Very Shallow Water Bathymetry Retrieval from Hyperspectral Imagery at the Virginia Coast Reserve (VCR'07) Multi-Sensor Campaign

Bachmann, Charles M.; Montes, Marcos J.; Fusina, R.A.; Parrish, Christopher; Sellars, Jon; Weidemann, Alan; Goode, Wesley; Nichols, C. Reid; Woodward, P.; McIlhany, K.; Hill, Victoria; Zimmerman, Richard C.; Korwan, Daniel; Truitt, Barry R.; Schwarzschild, Arthur

doi:10.1109/igarss.2008.4778943

Cited by 11 publications

(7 citation statements)

References 8 publications

(10 reference statements)

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“…There are studies [42] showing that the 810 nm peak is suitable for mapping water depth in very shallow (less than 1 m deep) waters. This is reasonable as benthic vegetation has high reflectance in NIR part of spectrum [43,44] and there is a decrease in water absorbance at 810 nm making the bottom signal detectable in this spectral region.…”

Section: Discussionmentioning

confidence: 99%

Remote Sensing of Black Lakes and Using 810 nm Reflectance Peak for Retrieving Water Quality Parameters of Optically Complex Waters

et al. 2016

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Many lakes in boreal and arctic regions have high concentrations of CDOM (coloured dissolved organic matter). Remote sensing of such lakes is complicated due to very low water leaving signals. There are extreme (black) lakes where the water reflectance values are negligible in almost entire visible part of spectrum (400-700 nm) due to the absorption by CDOM. In these lakes, the only water-leaving signal detectable by remote sensing sensors occurs as two peaks-near 710 nm and 810 nm. The first peak has been widely used in remote sensing of eutrophic waters for more than two decades. We show on the example of field radiometry data collected in Estonian and Swedish lakes that the height of the 810 nm peak can also be used in retrieving water constituents from remote sensing data. This is important especially in black lakes where the height of the 710 nm peak is still affected by CDOM. We have shown that the 810 nm peak can be used also in remote sensing of a wide variety of lakes. The 810 nm peak is caused by combined effect of slight decrease in absorption by water molecules and backscattering from particulate material in the water. Phytoplankton was the dominant particulate material in most of the studied lakes. Therefore, the height of the 810 peak was in good correlation with all proxies of phytoplankton biomass-chlorophyll-a (R 2 = 0.77), total suspended matter (R 2 = 0.70), and suspended particulate organic matter (R 2 = 0.68). There was no correlation between the peak height and the suspended particulate inorganic matter. Satellite sensors with sufficient spatial and radiometric resolution for mapping lake water quality (Landsat 8 OLI and Sentinel-2 MSI) were launched recently. In order to test whether these satellites can capture the 810 nm peak we simulated the spectral performance of these two satellites from field radiometry data. Actual satellite imagery from a black lake was also used to study whether these sensors can detect the peak despite their band configuration. Sentinel 2 MSI has a nearly perfectly positioned band at 705 nm to characterize the 700-720 nm peak. We found that the MSI 783 nm band can be used to detect the 810 nm peak despite the location of this band is not in perfect to capture the peak.

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Section: Discussionmentioning

confidence: 99%

Remote Sensing of Black Lakes and Using 810 nm Reflectance Peak for Retrieving Water Quality Parameters of Optically Complex Waters

et al. 2016

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“…This paper will summarize how data were archived during remote sensing campaigns conducted in littoral areas surrounding the Virginia Coast Reserve (VCR), Marine Corps Base Hawaii (MCB-HI), and Shoalwater Bay Training Area (SWBTA) in Queensland, Australia. The first investigation used NRL's Compact Airborne Spectral Imager (CASI) (www.itres.com), a visible and near infra-red (VNIR) hyperspectral sensor, to study the barrier island coast and lagoons found along Cape Charles, Virginia [4], [5], [6], [7]. The second study occurred during January and February 2009 and involved analysis of the coralline coast surrounding Kaneohe and Waimanalo Bays in Hawaii.…”

