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Search results for: SATELLITE IMAGES
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Classification of Sea Going Vessels Properties Using SAR Satellite Images
PublicationThe aim of the project was to analyze the possibility of using machine learning and computer vision to identify (indicate the location) of all sea-going vessels located in the selected area of the open sea and to classify the main attributes of the vessel. The key elements of the project were to download data from the Sentinel-1 satellite [1], download data on the sea vessels [2], then automatically tag data and develop a detection...
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Operational Enhancement of Numerical Weather Prediction with Data from Real-time Satellite Images
PublicationNumerical weather prediction (NWP) is a rapidly expanding field of science, which is related to meteorology, remote sensing and computer science. Authors present methods of enhancing WRF EMS (Weather Research and Forecast Environmental Modeling System) weather prediction system using data from satellites equipped with AMSU sensor (Advanced Microwave Sounding Unit). The data is acquired with Department of Geoinformatics’ ground...
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Temporal Satellite Images in The Process of Automatic Efficient Detection of Changes of the Baltic Sea Coastal Zone
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Particle Filter Modification using Kalman Optimal Filtering Method as Applied to Road Detection from Satellite Images
PublicationIn the paper recursive state estimation approach is presented as applied to satellite images. Especially, a model of dynamic systems of the non-linear and non-Gaussian systems is presented, and finally the Kalman filter and particle filter and an integration of both is figured out. Special attention is paid to the application for satellite image analysis.
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A method of selecting light sources from night satellite scenes
PublicationSatellite images carries a lot of data. Very sophisticated methods of analyses may reveal very complicated nature of the observed objects. In case of night images, lights play the role of information sources. In this paper we would like to present results of the research aimed to describe light sources from satellite night images by providing description of their luminosity. The authors point source imaging data from the satellite...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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The Application of Satellite Image Analysis in Oil Spill Detection
PublicationIn recent years, there has been an increasing use of satellite sensors to detect and track oil spills. The satellite bands, namely visible, short, medium infrared, and microwave radar bands, are used for this purpose. The use of satellite images is extremely valuable for oil spill analysis. With satellite images, we can identify the source of leakage and assess the extent of potential damage. However, it is not yet clear how to...
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Study on the Coastline Evolution in Sopot (2008–2018) Based on Landsat Satellite Imagery
PublicationThe coastline is the boundary between the water surface in a reservoir or watercourse and the land, which is characterised by high instability and functional diversity. For these reasons, research on coastal monitoring has been conducted for several decades. Currently, satellite images performed with synthetic aperture radars (SARs) are used to determine its course and variability together with high-resolution multispectral imagery...
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Processing of Satellite Data in the Cloud
PublicationThe dynamic development of digital technologies, especially those dedicated to devices generating large data streams, such as all kinds of measurement equipment (temperature and humidity sensors, cameras, radio-telescopes and satellites – Internet of Things) enables more in-depth analysis of the surrounding reality, including better understanding of various natural phenomenon, starting from atomic level reactions, through macroscopic...
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Analysis of the objects images on the sea using Dempster-Shafer Theory
PublicationThe paper presents the concept of using aerial and satellite imagery or images coming from the marine radar to identify and track vessels at sea. The acquired data were subjected to a highly advanced image analysis. The development of remote sensing techniques allows to gain a huge amount of data. These data are useful information source however usually we have to use different data mining methods to gain interested information....
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Input files for the Floodsar software
Open Research DataInput files for the Floodsar softwareAuthor: Tomasz Berezowski, Gdansk University of Technology, tomberez@eti.pg.edu.pl
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Monthly mean concentration of chlorophyll a on the sea surface of the Baltic Sea
Open Research DataMonthly mean surface concentration of chlorophyll a in the years 2003-2022 calculated on the basis of data from the SatBaltic System (https://satbaltyk.iopan.gda.pl/). Maps of monthly average values with a resolution of 1 km were derived from daily satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Gaps in satellite images...
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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublicationIn remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image analysis for change detection, yet many of them have limitations, including the overfitting problem. This research proposes the Feature Weighted Attention (FWA) in Bidirectional Long...
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Towards Precise Visual Navigation and Direct Georeferencing for MAV Using ORB-SLAM2
PublicationA low accuracy of positioning using Global Navigation Satellite System (GNSS) are not meet geodetic requirements for direct images georeferencing for Unmanned Aerial Vehicle (UAV) photogrammetry. A majority of UAVs are equipped with a monocular or stereo non-metric cameras for either visual data gathering or live video feed for operator. A cheap positioning techniques used on board commercial UAVs are not that precise as geodetic...
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Monthly mean sea surface temperature (SST) of the Baltic Sea
Open Research DataMonthly mean sea surface temperature (SST) from 2001 to 2022 calculated from data from the SatBaltic System (https://satbaltyk.iopan.gda.pl/). The spatial resolution of the maps is 1 km. The calculation of monthly mean values at each pixel was based on four SST maps on each day of the month. The primary source of SST information was satellite data collected...
