scholarly journals A Review of Remote Sensing Image Dehazing

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3926
Author(s):  
Juping Liu ◽  
Shiju Wang ◽  
Xin Wang ◽  
Mingye Ju ◽  
Dengyin Zhang
Keyword(s):  
Remote Sensing ◽  
Data Driven ◽  
Future Research ◽  
Research Focus ◽  
Image Dehazing ◽  
Surface Information ◽  
Haze Removal ◽  
Advantages And Disadvantages ◽  
Extra Information ◽  
Removal Technique

Remote sensing (RS) is one of the data collection technologies that help explore more earth surface information. However, RS data captured by satellite are susceptible to particles suspended during the imaging process, especially for data with visible light band. To make up for such deficiency, numerous dehazing work and efforts have been made recently, whose strategy is to directly restore single hazy data without the need for using any extra information. In this paper, we first classify the current available algorithm into three categories, i.e., image enhancement, physical dehazing, and data-driven. The advantages and disadvantages of each type of algorithm are then summarized in detail. Finally, the evaluation indicators used to rank the recovery performance and the application scenario of the RS data haze removal technique are discussed, respectively. In addition, some common deficiencies of current available methods and future research focus are elaborated.

scholarly journals A Review on Remote Sensing Data Fusion with Generative Adversarial Networks (GAN)

2021 ◽  
Author(s):  
Peng Liu
Keyword(s):  
Remote Sensing ◽  
Data Fusion ◽  
Remote Sensing Data ◽  
Generative Adversarial Networks ◽  
Future Research ◽  
Observation Data ◽  
Sensing Data ◽  
Advantages And Disadvantages ◽  
Adversarial Networks ◽  
Active Research

In the past decades, remote sensing (RS) data fusion has always been an active research community. A large number of algorithms and models have been developed. Generative Adversarial Networks (GAN), as an important branch of deep learning, show promising performances in variety of RS image fusions. This review provides an introduction to GAN for remote sensing data fusion. We briefly review the frequently-used architecture and characteristics of GAN in data fusion and comprehensively discuss how to use GAN to realize fusion for homogeneous RS data, heterogeneous RS data, and RS and ground observation data. We also analyzed some typical applications with GAN-based RS image fusion. This review takes insight into how to make GAN adapt to different types of fusion tasks and summarizes the advantages and disadvantages of GAN-based RS data fusion. Finally, we discuss the promising future research directions and make a prediction on its trends.

scholarly journals Estimation of Chlorophyll Fluorescence at Different Scales: A Review

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 3000 ◽  
Author(s):  
Zhuoya Ni ◽  
Qifeng Lu ◽  
Hongyuan Huo ◽  
Huili Zhang
Keyword(s):  
Remote Sensing ◽  
Chlorophyll Fluorescence ◽  
Multiple Scales ◽  
Future Research ◽  
Passive Remote Sensing ◽  
Advantages And Disadvantages ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Key Issues ◽  
Non Destructive

Measuring chlorophyll fluorescence is a direct and non-destructive way to monitor vegetation. In this paper, the fluorescence retrieval methods from multiple scales, ranging from near the ground to the use of space-borne sensors, are analyzed and summarized in detail. At the leaf-scale, the chlorophyll fluorescence is measured using active and passive technology. Active remote sensing technology uses a fluorimeter to measure the chlorophyll fluorescence, and passive remote sensing technology mainly depends on the sun-induced chlorophyll fluorescence filling in the Fraunhofer lines or oxygen absorptions bands. Based on these retrieval principles, many retrieval methods have been developed, including the radiance-based methods and the reflectance-based methods near the ground, as well as physically and statistically-based methods that make use of satellite data. The advantages and disadvantages of different approaches for sun-induced chlorophyll fluorescence retrieval are compared and the key issues of the current sun-induced chlorophyll fluorescence retrieval algorithms are discussed. Finally, conclusions and key problems are proposed for the future research.

scholarly journals Forest Leaf Mass per Area (LMA) through the Eye of Optical Remote Sensing: A Review and Future Outlook

2021 ◽  
Vol 13 (17) ◽  
pp. 3352
Author(s):  
Tawanda W. Gara ◽  
Parinaz Rahimzadeh-Bajgiran ◽  
Roshanak Darvishzadeh
Keyword(s):  
Remote Sensing ◽  
Forest Ecosystems ◽  
Leaf Traits ◽  
Spatial And Temporal Variation ◽  
Future Research ◽  
Leaf Mass Per Area ◽  
Ecosystem Structure ◽  
Advantages And Disadvantages ◽  
Leaf Mass ◽  
Quantitative Remote Sensing

