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Abstract
The contemporary scientific literature that deals with the dynamics of marine chlorophyll-a concentration is already customarily employing data mining techniques in small geographic areas or regional samples. However, there is little focus on the issue of missing data related to chlorophyll-a concentration estimated by remote sensors. Intending to provide greater scope to the identification of the spatiotemporal distribution patterns of marine chlorophyll-a concentrations, and to improve the reliability of results, this study presents a data mining approach to cluster similar chlorophyll-a concentration behaviors while implementing an iterative spatiotemporal interpolation technique for missing data inference. Although some dynamic behaviors of said concentrations in specific areas are already known by specialists, systematic studies in large geographical areas are still scarce due to the computational complexity involved. For this reason, this study analyzed 18 years of NASA satellite observations in one portion of the Western Atlantic Ocean, totaling more than 60 million records. Additionally, performance tests were carried out in low-cost computer systems to check the accessibility of the proposal implemented for use in computational structures of different sizes. The approach was able to identify patterns with high spatial resolution, accuracy and reliability, rendered in low-cost computers even with large volumes of data, generating new and consistent patterns of spatiotemporal variability. Thus, it opens up new possibilities for data mining research on a global scale in this field of application.
Highlights
At a global level, phytoplankton organisms are responsible for net primary production of 50 petagrams of carbon per year [1] and chlorophyll-a concentrations in the ocean, commonly used as a proxy of phytoplankton biomass, become an important variable in the ecological study of marine and coastal environments.When interacting with electromagnetic radiation in the visible range (400 700 nm), phytoplankton absorbs more energy at the wavelength of the blue region (400 - 500 nm) and reflects more in the green region (500 - 600 nm) [2]
Regarding the smaller matrices, such as the climatology with average values, the Ultrabook Dell completed it in 1 hour, the Xeon Server in 2.5 hours and the Ultrabook Positivo in 24 hours
More than one mode of spatiotemporal variability was found for chlorophyll-a concentrations within each biogeochemical province in the Atlantic Ocean
Summary
When interacting with electromagnetic radiation in the visible range (400 700 nm), phytoplankton absorbs more energy at the wavelength of the blue region (400 - 500 nm) and reflects more in the green region (500 - 600 nm) [2] This relationship between absorbed and reflected energy in the blue and green bands provides the basis for quantifying the concentrations of said energy in the oceans by means of Remote Sensing at the orbital level. The works of [3] [4] [5] showed the importance of chlorophyll-a concentrations by remote sensing in the demarcation of marine ecoregions These regions provide an understanding of the interaction and control mechanisms of physical, chemical and biological processes that reflect the diversity of the ocean environment. Due to orbital satellite sensors, finer spatial resolution products are available, of approximately 4 km or 9 km; this allows for more accurate discrimination of oceanic regions that have seasonal and temporal variability characteristics of chlorophyll-a
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