Literature DB >> 32905527

Real Time HABs Mapping Using NASA Glenn Hyperspectral Imager.

Reid W Sawtell1, Robert Anderson2, Roger Tokars2, John D Lekki2, Robert A Shuchman1, Karl R Bosse1, Michael J Sayers1.   

Abstract

The hyperspectral imaging system (HSI) developed by the NASA Glenn Research Center was used from 2015-2017 to collect high spatial resolution data over Lake Erie and the Ohio River. Paired with a vicarious correction approach implemented by the Michigan Tech Research Institute, radiance data collected by the HSI system can be converted to high quality reflectance data which can be used to generate near-real time (within 24 hours) products for the monitoring of harmful algal blooms using existing algorithms. The vicarious correction method relies on imaging a spectrally constant target to normalize HSI data for atmospheric and instrument calibration signals. A large asphalt parking lot near the Western Basin of Lake Erie was spectrally characterized and was determined to be a suitable correction target. Due to the HSI deployment aboard an aircraft, it is able to provide unique insights into water quality conditions not offered by space-based solutions. Aircraft can operate under cloud cover and flight paths can be chosen and changed on-demand, allowing for far more flexibility than space-based platforms. The HSI is also able to collect data at a high spatial resolution (~1 m), allowing for the monitoring of small water bodies, the ability to detect small patches of surface scum, and the capability to monitor the proximity of blooms to targets of interest such as water intakes. With this new rapid turnaround time, airborne data can serve as a complementary monitoring tool to existing satellite platforms, targeting critical areas and responding to bloom events on-demand.

Entities:  

Keywords:  Harmful Algal Blooms; Hyperspectral; Lake Erie; Real Time Data Products

Year:  2019        PMID: 32905527      PMCID: PMC7473400          DOI: 10.1016/j.jglr.2019.02.007

Source DB:  PubMed          Journal:  J Great Lakes Res        ISSN: 0380-1330            Impact factor:   2.480


  15 in total

1.  Effect of bio-optical parameter variability on the remote estimation of chlorophyll-a concentration in turbid productive waters: experimental results.

Authors:  Giorgio Dall'Olmo; Anatoly A Gitelson
Journal:  Appl Opt       Date:  2005-01-20       Impact factor: 1.980

2.  Internal ecosystem feedbacks enhance nitrogen-fixing cyanobacteria blooms and complicate management in the Baltic Sea.

Authors:  Emil Vahtera; Daniel J Conley; Bo G Gustafsson; Harri Kuosa; Heikki Pitkänen; Oleg P Savchuk; Timo Tamminen; Markku Viitasalo; Maren Voss; Norbert Wasmund; Fredrik Wulff
Journal:  Ambio       Date:  2007-04       Impact factor: 5.129

3.  Estimation of the remote-sensing reflectance from above-surface measurements.

Authors:  C D Mobley
Journal:  Appl Opt       Date:  1999-12-20       Impact factor: 1.980

4.  Variation of microcystins, cyanobacterial hepatotoxins, in Anabaena spp. as a function of growth stimuli.

Authors:  J Rapala; K Sivonen; C Lyra; S I Niemelä
Journal:  Appl Environ Microbiol       Date:  1997-06       Impact factor: 4.792

Review 5.  Controlling harmful cyanobacterial blooms in a world experiencing anthropogenic and climatic-induced change.

Authors:  Hans W Paerl; Nathan S Hall; Elizabeth S Calandrino
Journal:  Sci Total Environ       Date:  2011-02-23       Impact factor: 7.963

6.  Comparison of satellite reflectance algorithms for estimating turbidity and cyanobacterial concentrations in productive freshwaters using hyperspectral aircraft imagery and dense coincident surface observations.

Authors:  Richard Beck; Min Xu; Shengan Zhan; Richard Johansen; Hongxing Liu; Susanna Tong; Bo Yang; Song Shu; Qiusheng Wu; Shujie Wang; Kevin Berling; Andrew Murray; Erich Emery; Molly Reif; Joseph Harwood; Jade Young; Christopher Nietch; Dana Macke; Mark Martin; Garrett Stillings; Richard Stumpf; Haibin Su; Zhaoxia Ye; Yan Huang
Journal:  J Great Lakes Res       Date:  2019-06-01       Impact factor: 2.480

7.  A fluorometric method for the differentiation of algal populations in vivo and in situ.

Authors:  M Beutler; K H Wiltshire; B Meyer; C Moldaenke; C Lüring; M Meyerhöfer; U-P Hansen; H Dau
Journal:  Photosynth Res       Date:  2002       Impact factor: 3.573

8.  A drinking water crisis in Lake Taihu, China: linkage to climatic variability and lake management.

Authors:  Boqiang Qin; Guangwei Zhu; Guang Gao; Yunlin Zhang; Wei Li; Hans W Paerl; Wayne W Carmichael
Journal:  Environ Manage       Date:  2010-01       Impact factor: 3.266

9.  Interannual variability of cyanobacterial blooms in Lake Erie.

Authors:  Richard P Stumpf; Timothy T Wynne; David B Baker; Gary L Fahnenstiel
Journal:  PLoS One       Date:  2012-08-01       Impact factor: 3.240

10.  A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing.

Authors:  Erin A Urquhart; Blake A Schaeffer; Richard P Stumpf; Keith A Loftin; P Jeremy Werdell
Journal:  Harmful Algae       Date:  2017-07-14       Impact factor: 4.273

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  3 in total

1.  Predicting Cyanobacterial Blooms Using Hyperspectral Images in a Regulated River.

Authors:  Jung Min Ahn; Byungik Kim; Jaehun Jong; Gibeom Nam; Lan Joo Park; Sanghyun Park; Taegu Kang; Jae-Kwan Lee; Jungwook Kim
Journal:  Sensors (Basel)       Date:  2021-01-13       Impact factor: 3.576

2.  Hyperspectral Image Labeling and Classification Using an Ensemble Semi-Supervised Machine Learning Approach.

Authors:  Vidya Manian; Estefanía Alfaro-Mejía; Roger P Tokars
Journal:  Sensors (Basel)       Date:  2022-02-18       Impact factor: 3.576

3.  Laser Remote Sensing of Lake Kinneret by Compact Fluorescence LiDAR.

Authors:  Sergey M Pershin; Boris G Katsnelson; Mikhail Ya Grishin; Vasily N Lednev; Vladimir A Zavozin; Ilia Ostrovsky
Journal:  Sensors (Basel)       Date:  2022-09-26       Impact factor: 3.847

  3 in total

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