Bio-optical Modeling and Remote Sensing of Aquatic Macrophytes

Malthus, Tim J.

doi:10.1016/b978-0-12-804644-9.00009-4

Cited by 23 publications

(55 citation statements)

References 114 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Remote sensing offers a practical means of regularly mapping and monitoring optically shallow waters (those where the bottom is visible from the water surface and measurably influences the remote sensing reflectance, (Dekker et al 2011)), which include inland waters, estuarine, tropical coral reef and temperate coastal ecosystems. In particular, EO has been used since the early 1990 s for mapping of bottom types and benthic communities (e.g., mud, sand-mud mixture, coral sands, coral reefs, seagrass, macrophytes): a thorough review of state of the art and future perspectives of remote sensing of aquatic macrophytes is given by Malthus (2017), while a recent review of remote sensing approaches of coral reefs mapping is provided by Hedley et al (2016). With a spatial resolution of 10-30 m (up to 2-5 m from WorldView-like sensors) multispectral sensors are ideal for most of the application scales but they are limited to identify species with distinctively different spectral characteristics (e.g., Dekker et al 2005;Villa et al 2014).…”

Section: Mapping Of Shallow Water Habitatsmentioning

confidence: 99%

Imaging Spectrometry of Inland and Coastal Waters: State of the Art, Achievements and Perspectives

et al. 2018

View full text Add to dashboard Cite

Imaging spectrometry of non-oceanic aquatic ecosystems has been in development since the late 1980s when the first airborne hyperspectral sensors were deployed over lakes. Most water quality management applications were, however, developed using multispectral mid-spatial resolution satellites or coarse spatial resolution ocean colour satellites till now. This situation is about to change with a suite of upcoming imaging spectrometers being deployed from experimental satellites or from the International Space Station. We review the science of developing applications for inland and coastal aquatic ecosystems * C. Giardino

show abstract

Section: Mapping Of Shallow Water Habitatsmentioning

confidence: 99%

Imaging Spectrometry of Inland and Coastal Waters: State of the Art, Achievements and Perspectives

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Remote sensing has been used for many years for mapping of bottom cover types and benthic communities (e.g., mud, sand-mud mixture, coral sands, coral reefs, seagrass, macrophytes). In particular, recent reviews of the state of the art were published by Malthus (2017) [23] and Hedley et al (2018) [24] for aquatic macrophytes and for coral reefs, respectively. Both reviews recognized that multispectral sensors are suitable for large-scale and long-term monitoring of lacustrine SAV.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Dynamics of Submerged Aquatic Vegetation in a Deep Lake from Sentinel-2 Data

Ghirardi

Bolpagni

Bresciani

et al. 2019

Water

View full text Add to dashboard Cite

We mapped the extent of submerged aquatic vegetation (SAV) of Lake Iseo (Northern Italy, over the 2015–2017 period based on satellite data (Sentinel 2 A-B) and in-situ measurements; the objective was to investigate its spatiotemporal variability. We focused on the southern sector of the lake, the location of the shallowest littorals and the most developed macrophyte communities, mainly dominated by Vallisneria spiralis and Najas marina. The method made use of both in-situ measurements and satellite data (22 Sentinel 2 A-B images) that were atmospherically corrected with 6SV code and processed with the BOMBER (Bio-Optical Model-Based tool for Estimating water quality and bottom properties from Remote sensing images). This modeling system was used to estimate the different substrate coverage (bare sediment, dense stands of macrophytes with high albedo, and sparse stand of macrophytes with low albedo). The presented results substantiate the existence of striking inter- and intra-annual variations in the spatial-cover patterns of SAV. Intense uprooting phenomena were also detected, mainly affecting V. spiralis, a species generally considered a highly plastic pioneer taxon. In this context, remote sensing emerges as a very reliable tool for mapping SAV with satisfactory accuracy by offering new perspectives for expanding our comprehension of lacustrine macrophyte dynamics and overcoming some limitations associated with traditional field surveys.

show abstract

“…Several other studies have concluded that high resolution airborne or satellite images may not be able to extract information about SAV in relatively deep reservoirs using frequently adopted simple methods such as image classification or empirical band ratios because of the target's low signal to noise ratio (Rotta et al, 2016(Rotta et al, , 2013Boschi, 2011;Malthus, 2017). Semi-analytical models have been proposed as an alternative to remove the water column influence and to retrieve bottom reflectance in water bodies to study submerged targets.…”

Section: Introductionmentioning

confidence: 99%

Analyzing the feasibility of a space-borne sensor (SPOT-6) to estimate the height of submerged aquatic vegetation (SAV) in inland waters

Rotta

Mishra

Watanabe

et al. 2018

ISPRS Journal of Photogrammetry and Remote Sensing

View full text Add to dashboard Cite

Remote sensing based approaches have been widely used over the years to monitor and manage submerged aquatic vegetation (SAV) or aquatic macrophytes mainly by mapping their spatial distribution and at the most, modeling SAV biomass. Remote sensing based studies to map SAV heights are rare because of the complexities in modeling water column optical proprieties. SAV height is a proxy for biomass and can be used to estimate plant volume when combined with percent cover. The objective of this study was to explore the feasibility of a satellite sensor to estimate the SAV height distribution in an inland reservoir. Also to test different radiative transfer theory based bio-optical models for estimating SAV heights using SPOT-6 data. The satellite-based multispectral data have rarely been used and SPOT-6 data, to the best of our knowledge, have never been used to estimate SAV heights in inland water bodies. In addition to depth and hydroacoustic data, in situ hyperspectral radiance and irradiance were measured at different depths to compute remote sensing reflectance (R rs) and the attenuation coefficients (K d and K Lu). Two models, Palandro et al. (2008) and Dierssen et al. (2003), were used to derive bottom reflectance from both in situ and atmospherically corrected SPOT-6 R rs. Bottom reflectance-based vegetation indices (green-red index, slope index, and simple ratio) were used to estimate SAV heights. Validation was performed using echosounder acquired hydroacoustic data. In situ model calibration produced an R 2 of 0.7, however, the validation showed a systematic underestimation of SAV heights and high Root Mean Square Error (RMSE); indicating that there is a greater sensitivity in in situ models to localized variations in water column optical properties. The model based on SPOT-6 data presented higher accuracy, with R 2 of 0.54 and RMSE of 0.29 m (NRMSE = 15%). Although the models showed a decreased sensitivity for SAVs at depths greater than 5 m with a height of 1.5 m, the finding nonetheless is significant because it proves that re-calibration of existing bottom reflectance models with more field data can enhance the accuracy to be able to periodically map SAV heights and biomass in inland waters. Although the initial results presented in this study are encouraging, further calibration of the model is required across different species, seasons, sites, and turbidity regime in order to test its application potential.

show abstract

Bio-optical Modeling and Remote Sensing of Aquatic Macrophytes

Cited by 23 publications

References 114 publications

Imaging Spectrometry of Inland and Coastal Waters: State of the Art, Achievements and Perspectives

Imaging Spectrometry of Inland and Coastal Waters: State of the Art, Achievements and Perspectives

Spatiotemporal Dynamics of Submerged Aquatic Vegetation in a Deep Lake from Sentinel-2 Data

Analyzing the feasibility of a space-borne sensor (SPOT-6) to estimate the height of submerged aquatic vegetation (SAV) in inland waters

Contact Info

Product

Resources

About