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Modeling and Accuracy Assessment of Determining the Coastline Course Using Geodetic, Photogrammetric and Satellite Measurement Methods: Case Study in Gdynia Beach in Poland
PublicationThe coastal environment represents a resource from both a natural and economic point of view, but it is subject to continuous transformations due to climate change, human activities, and natural risks. Remote sensing techniques have enormous potential in monitoring coastal areas. However, one of the main tasks is accurately identifying the boundary between waterbodies such as oceans, seas, lakes or rivers, and the land surface....
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Validation of Interpolation Algorithms for Multiscale UV-VIS Imaging Using UAV Spectrometer
PublicationIn this study, we present a comparison of popular methods for the interpolation of irregular spatial data in order to determine the applicability of each algorithm for hyperspectral reflectance estimation. The algorithms were benchmarked against a very high-resolution orthoimage from an RGB camera and medium-resolution satellite imagery from Sentinel-2A. We tested five interpolation algorithms: Triangulated Irregular Network (TIN),...
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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublicationCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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Analysis of Methods for Determining Shallow Waterbody Depths Based on Images Taken by Unmanned Aerial Vehicles
PublicationHydrographic surveys enable the acquisition and processing of bathymetric data, which after being plotted onto nautical charts, can help to ensure safety of navigation, monitor changes in the coastal zone, and assess hydro-engineering structure conditions. This study involves the measurement of waterbody depth, identification of the seabed shape and geomorphology, the coastline course, and the location of underwater obstacles....
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Spiral Search Grasshopper Features Selection with VGG19-ResNet50 for Remote Sensing Object Detection
PublicationRemote sensing object detection plays a major role in satellite imaging and is required in various scenarios such as transportation, forestry, and the ocean. Deep learning techniques provide efficient performance in remote sensing object detection. The existing techniques have the limitations of data imbalance, overfitting, and lower efficiency in detecting small objects. This research proposes the spiral search grasshopper (SSG)...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublicationIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Detecting Apples in the Wild: Potential for Harvest Quantity Estimation
PublicationKnowing the exact number of fruits and trees helps farmers to make better decisions in their orchard production management. The current practice of crop estimation practice often involves manual counting of fruits (before harvesting), which is an extremely time-consuming and costly process. Additionally, this is not practicable for large orchards. Thanks to the changes that have taken place in recent years in the field of image...
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Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk
PublicationSatellite imaging systems have known limitations regarding their spatial and temporal resolution. The approaches based on subpixel mapping of the Earth’s environment, which rely on combining the data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution, are of considerable interest. The paper presents the downscaling process of the land...
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Identification of Shift in Sowing and Harvesting Dates of Rice Crop (L. Oryza sativa) through Remote Sensing Techniques: A Case Study of Larkana District
PublicationThe present study aimed to determine the impact of climate variability on rice crops in terms of sowing and harvesting dates and crop period. The identification of sowing and harvesting dates were spotted by mask identification, variations in land surface temperature (LST) on a temporal scale in the respective months, and a field-level social inquiry. The study was conducted during a time period (1994–2017), in which geo-referenced...
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The Impact of Spatiotemporal Changes in Land Development (1984–2019) on the Increase in the Runoff Coefficient in Erbil, Kurdistan Region of Iraq
PublicationNowadays, geospatial techniques are a popular approach for estimating urban flash floods by considering spatiotemporal changes in urban development. In this study, we investigated the impact of Land Use/Land Cover (LULC) changes on the hydrological response of the Erbil basin in the Kurdistan Region of Iraq (KRI). In the studied area, the LULC changes were calculated for 1984, 1994, 2004, 2014 and 2019 using the Digital Elevation...
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GPU based implementation of Temperature-Vegetation Dryness Index for AVHRR3 Satellite Data
PublicationPaper presents an implementation of TVDI (Temperature-Vegetation-Dryness Index) algorithm on GPU (Graphics Processing Unit). Calculation of this index is based on LST (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index). Discussed results are based on multi-spectral imagery retrieved from AVHRR3 sensors for area of Poland. All phases of TVDI implementation on GPU are modified in respect to CUDA platform....
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Mathematical Modeling of Ice Dynamics as a Decision Support Tool in River Engineering
PublicationThe prediction of winter flooding is a complicated task since it is affected by many meteorological and hydraulic factors. Typically, information on river ice conditions is based on historical observations, which are usually incomplete. Recently, data have been supplemented by information extracted from satellite images. All the above mentioned factors provide a good background of the characteristics of ice processes, but are not...
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Exploring the Beam Squint Effects on Reflectarray Perfromance: A Comprehensive Analysis of the Specular and Scattered Reflection of the Unit Cell
PublicationIn this article, the phenomena of beam deviation in reflectarray is discussed. The radiation pattern of the unit cell, which plays a vital role in shaping the beam of the reflectarray, is analyzed by considering undesired specular and scattered reflections. These unwanted reflections adversely affect the pattern of the single unit cell, thereby reducing the overall performance of the reflectarray. To conduct our investigations,...