Quantitative remote sensing of leaf traits offers an opportunity to track biodiversity changes from space. Augmenting field measurement of leaf traits with remote sensing provides a pathway for monitoring essential biodiversity variables (EBVs) over space and time. Detailed information on key leaf traits such as leaf mass per area (LMA) is critical for understanding ecosystem structure and functioning, and subsequently the provision of ecosystem services. Although studies on remote sensing of LMA and related constituents have been conducted for over three decades, a comprehensive review of remote sensing of LMA—a key driver of leaf and canopy reflectance—has been lacking. This paper reviews the current state and potential approaches, in addition to the challenges associated with LMA estimation/retrieval in forest ecosystems. The physiology and environmental factors that influence the spatial and temporal variation of LMA are presented. The scope of scaling LMA using remote sensing systems at various scales, i.e., near ground (in situ), airborne, and spaceborne platforms is reviewed and discussed. The review explores the advantages and disadvantages of LMA modelling techniques from these platforms. Finally, the research gaps and perspectives for future research are presented. Our review reveals that although progress has been made, scaling LMA to regional and global scales remains a challenge. In addition to seasonal tracking, three-dimensional modeling of LMA is still in its infancy. Over the past decade, the remote sensing scientific community has made efforts to separate LMA constituents in physical modelling at the leaf level. However, upscaling these leaf models to canopy level in forest ecosystems remains untested. We identified future opportunities involving the synergy of multiple sensors, and investigated the utility of hybrid models, particularly at the canopy and landscape levels.

scholarly journals A Review on Remote Sensing Data Fusion with Generative Adversarial Networks (GAN)

2021 ◽  
Author(s):  
Peng Liu
Keyword(s):  
Remote Sensing ◽  
Data Fusion ◽  
Remote Sensing Data ◽  
Generative Adversarial Networks ◽  
Future Research ◽  
Observation Data ◽  
Sensing Data ◽  
Advantages And Disadvantages ◽  
Adversarial Networks ◽  
Active Research

In the past decades, remote sensing (RS) data fusion has always been an active research community. A large number of algorithms and models have been developed. Generative Adversarial Networks (GAN), as an important branch of deep learning, show promising performances in variety of RS image fusions. This review provides an introduction to GAN for remote sensing data fusion. We briefly review the frequently-used architecture and characteristics of GAN in data fusion and comprehensively discuss how to use GAN to realize fusion for homogeneous RS data, heterogeneous RS data, and RS and ground observation data. We also analyzed some typical applications with GAN-based RS image fusion. This review takes insight into how to make GAN adapt to different types of fusion tasks and summarizes the advantages and disadvantages of GAN-based RS data fusion. Finally, we discuss the promising future research directions and make a prediction on its trends.

scholarly journals Continuous Multi-Angle Remote Sensing and Its Application in Urban Land Cover Classification

2021 ◽  
Vol 13 (3) ◽  
pp. 413
Author(s):  
Yuan Yao ◽  
Yee Leung ◽  
Tung Fung ◽  
Zhenfeng Shao ◽  
Jie Lu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Real Life ◽  
Urban Land ◽  
Future Research ◽  
Support Vector ◽  
Svm Classifier ◽  
Optical Remote Sensing ◽  
Advantages And Disadvantages ◽  
Urban Land Cover ◽  
Land Covers

Because of the limitations of hardware devices, such as the sensors, processing capacity, and high accuracy altitude control equipment, traditional optical remote sensing (RS) imageries capture information regarding the same scene from mostly one single angle or a very small number of angles. Nowadays, with video satellites coming into service, obtaining imageries of the same scene from a more-or-less continuous array of angles has become a reality. In this paper, we analyze the differences between the traditional RS data and continuous multi-angle remote sensing (CMARS) data, and unravel the characteristics of the CMARS data. We study the advantages of using CMARS data for classification and try to capitalize on the complementarity of multi-angle information and, at the same time, to reduce the embedded redundancy. Our arguments are substantiated by real-life experiments on the employment of CMARS data in order to classify urban land covers while using a support vector machine (SVM) classifier. They show the superiority of CMARS data over the traditional data for classification. The overall accuracy may increase up to about 9% with CMARS data. Furthermore, we investigate the advantages and disadvantages of directly using the CMARS data, and how such data can be better utilized through the extraction of key features that characterize the variations of spectral reflectance along the entire angular array. This research lay the foundation for the use of CMARS data in future research and applications.

