The monitoring, sampling and mapping of plastic waste in the water column and on the sea bottom represents a serious challenge for both responsible government authorities and scientific researchers. Typically, these activities are performed by divers equipped with the necessary recording equipment and special breathing mixtures when working at depths greater than 30 meters or more. The complexity, risk, respectively budget and time required for deeper diving increases due to the neediness of complying with safety of life and diving decompression procedures. This paper represents an approach of using underwater drones (ROV) for monitoring, sampling and mapping of plastic waste in the port aquatories, coastal zone and sea bottom.
In recent years, more and more attention has been focused to the pollution of the seas and oceans with plastic waste. It is no coincidence that monitoring and prevention activities and measures to reduce the pollution of seas and oceans with plastic waste occupy a major role in the EU Marine Strategy Framework Directive (EU MSFD). In accordance with Descriptor 10, plastic waste must be monitored, collected and reported regularly at European Union level. This paper represents possibilities for monitoring of plastic waste on the sea surface, using aerial drones equipped with thermal and multispectral cameras.
Intelligent agriculture increasingly relies on modern technologies for reliable monitoring of crops and timely detection of areas in which special intervention is needed to ensure the planned yields. This paper represents the results of a study of the possibilities of fusion and processing of multi-spectral and thermal data from satellite systems and such from remotely controlled platforms (drones) for the decision making support in intelligent agriculture. The study examined images with different resolutions, such as from the Sentinel-2, Landsat and Planet Labs satellite systems, as well as multi-spectral images from the commercial drones DJI Phantom 4 Multispectral and thermal images (thermograms) from the DJI Mavic 2 Enterprise Advanced.
KEYWORDS: Agriculture, Sensors, Thermography, Multispectral imaging, Long wavelength infrared, Data processing, Cameras, Image fusion, Data fusion, RGB color model
Nowadays, modern technologies are more and more accessible, cheaper and easier to use. Part of them are the multisensor remotely controlled aerial platforms or the so-called “drones”. This paper presents the results of a research for the possibilities of mixing and processing multi-spectral and thermal images from aerial drone sensors for the intelligent agriculture support. Time series of multi-spectral images from the DJI Phantom 4 Multispectral and thermal images from the DJI Mavic 2 Enterprise Advanced over same area are processed. An approach of a new methodology for data fusion of drone multispectral and thermal (LWIR) images data processing for intelligent agriculture support is proposed.
Unfortunately, the year 2023 began with a devastating earthquake unprecedented in recent years, spreading over the territories of two neighboring countries (Turkey and Syria) located on the same tectonic plate. On the night of February 6, 2023, Turkey and Syria were hit by a powerful 7.8 magnitude earthquake. The earthquake was one of the strongest in the region in more than a century. Even more devastation was caused by aftershocks that hit both countries hours later. A few days later, weaker earthquakes were reported in two other countries (Romania and Croatia) located on different with respect to first one, but neighboring, tectonic plate. This paper represents an approach for using change detection techniques based on free access high resolution Earth observation satellite data (Sentinel, Landsat) for assessment of the consequences caused by earthquakes in an urban area. Known change detection techniques have been investigated such as: image differencing, image rationing, change detection based on indexes calculation and comparison, etc. As a result, a comparative analysis of the investigated change detection techniques with respect to an urban area adequacy is presented.
In recent years, many reports have shown increasing pollution of the world's oceans with plastic waste, even the formation of plastic islands on the sea surface. Considering that marine currents are the major factor of the plastic waste movement into the marine environment, an approach for determining of sea surface flows using zonal and meridional components of ocean currents velocity data of “Physics analysis and forecast” products delivered by Copernicus Marine Service. By numerical modeling and simulations in MATLAB environment are derived sea surface flows which are considered to be the main transport routes of plastic waste on the sea surface. A georeferenced map, as a result of study focused on the West Black Sea aquatory is presented.
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