Objects outline delineation by nonliniear filtration methods for boundary pixels by D. V. Zaerko, V. A. Lipnitski, N. L. Bobrova, Dm. V. Zaerko

“…Analysis, the influence of the algorithm for the outline objects segmentation on the boundary pixels from the preliminary selection of methods of redefinition is carried out by example of combining several satellite images along the outline of urban infrastructure. …”
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The role of urban transport corridors in the formation of agglomerations by A. G. Levashev

“…For the territory of Irkutsk agglomeration, which includes Irkutsk city as the main core of agglomeration, satellite cities Angarsk and Shelekhov and the surrounding territory of Irkutsk district, approaches to the formation of a unified transport model of agglomeration as the main tool for assessing transport demand, analyzing the distribution of traffic flows and indicators of the effectiveness of measures to develop the territories of transport corridors and the territories served by them are proposed. …”
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Wildfire Susceptibility Mapping using NBR Index and Frequency Ratio Model by Farzad Bolouk Heidari, Ramin Arfania

“…The locations of eight-year fire points from 2013 to 2020 of Nova satellite sensor VIIRS were received and the fire map of each was constructed using the NBR (Normalized Burn Ratio). …”
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Drought Vulnerability Characterization and Nature-Based Adaptation, Eerer Sub-Basin, Eastern Ethiopia by Asfaw Kebede Kassa, Dejene W. Sintayehu, Negash Tessema, Bekele Girma, Jemal Yousuf

“…Moreover, it proposed a long-term strategy to integrating NbS into disaster risk reduction plans by leveraging multi-sensor satellite data and other sources. The Analytical Hierarchy Process (AHP), Geographic Information System (GIS) and Remote Sensing (RS) were employed to evaluate drought vulnerability in the study area. …”
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Environmental threats and risks to protected areas in the context of war (case study of Molochnyi Lyman) by L. A. Horoshkovа, Y. D. Korniichuk

“…System analysis, remote sensing data were used, specifically satellite images from Landsat 5, Landsat 8, Sentinel-2, and the software tool Google Earth Engine. …”
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Coastal Inlet Analysis by Image Color Intensity Variations: Implications for the Barrier Coast of Ukraine by Ilya V. Buynevich, Oleksiy V. Davydov, Duncan M. FitzGerald

“…Increasingly, remote sensing technologies (aerial and satellite imagery, small unmanned aerial vehicles, etc.) are employed as sources of high-definition spatial databases. …”
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Reconstruction of Sea Surface Chlorophyll-a Concentration in the Bohai and Yellow Seas Using LSTM Neural Network by Qing Xu, Guiying Yang, Xiaobin Yin, Tong Sun

“…In order to improve the spatiotemporal coverage of satellite Chlorophyll-a (Chl-a) concentration products in marginal seas, a physically constrained deep learning model was established in this work to reconstruct sea surface Chl-a concentration in the Bohai and Yellow Seas using a Long Short-Term Memory (LSTM) neural network. …”
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Performance of Three Reanalysis Precipitation Datasets over the Qinling-Daba Mountains, Eastern Fringe of Tibetan Plateau, China by Gefei Wang, Xiaowen Zhang, Shiqiang Zhang

“…Although the evaluation of satellite precipitation data in this region has been performed, another kind of popular precipitation product-reanalysis dataset has not been assessed in depth. …”
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FTA: A Feature Tracking Empirical Model of Auroral Precipitation by Chen Wu, Aaron J. Ridley, Anna D. DeJong, Larry J. Paxton

“…Predictions from the FTA and two other auroral models were compared to the measurements by the Defense Meteorological Satellite Program Special Sensor Ultraviolet Spectrographic Imagers (SSUSI) on March 17, 2013. …”
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Atmospheric Methane Condition over the South Sumatera Peatland during the COVID-19 Pandemic by Muhammad Rendana, Wan Mohd Razi Idris, Sahibin Abdul Rahim

“…To evaluate the effects of anthropogenic activity on peatlands, we investigated the CH4 concentrations in the atmosphere above the tropical peatlands of the Indonesian province South Sumatra before the LSSR (March 2020), during the LSSR (May 2020), and during the corresponding months of the previous year (March and May 2019). Using satellite-retrieved data from NASA, viz., the CH4 concentration and gross primary production (GPP) measured by the Atmospheric Infrared Sounder (AIRS) on board Aqua and Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra, respectively, we discovered a decrease of approximately 5.5% in the mean CH4 concentration (which averaged 1.73 ppm across the periods prior to lockdown) as well as an increase in the GPP (which ranged from 53.3 to 63.9 g C m−2 day−1 during the lockdown, indicating high atmospheric carbon intake) during the LSSR. …”
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Vision-Based Object Recognition and Precise Localization for Space Body Control by Zeyu Shangguan, Lingyu Wang, Jianquan Zhang, Wenbo Dong

