Geoinformatics & Geostatistics: An OverviewISSN: 2327-4581

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Short Communication, Geoinfor Geostat An Overview Vol: 11 Issue: 2

Remote Sensing Involved in Oceanographic Studies

Fatih Dur*

1Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, USA

*Corresponding Author: Fatih Dur,
Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, USA

Received date: 28 March, 2023, Manuscript No. GIGS-23-100508;

Editor assigned date: 30 March, 2023, PreQC No. GIGS-23-100508 (PQ);

Reviewed date: 13 April, 2023, QC No. GIGS-23-100508;

Revised date: 20 April, 2023, Manuscript No. GIGS-23-100508 (R);

Published date: 27 April, 2023, DOI: 10.4172/ 2327-4581.1000329

Citation: Dur F (2023) Remote Sensing Involved in Oceanographic Studies. Geoinfor Geostat: An Overview 11:2.


Oceanography, the study of the Earth's oceans, is a complex field that requires extensive data collection to understand the dynamics of the marine environment. In recent decades, remote sensing has emerged as a powerful tool in oceanographic studies, enabling scientists to gather valuable information about the oceans from space.

Satellite-based remote sensing

Satellite-based remote sensing involves the use of specialized sensors mounted on satellites to observe and measure various properties of the oceans [1]. These sensors capture data in different wavelengths of the electromagnetic spectrum, including visible, infrared, and microwave regions. Here are some key remote sensing applications in oceanography:

Sea Surface Temperature (SST) mapping: Remote sensing satellites can measure the temperature of the ocean surface with high precision. By analyzing variations in sea surface temperature, scientists gain insights into ocean circulation patterns, identify oceanic fronts, and monitor phenomena like El Niño and La Niña events [2]. SST mapping helps in understanding the impact of climate change on the oceans and assists in predicting weather patterns.

Ocean color monitoring: The color of the ocean's surface is an indicator of the presence and concentration of phytoplankton, which are microscopic marine plants that form the base of the oceanic food chain [3]. Remote sensing enables the measurement of ocean color, which is influenced by the chlorophyll content in the water. By monitoring changes in ocean color, scientists can assess the health of marine ecosystems, track harmful algal blooms, and study the carbon cycle.

Sea surface height and ocean currents: Remote sensing satellites equipped with altimeters measure the height of the ocean surface with remarkable accuracy [4]. By detecting small changes in sea surface height, scientists can infer ocean currents, identify eddies, and study the movement of large-scale oceanic features like the Gulf Stream. Understanding ocean currents is crucial for climate modeling, navigation, and fisheries management.

Ocean salinity and sea ice monitoring: Remote sensing sensors can also estimate the salinity of the oceans by measuring microwave radiation emitted by seawater [5]. This information helps in understanding the distribution of saltwater, studying ocean circulation patterns, and monitoring changes in ocean currents. Additionally, remote sensing plays a vital role in monitoring sea ice extent, thickness, and movement in polar regions, providing important data for climate studies and ecological research.

Airborne remote sensing

In addition to satellite-based remote sensing, airborne platforms such as aircraft and drones are used in oceanographic research [6]. These platforms carry specialized sensors that collect high-resolution data with greater flexibility and spatial coverage. Airborne remote sensing allows for detailed observations of coastal zones, coral reefs, and other ecologically important areas that require higher spatial resolution than satellite sensors can provide.

Data integration and analysis

The wealth of remote sensing data collected from satellites and airborne platforms is integrated with in situ measurements and oceanographic models for comprehensive analysis [7,8]. Advanced data processing techniques, such as image classification, data fusion, and machine learning, are applied to extract meaningful information from the remote sensing data. This integrated approach enhances our understanding of ocean processes, improves oceanographic models, and contributes to effective coastal management and marine conservation.

Advancements and future directions

The field of remote sensing in oceanographic research is rapidly advancing. Ongoing technological advancements are improving the spatial and temporal resolution of remote sensing sensors, allowing for more detailed observations of the oceans. The integration of multiple remote sensing data sources, along with other Earth-observing systems, is enhancing the multidimensional understanding of the marine environment [9,10]. Additionally, the development of autonomous underwater vehicles and underwater imaging technologies is complementing remote sensing by providing detailed observations of the ocean's interior.


Remote sensing has revolutionized oceanographic research by providing valuable data on various oceanic parameters from a global perspective. Satellite-based and airborne remote sensing techniques offer unique capabilities to monitor sea surface temperature, ocean color, sea surface height, salinity, and other essential oceanographic parameters. By leveraging these technologies, scientists can gain insights into the complex dynamics of the oceans, monitor changes in marine ecosystems, and contribute to effective ocean management and conservation efforts. As remote sensing technology continues to evolve, it holds tremendous potential for further advancements in our understanding of the oceans and their crucial role in shaping our planet's climate and biodiversity.


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