2014
DOI: 10.1109/lgrs.2013.2287458
|View full text |Cite
|
Sign up to set email alerts
|

HICO-Based NIR–Red Models for Estimating Chlorophyll- $a$ Concentration in Productive Coastal Waters

Abstract: We present here results that demonstrate the potential of near-infrared (NIR)-red models to estimate chlorophyll-a (chl-a) concentration in coastal waters using data from the spaceborne Hyperspectral Imager for the Coastal Ocean (HICO). Since the recent demise of the MEdium Resolution Imaging Spectrometer (MERIS), the use of sensors such as HICO has become critical for coastal ocean color research. Algorithms based on two-and three-band NIR-red models, which were previously used very successfully with MERIS da… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
22
0
1

Year Published

2015
2015
2018
2018

Publication Types

Select...
6
1

Relationship

0
7

Authors

Journals

citations
Cited by 34 publications
(23 citation statements)
references
References 24 publications
0
22
0
1
Order By: Relevance
“…For satellite hyperspectral imagery this is more likely to occur over dark targets where there is a reduced signal-to-noise ratio with a higher proportion of atmospheric path radiance to the total at-sensor radiance. Here small errors in the sensor's radiometric calibration or inaccuracies in the atmospheric parameters used during atmospheric correction can significantly impact R sens rs (e.g., [59][60][61]). Bottom reflectance and benthic classification of hyperspectral imagery are products that can be generated using shallow water inversion models.…”
Section: Discussionmentioning
confidence: 99%
“…For satellite hyperspectral imagery this is more likely to occur over dark targets where there is a reduced signal-to-noise ratio with a higher proportion of atmospheric path radiance to the total at-sensor radiance. Here small errors in the sensor's radiometric calibration or inaccuracies in the atmospheric parameters used during atmospheric correction can significantly impact R sens rs (e.g., [59][60][61]). Bottom reflectance and benthic classification of hyperspectral imagery are products that can be generated using shallow water inversion models.…”
Section: Discussionmentioning
confidence: 99%
“…Unfortunately, both of these sensors have been plagued with issues, such as unreliable spectral and radiometric calibration [100] and their low signal-to-noise ratio (SNR), especially over bodies of water, and this often leads to poor retrievals [101,102], e.g., the SNR of Hyperion ranges between 50:1 and 150:1 [103]. As HICO was specifically developed for ocean colour sensing, its 128 bands, which cover a spectral range from 380-960 nm, capture with a reasonable SNR (>200:1 for water-penetrating wavelengths and assuming 5% albedo) [18].…”
Section: Sensor Resolutionsmentioning
confidence: 99%
“…For HICO to achieve accurate retrievals over turbid waters, measurements of the aerosol optical depth [112] and aerosol type [113] needed to be either estimated or measured from other sources, such as AERONET. Other limitations include the fact that HICO suffered from spectral shifts (of up to 1 nm) and a low radiometric sensitivity (especially below 450 nm) [102]; it was not designed for regular global coverage [114], and its location on the International Space Station only permitted data capture within the latitude range ≈ +54°/−53°(which covered around 80% of the Earth's surface) [115]. Radiometric resolution is defined as the minimum amount of radiance that each spectral band of a sensor can reliably measure, and it is determined by the way the data are digitally stored [26].…”
Section: Sensor Resolutionsmentioning
confidence: 99%
See 2 more Smart Citations