“…The space motion control is an important issue on space robot, rendezvous and docking, small satellite formation, and some on-orbit services. The motion control needs robust object detection and high-precision object localization. …”
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Association of Catharanthus yellow mosaic virus and a novel Tomato leaf curl Lucknow betasatellite with papaya leaf curl disease (PaLCD) in India by Priyanka, Yusuf Akhter, Sangeeta Saxena

“…Molecular characterization revealed the presence of a begomovirus and associated satellite molecules. Analysis of the full-length DNA-A component of one begomovirus isolate (PP998006) showed a 93 % nucleotide similarity with Catharanthus yellow mosaic virus (CaYMV). …”
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Tourism-Induced Land Use Transformations, Urbanisation, and Habitat Degradation in the Phu Quoc Special Economic Zone by Can Trong Nguyen, Nigel K. Downes, Asamaporn Sitthi, Chudech Losiri

“…Using multi-temporal Landsat satellite imagery and random forest classification, we quantify LULCCs and assess the environmental consequences of urban expansion on habitat degradation and intensification of the island’s thermal environment, focusing on land surface temperature (LST) changes. …”
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STURM-Flood: a curated dataset for deep learning-based flood extent mapping leveraging Sentinel-1 and Sentinel-2 imagery by Nicla Notarangelo, Charlotte Wirion, Frankwin van Winsen

“…This study introduces the STURM-Flood dataset, a high-quality, open-access, and DL-ready resource for flood extent mapping using Sentinel-1 and Sentinel-2 satellite imagery, combined with ground-truth data from the Copernicus Emergency Management Service. …”
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Exploring the Potential of Neural Networks to Predict Statistics of Solar Wind Turbulence by Daniel Wrench, Tulasi N. Parashar, Ritesh K. Singh, Marcus Frean, Ramesh Rayudu

“…For example, in the context of space physics, calibration issues, satellite telemetry issues, and unexpected events can make parts of a time series unusable. …”
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Test of the RUSLE and Key Influencing Factors Using GIS and Probability Methods: A Case Study in Nanling National Nature Reserve, South China by Jun Wang, Qian He, Ping Zhou, Qinghua Gong

“…We then used consecutive Landsat 8 satellite images to obtain the spatial distribution of four types of soil erosion and carried out ground truth checking of the RUSLE. …”
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Investigating Mechanisms Driving Differences in the Characteristics of Precipitation in the E3SM Multiscale Modeling Framework With 2D Versus 3D Cloud Resolving Model Configuration... by Wei‐Ching Hsu, Gabriel J. Kooperman, Walter M. Hannah

“…Our results show that tropical mean precipitation patterns are better represented in 3dMMF compared to observations (Integrated Multi‐satellitE Retrivals for GPM and Global Precipitation Climatology Project One Degree Daily products), while 2dMMF better captures extreme precipitation intensity, with systematic land‐ocean differences in precipitation and cloud‐associated variables. …”
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Estimation of PM10 and PM2.5 Using Backscatter Coefficient of Ceilometer and Machine Learning by Bu-Yo Kim, Joo Wan Cha, Yong Hee Lee

“…The estimation of PM10 and PM2.5 for the test data set was more accurate than that in previous studies that used satellite and ground-based meteorological data (bias = 0.10 µg m−3, root mean square error (RMSE) = 14.44 µg m−3, and R = 0.92 for PM10; and bias = 0.12 µg m−3, RMSE = 7.16 µg m−3, and R = 0.91 for PM2.5). …”
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Response of the Ionospheric TEC to SSW and Associated Geomagnetic Storm Over the American Low Latitudinal Sector by J. B. Fashae, O. S. Bolaji, A. B. Rabiu

“…We used 12 Global Positioning System (GPS) receivers, a pair of magnetometers, and the NASA Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite airglow instrument to unveil the total electron content (TEC), inferred vertical drift, and the changes in the neutral composition, respectively. …”
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An innovative framework for incorporating iPhone LiDAR point cloud in digitized documentation of road operations by Srikulnath Nilnoree, Tsukasa Mizutani

“…To address these gaps and unlock the immense potential of iPhone LiDAR technology, this article proposes an innovative workflow that integrates iPhone 13 Pro LiDAR technology with Augmented Reality (AR) marks and the Global Navigation Satellite System (GNSS) to enable digitized multi-scene road maintenance documentation and revolutionize current practices. …”
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