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Distribution and extent of benthic habitats in Puck Bay (Gulf of Gdańsk, southern Baltic Sea)
PublicationThe majority of the southern Baltic Sea seabed encompasses homogenous soft-bottom sediments of limited productivity and low biological diversity, but shallow productive areas in the coastal zone such as wetlands, vegetated lagoons and sheltered bays show a high variety of benthic habitat types offering favourable biotopic conditions for benthic fauna. Within Polish marine areas, semi-enclosed Puck Bay (the western part of the...
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Sea surface temperature in the Baltic Sea derived from Landsat 8 satellite data - path 194
Open Research DataThe data set contains high resolution sea surface temperature (SST) maps estimated from Landsat 8 Level 1 Thermal Infrared Sensor (TIRS) data using NLSST algorithm. SST was calculated only for granules (185 x 180 km) from satellite path number 194, that covered at least 2000 km2 of the cloud-free area of the Baltic Sea.
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Sea surface temperature in the Baltic Sea derived from Landsat 8 satellite data - path 192
Open Research DataThe data set contains high resolution sea surface temperature (SST) maps estimated from Landsat 8 Level 1 Thermal Infrared Sensor (TIRS) data using NLSST algorithm. SST was calculated only for granules (185 x 180 km) from satellite path number 192, that covered at least 2000 km2 of the cloud-free area of the Baltic Sea.
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Sea surface temperature in the Baltic Sea derived from Landsat 8 satellite data - path 191
Open Research DataThe data set contains high resolution sea surface temperature (SST) maps estimated from Landsat 8 Level 1 Thermal Infrared Sensor (TIRS) data using NLSST algorithm. SST was calculated only for granules (185 x 180 km) from satellite path number 191, that covered at least 2000 km2 of the cloud-free area of the Baltic Sea.
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Sea surface temperature in the Baltic Sea derived from Landsat 8 satellite data - path 193
Open Research DataThe data set contains high resolution sea surface temperature (SST) maps estimated from Landsat 8 Level 1 Thermal Infrared Sensor (TIRS) data using NLSST algorithm. SST was calculated only for granules (185 x 180 km) from satellite path number 193, that covered at least 2000 km2 of the cloud-free area of the Baltic Sea.
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Sea surface temperature in the Baltic Sea derived from Landsat 8 satellite data - path 190
Open Research DataThe data set contains high resolution sea surface temperature (SST) maps estimated from Landsat 8 Level 1 Thermal Infrared Sensor (TIRS) data using NLSST algorithm. SST was calculated only for granules (185 x 180 km) from satellite path number 190, that covered at least 2000 km2 of the cloud-free area of the Baltic Sea.
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Free-air anomaly grid on the Gulf of Gdańsk
Open Research DataWe present an attempt to determine the accuracy of shipborne gravimetry for the needs of geoid determination. The shipborne gravity campaign, is the beginning of a series of gravimetry measurements in the Polish Exclusive Economy Zone. The campaign was conducted in the area where the accuracy of geoid determination is crucial for the safety of navigation...
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AVHRR Level1CD covering Baltic Sea area year 2001
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
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AVHRR Level1CD covering Baltic Sea area year 2005
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
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AVHRR Level1CD covering Baltic Sea area year 2004
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
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AVHRR Level1CD covering Baltic Sea area year 2003
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
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AVHRR Level1CD covering Baltic Sea area year 2002
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
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Papillary and follicular carcinoma - Not available, 59 - Tissue image [3300730069481581]
Open Research DataThis is the histopathological image of THYROID GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Papillary and follicular carcinoma - Not available, 59 - Tissue image [3300730069487851]
Open Research DataThis is the histopathological image of THYROID GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Papillary and follicular carcinoma - Not available, 59 - Tissue image [3300730069491591]
Open Research DataThis is the histopathological image of THYROID GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Papillary and follicular carcinoma - Not available, 59 - Tissue image [3300730069485271]
Open Research DataThis is the histopathological image of THYROID GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Papillary and follicular carcinoma - Not available, 59 - Tissue image [3300730069489831]
Open Research DataThis is the histopathological image of THYROID GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Papillary and follicular carcinoma - Not available, 59 - Tissue image [3300730069484831]
Open Research DataThis is the histopathological image of THYROID GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Papillary and follicular carcinoma - Not available, 59 - Tissue image [3300730069485401]
Open Research DataThis is the histopathological image of THYROID GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Papillary and follicular carcinoma - Not available, 59 - Tissue image [3300730069482681]
Open Research DataThis is the histopathological image of THYROID GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Papillary and follicular carcinoma - Not available, 59 - Tissue image [3300730069489181]
Open Research DataThis is the histopathological image of THYROID GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.