Literature DB >> 17593532

Remote sensing of aquatic vegetation: theory and applications.

Thiago S F Silva1, Maycira P F Costa, John M Melack, Evlyn M L M Novo.   

Abstract

Aquatic vegetation is an important component of wetland and coastal ecosystems, playing a key role in the ecological functions of these environments. Surveys of macrophyte communities are commonly hindered by logistic problems, and remote sensing represents a powerful alternative, allowing comprehensive assessment and monitoring. Also, many vegetation characteristics can be estimated from reflectance measurements, such as species composition, vegetation structure, biomass, and plant physiological parameters. However, proper use of these methods requires an understanding of the physical processes behind the interaction between electromagnetic radiation and vegetation, and remote sensing of aquatic plants have some particular difficulties that have to be properly addressed in order to obtain successful results. The present paper reviews the theoretical background and possible applications of remote sensing techniques to the study of aquatic vegetation.

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Year:  2007        PMID: 17593532     DOI: 10.1007/s10661-007-9855-3

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  2 in total

1.  Preliminary investigation of submerged aquatic vegetation mapping using hyperspectral remote sensing.

Authors:  David J William; Nancy B Rybicki; Alfonso V Lombana; Tim M O'Brien; Richard B Gomez
Journal:  Environ Monit Assess       Date:  2003 Jan-Feb       Impact factor: 2.513

2.  Passive remote sensing techniques for mapping water depth and bottom features.

Authors:  D R Lyzenga
Journal:  Appl Opt       Date:  1978-02-01       Impact factor: 1.980

  2 in total
  5 in total

1.  Assessment of water quality parameters of the Harike wetland in India, a Ramsar site, using IRS LISS IV satellite data.

Authors:  Samson Okongo Mabwoga; Amit Chawla; Ashwani Kumar Thukral
Journal:  Environ Monit Assess       Date:  2009-10-31       Impact factor: 2.513

2.  Mapping the spatio-temporal distribution of key vegetation cover properties in lowland river reaches, using digital photography.

Authors:  Veerle Verschoren; Jonas Schoelynck; Kerst Buis; Fleur Visser; Patrick Meire; Stijn Temmerman
Journal:  Environ Monit Assess       Date:  2017-05-26       Impact factor: 2.513

3.  Relating remotely sensed optical variability to marine benthic biodiversity.

Authors:  Kristjan Herkül; Jonne Kotta; Tiit Kutser; Ele Vahtmäe
Journal:  PLoS One       Date:  2013-02-06       Impact factor: 3.240

4.  Predicting species cover of marine macrophyte and invertebrate species combining hyperspectral remote sensing, machine learning and regression techniques.

Authors:  Jonne Kotta; Tiit Kutser; Karolin Teeveer; Ele Vahtmäe; Merli Pärnoja
Journal:  PLoS One       Date:  2013-06-03       Impact factor: 3.240

5.  Novel approach to large-scale monitoring of submerged aquatic vegetation: A nationwide example from Sweden.

Authors:  Silvia Huber; Lars B Hansen; Lisbeth T Nielsen; Mikkel L Rasmussen; Jonas Sølvsteen; Johnny Berglund; Carlos Paz von Friesen; Magnus Danbolt; Mats Envall; Eduardo Infantes; Per Moksnes
Journal:  Integr Environ Assess Manag       Date:  2021-08-20       Impact factor: 3.084

  5 in total

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