Section: Introductionmentioning

confidence: 99%

Geodatabase development to support hyperspectral imagery exploitation

Fusina

Fry²,

Nichols³

et al. 2010

2010 IEEE International Geoscience and Remote Sensing Symposium

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Geodatabase development for coastal studies conducted by the Naval Research Laboratory (NRL) is essential to support the exploitation of hyperspectral imagery (HSI). NRL has found that the remote sensing and mapping science community benefits from coastal classifications that group coastal types based on similar features. Selected features in project geodatabases relate to significant biological and physical forces that shape the coast. The project geodatabases help researchers understand factors that are necessary for imagery post processing, especially those features having a high degree of temporal and spatial variability. NRL project geodatabases include a hierarchy of environmental factors that extend from shallow water bottom types and beach composition to inland soil and vegetation characteristics. These geodatabases developed by NRL allow researchers to compare features among coast types. The project geodatabases may also be used to enhance littoral data archives that are sparse. This paper highlights geodatabase development for recent remote sensing experiments in barrier island, coral, and mangrove coast types.

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“…MI-HARES'10 builds upon several projects completed by NRL-7232 at: During VCR'07, a multi-sensor airborne remote sensing suite of NRL Coastal and Ocean Remote Sensing Branch (Code 7230) instruments, including two hyperspectral cameras and a broad band mid-wave IR camera (Bachmann et al, 2008 and were flown aboard a Twin Otter aircraft. Results from VCR'07 were presented to the sponsors at a demonstration day at the conclusion of the exercise, and included the debut of a trafficability map product derived from airborne hyperspectral imagery (HSI) in a barrier island coastal environment.…”

Section: Introductionmentioning

confidence: 99%

Mariana Islands-Hyperspectral Airborne Remote Environmental Sensing Experiment 2010

Bachmann¹,

Montes²,

Fusina³

et al. 2012

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Standard Form 298 (Rev. 8-98)Prescribed by ANSI Std. Z39.18Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. This report describes the data collected during one of a series of Naval Research Laboratory (NRL) remote sensing and calibration and validation (Cal/Val) campaigns, providing data and information for the development of models of coast types and their associated environmental factors. Models allow rapid processing of hyperspectral imagery (HSI), generating shallow water bathymetric charts and trafficability maps. Cal/Val data collected during the Mariana Islands Hyperspectral Airborne Remote Environmental Sensing 2010 (MIHARES 2010) campaign focused on spectral and geotechnical library development, bathymetry, and location of WWII remnant hazards on Pagan, Tinian, and Guam. Ground control data collected during the remote sensing experiment will be useful in building digital elevation models and maps for remote areas such as Pagan, a volcanic island in the Commonwealth of the Northern Mariana Islands (CNMI). Surveyed calibration panels, WWII relics, and underwater panels are all useful in developing anomaly detection algorithms. The primary purpose of this memorandum report is to summarize imagery collections and all Cal/Val data and the project geodatabase, with products described in future publications. REPORT TYPE 1. REPORT DATE (DD-MM-YYYY) TITLE AND SUBTITLE AUTHOR(S) PERFORMING ORGANIZATION REPORT NUMBER PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) SPONSOR / MONITOR'S ACRONYM(S) 9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) SPONSOR / MONITOR'S REPORT NUMBER(S)

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Very Shallow Water Bathymetry Retrieval from Hyperspectral Imagery at the Virginia Coast Reserve (VCR'07) Multi-Sensor Campaign

Cited by 11 publications

References 8 publications

Remote Sensing of Black Lakes and Using 810 nm Reflectance Peak for Retrieving Water Quality Parameters of Optically Complex Waters

Remote Sensing of Black Lakes and Using 810 nm Reflectance Peak for Retrieving Water Quality Parameters of Optically Complex Waters

Geodatabase development to support hyperspectral imagery exploitation

Mariana Islands-Hyperspectral Airborne Remote Environmental Sensing Experiment 2010

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