Simplifying Regional Tuning of MODIS Algorithms for Monitoring Chlorophyll-a in Coastal Waters

Jiang, Weimin; Knight, Ben; Cornelisen, Chris; Barter, Paul; Kudela, Raphael M.

doi:10.3389/fmars.2017.00151

Cited by 13 publications

(8 citation statements)

References 32 publications

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“…The regional algorithms also had a higher correlation coefficient than the original methods for all sensors, all algorithms. The RMSLE exhibited values (from 0.29 to 0.47) that were in agreement with values reported in the literature for regional algorithms for the retrieval of chla [40][41][42]. Tuned algorithms showed smaller RMSLE than original algorithms for both semi-analytical and band ratio approaches except for the GSM approaches for VIIRS.…”

Section: Algorithms Performance In the Nwasupporting

confidence: 88%

Evaluation of Satellite-Based Algorithms to Retrieve Chlorophyll-a Concentration in the Canadian Atlantic and Pacific Oceans

et al. 2019

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Remote-sensing reflectance data collected by ocean colour satellites are processed using bio-optical algorithms to retrieve biogeochemical properties of the ocean. One such important property is the concentration of chlorophyll-a, an indicator of phytoplankton biomass that serves a multitude of purposes in various ocean science studies. Here, the performance of two generic chlorophyll-a algorithms (i.e., a band ratio one, Ocean Colour X (OCx), and a semi-analytical one, Garver–Siegel Maritorena (GSM)) was assessed against two large in situ datasets of chlorophyll-a concentration collected between 1999 and 2016 in the Northeast Pacific (NEP) and Northwest Atlantic (NWA) for three ocean colour sensors: Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS). In addition, new regionally-tuned versions of these two algorithms are presented, which reduced the mean error (mg m−3) of chlorophyll-a concentration modelled by OCx in the NWA from −0.40, −0.58 and −0.45 to 0.037, −0.087 and −0.018 for MODIS, SeaWiFS, and VIIRS respectively, and −0.34 and −0.36 to −0.0055 and −0.17 for SeaWiFS and VIIRS in the NEP. An analysis of the uncertainties in chlorophyll-a concentration retrieval showed a strong seasonal pattern in the NWA, which could be attributed to changes in phytoplankton community composition, but no long-term trends were found for all sensors and regions. It was also found that removing the 443 nm waveband for the OCx algorithms significantly improved the results in the NWA. Overall, GSM performed better than the OCx algorithms in both regions for all three sensors but generated fewer chlorophyll-a retrievals than the OCx algorithms.

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Section: Algorithms Performance In the Nwasupporting

confidence: 88%

Evaluation of Satellite-Based Algorithms to Retrieve Chlorophyll-a Concentration in the Canadian Atlantic and Pacific Oceans

et al. 2019

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“…Here, we hypothesize that the translation of a land-cover element may co-variate with its spatial coordinates (latitude and longitude). This assumption is in line with the current practices in large-scale land-cover classification approaches in the remote sensing community: it is implicitly performed by either locally fine-tuning a global classification model or by defining distinct local models based on a specific stratification strategy [44,58]. Thus, we decide to incorporate into our network a positional encoding sub-module to take into account the coordinates of each patch during the translation process.…”

Section: Geographical Contextmentioning

confidence: 88%

Toward a Yearly Country-Scale CORINE Land-Cover Map without Using Images: A Map Translation Approach

2021

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CORINE Land-Cover (CLC) and its by-products are considered as a reference baseline for land-cover mapping over Europe and subsequent applications. CLC is currently tediously produced each six years from both the visual interpretation and the automatic analysis of a large amount of remote sensing images. Observing that various European countries regularly produce in parallel their own land-cover country-scaled maps with their own specifications, we propose to directly infer CORINE Land-Cover from an existing map, therefore steadily decreasing the updating time-frame. No additional remote sensing image is required. In this paper, we focus more specifically on translating a country-scale remote sensed map, OSO (France), into CORINE Land Cover, in a supervised way. OSO and CLC not only differ in nomenclature but also in spatial resolution. We jointly harmonize both dimensions using a contextual and asymmetrical Convolution Neural Network with positional encoding. We show for various use cases that our method achieves a superior performance than the traditional semantic-based translation approach, achieving an 81% accuracy over all of France, close to the targeted 85% accuracy of CLC.

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“…The model tended to slightly overestimate SST in the region of the South Equatorial Counter Current (SECC) (2 • S-2 • N) and underestimates SST around the islands (Figure 5 and Table 1) particularly the shelf area between India and Sri Lanka by a mean difference of <2 • C (Figure 5). This discrepancy could be due to the bottom reflectance from the shallow depth in this shelf region (<10 m) which has been known to affect the estimation of MODIS measurements (Jiang et al, 2017). Conversely, the overestimation of temperatures occurred closer to the SECC region (Figure 5).…”

Section: Sea Surface Temperaturementioning

confidence: 94%

Monsoon Influence on the Island Mass Effect Around the Maldives and Sri Lanka

Wijeratne

Pattiaratchi

2021

Front. Mar. Sci.

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The monsoon circulation in the Northern Indian Ocean (NIO) is unique since it develops in response to the bi-annual reversing monsoonal winds, with the ocean currents mirroring this change through directionality and intensity. The interaction between the reversing currents and topographic features have implications for the development of the Island Mass Effect (IME) in the NIO. The IME in the NIO is characterized by areas of high chlorophyll concentrations identified through remote sensing to be located around the Maldives and Sri Lanka in the NIO. The IME around the Maldives was observed to reverse between the monsoons to downstream of the incoming monsoonal current whilst a recirculation feature known as the Sri Lanka Dome (SLD) developed off the east coast of Sri Lanka during the Southwest Monsoon (SWM). To understand the physical mechanisms underlying this monsoonal variability of the IME, a numerical model based on the Regional Ocean Modeling System (ROMS) was implemented and validated. The model was able to simulate the regional circulation and was used to investigate the three-dimensional structure of the IME around the Maldives and Sri Lanka in terms of its temperature and velocity. Results revealed that downwelling processes were prevalent along the Maldives for both monsoon periods but was applicable only to latitudes above 4°N since that was the extent of the monsoon current influence. For the Maldives, atolls located south of 4°N, were influenced by the equatorial currents. Around Sri Lanka, upwelling processes were responsible for the IME during the SWM but with strong downwelling during the NEM. In addition, there were also regional differences in intra-seasonal variability for these processes. Overall, the strength of the IME processes was closely tied to the monsoon current intensity and was found to reach its peak when the monsoon currents were at the maximum.

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Simplifying Regional Tuning of MODIS Algorithms for Monitoring Chlorophyll-a in Coastal Waters

Cited by 13 publications

References 32 publications

Evaluation of Satellite-Based Algorithms to Retrieve Chlorophyll-a Concentration in the Canadian Atlantic and Pacific Oceans

Evaluation of Satellite-Based Algorithms to Retrieve Chlorophyll-a Concentration in the Canadian Atlantic and Pacific Oceans

Toward a Yearly Country-Scale CORINE Land-Cover Map without Using Images: A Map Translation Approach

Monsoon Influence on the Island Mass Effect Around the Maldives and Sri Lanka

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