetland and Watershed Research, School of Geography and Environmental Science, Jiangxi Normal University, Nanchang, Jiangxi, China

    Yeqiao Wang, Shuhua Qi & Jian Xu

  3. College of Chemistry and Chemical Engineering, Jiangxi Normal University, Nanchang, Jiangxi, China

    Jian Xu

Authors
  1. Yeqiao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shuhua Qi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jian Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yeqiao Wang .

Editor information

Editors and Affiliations

  1. Division of Geoinformatics, KTH Royal Institute of Technology, Stockholm, Sweden

    Yifang Ban

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing AG

About this chapter

Cite this chapter

Wang, Y., Qi, S., Xu, J. (2016). Multitemporal Remote Sensing for Inland Water Bodies and Wetland Monitoring. In: Ban, Y. (eds) Multitemporal Remote Sensing. Remote Sensing and Digital Image Processing, vol 20. Springer, Cham. https://doi.org/10.1007/978-3-319-47037-5_17

Download citation

Publish with us

Policies and ethics

Search

Navigation