Special Issue on Selected Papers from the “International Symposium on Remote Sensing 2018”

Jung, Hyung-Sup; Ryu, Joo-Hyung; Park, Sang-Eun; Lee, Hoonyol; Park, No-Wook

doi:10.3390/rs11121439

Cited by 3 publications

(4 citation statements)

References 19 publications

(18 reference statements)

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“…These non-closed expressions can be treated as nonlinear optimization problems of the objective function, and population intelligence search methods from the field of artificial intelligence [27,28] offer common approaches for solving such problems. The application of artificial intelligence methods to parameter estimation of sea clutter distribution models is a relatively new research direction [29].…”

Section: Introductionmentioning

confidence: 99%

Enhanced Particle Swarm Optimization Algorithm for Sea Clutter Parameter Estimation in Generalized Pareto Distribution

Yang,

2023

Applied Sciences

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Accurate parameter estimation is essential for modeling the statistical characteristics of ocean clutter. Common parameter estimation methods in generalized Pareto distribution models have limitations, such as restricted parameter ranges, lack of closed-form expressions, and low estimation accuracy. In this study, the particle swarm optimization (PSO) algorithm is used to solve the non-closed-form parameter estimation equations of the generalized Pareto distribution. The goodness-of-fit experiments show that the PSO algorithm effectively solves the non-closed parameter estimation problem and enhances the robustness of fitting the generalized Pareto distribution to heavy-tailed oceanic clutter data. In addition, a new parameter estimation method for the generalized Pareto distribution is proposed in this study. By using the difference between the statistical histogram of the data and the probability density function/cumulative distribution function of the generalized Pareto distribution as the target, an adaptive function with weighted coefficients is constructed to estimate the distribution parameters. A hybrid PSO (HPSO) algorithm is used to search for the best position of the fitness function to achieve the best parameter estimation of the generalized Pareto distribution. Simulation analysis shows that the HPSO algorithm outperforms the PSO algorithm in solving the parameter optimization task of the generalized Pareto distribution. A comparison with other traditional parameter estimation methods for generalized Pareto distribution shows that the HPSOHPSO algorithm exhibits strong parameter estimation performance, is efficient and stable, and is not limited by the parameter range.

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Section: Introductionmentioning

confidence: 99%

Enhanced Particle Swarm Optimization Algorithm for Sea Clutter Parameter Estimation in Generalized Pareto Distribution

Yang,

2023

Applied Sciences

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“…Following its precedent [1], the organizer of the "2019 International Symposium on Remote Sensing" also planned a Special Issue in Remote Sensing to publish peer-reviewed feature papers presented at ISRS-2019. The submitted manuscripts were significantly extended from their original conference submissions.…”

Section: Introductionmentioning

confidence: 99%

Editorial for the Special Issue on Selected Papers from the “2019 International Symposium on Remote Sensing”

et al. 2020

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The 2019 International Symposium on Remote Sensing (ISRS-2019) took place in Taipei, Taiwan from 17 to 19 April 2019. ISRS is one of the distinguished conferences on the photogrammetry, remote sensing and spatial information sciences, especially in East Asia. More than 220 papers were presented in 37 technical sessions organized at the conference. This Special Issue publishes a limited number of featured peer-reviewed papers extended from their original contributions at ISRS-2019. The selected papers highlight a variety of topics pertaining to innovative concepts, algorithms and applications with geospatial sensors, systems, and data, in conjunction with emerging technologies such as artificial intelligence, machine leaning and advanced spatial analysis algorithms. The topics of the selected papers include the following: the on-orbit radiometric calibration of satellite optical sensors, environmental characteristics assessment with remote sensing, machine learning-based photogrammetry and image analysis, and the integration of remote sensing and spatial analysis. The selected contributions also demonstrate and discuss various sophisticated applications in utilizing remote sensing, geospatial data, and technologies to address different environmental and societal issues. Readers should find the Special Issue enlightening and insightful for understanding state-of-the-art remote sensing and spatial information science research, development and applications.

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“…Currently, the Korean government is integrating the satellite operating system to support comprehensive use of satellite images at the national level and is supporting R&D for the development and distribution of various technologies. The theory and applications of KOMPSAT satellite images can be found in several Special Issues [1][2][3][4][5][6] The KOMPSAT-3 is the successor satellite of the KOMPSAT-2 and was developed for continuous high-precision Earth observation image acquisition. The Advanced Earth Imaging Sensor System (AEISS), the payload of the KOMPSAT-3, provides a 0.7 m spatial resolution image and is widely used for producing precise maps because it allows stereo imaging on the same orbit.…”

mentioning

confidence: 99%

“…Currently, the Korean government is integrating the satellite operating system to support comprehensive use of satellite images at the national level and is supporting R&D for the development and distribution of various technologies. The theory and applications of KOMPSAT satellite images can be found in several Special Issues [1][2][3][4][5][6]. This Special Issue discusses recent The KOMPSAT images have been successfully used to observe Earth's surface in the fields of physics, ecology, geology, hydrology, environmentology, etc.…”

mentioning

confidence: 99%

Earth Observation from KOMPSAT Optical, Thermal, and Radar Satellite Images

2021

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Special Issue on Selected Papers from the “International Symposium on Remote Sensing 2018”

Abstract: The international symposium on remote sensing 2018 (ISRS 2018) was held in Pyeongchang, Korea, 9–11 May 2018 [...]

Cited by 3 publications

References 19 publications

Enhanced Particle Swarm Optimization Algorithm for Sea Clutter Parameter Estimation in Generalized Pareto Distribution

Enhanced Particle Swarm Optimization Algorithm for Sea Clutter Parameter Estimation in Generalized Pareto Distribution

Editorial for the Special Issue on Selected Papers from the “2019 International Symposium on Remote Sensing”

Earth Observation from KOMPSAT Optical, Thermal, and Radar Satellite Images

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