scholarly journals A Review of Fault Diagnosis Research on On-Load Tap-Changers

2020 ◽  
Vol 155 ◽  
pp. 01016 ◽  
Author(s):  
Liang Jin ◽  
Yuqi Cai
Keyword(s):  
Fault Diagnosis ◽  
Voltage Regulation ◽  
Future Research ◽  
Research Focus ◽  
Core Component ◽  
Advantages And Disadvantages ◽  
The Core ◽  
The Common ◽  
Tap Changer ◽  
Load Tap Changer

As the core component of transformer voltage regulation, on-load tap changer plays an important role in ensuring voltage stability of power system. With the increase of times of voltage regulation, the failure rate also increases correspondingly. In view of the common faults of on-load tap changer, this paper introduces several existing fault diagnosis methods and summarizes their advantages and disadvantages. Finally, the problems in fault diagnosis of on-load tap-changer and the future research focus are analysed.

Study on Scene Rendering Using Ray Tracing

2012 ◽  
Vol 241-244 ◽  
pp. 2625-2629
Author(s):  
Zhi Li
Keyword(s):  
Parallel Algorithms ◽  
Real Time ◽  
Ray Tracing ◽  
Technological Process ◽  
Research Priorities ◽  
Graphics Hardware ◽  
Future Research ◽  
Research Focus ◽  
Advantages And Disadvantages ◽  
Tracing Method

The paper synoptically discusses the basic technological process of the ray tracing method, analyzes its parallel algorithms. Introduce the recent research focus of the field from study on real-time ray tracing and based ray tracing of graphics hardware. Point out the advantages and disadvantages of the ray tracing algorithms to solve scene rendering as well as future research priorities.

6. The Communicative Pragmatics of Data-Use for Equity: A Theoretical and Methodological Framework

2020 ◽  
Vol 2 (1) ◽  
pp. 117-149
Author(s):  
Mary B. Ziskin
Keyword(s):  
Critical Race Theory ◽  
Communicative Action ◽  
Educational Equity ◽  
Data Use ◽  
College Faculty ◽  
Postsecondary Institutions ◽  
Data Driven ◽  
Future Research ◽  
Education Data ◽  
Critical Qualitative Research

<?page nr="117"?>Abstract Calls for higher education institutions to implement improvements guided by “data-driven” processes are prevalent and widespread. Despite the pervasiveness of this turn toward data, research on how data-use works on the ground in postsecondary institutions—that is, how individuals within institutions make sense of education data and use it to inform practice—is still developing.Drawing on Habermas’ Theory of Communicative Action (TCA), critical-race theory, and methodological guidance on critical-qualitative research methods, this paper synthesizes methodological and substantive insights from P–12 data-use research, with an eye to applying these insights to critical questions on postsecondary educational equity. The result of the review and analysis is a theoretical framework and a set of methodological recommendations for future research on the perceptions and experiences of college faculty, administrators, and practitioners, regarding their data-use and its implications for equity.

A Review of Drug Side Effect Identification Methods

2020 ◽  
Vol 26 (26) ◽  
pp. 3096-3104 ◽  
Author(s):  
Shuai Deng ◽  
Yige Sun ◽  
Tianyi Zhao ◽  
Yang Hu ◽  
Tianyi Zang
Keyword(s):  
Side Effects ◽  
Future Research ◽  
Drug Side Effects ◽  
Important Indicator ◽  
Advantages And Disadvantages ◽  
Key Points ◽  
Network Methods ◽  
Future Research Directions ◽  
The One ◽  
Approved Drugs

Drug side effects have become an important indicator for evaluating the safety of drugs. There are two main factors in the frequent occurrence of drug safety problems; on the one hand, the clinical understanding of drug side effects is insufficient, leading to frequent adverse drug reactions, while on the other hand, due to the long-term period and complexity of clinical trials, side effects of approved drugs on the market cannot be reported in a timely manner. Therefore, many researchers have focused on developing methods to identify drug side effects. In this review, we summarize the methods of identifying drug side effects and common databases in this field. We classified methods of identifying side effects into four categories: biological experimental, machine learning, text mining and network methods. We point out the key points of each kind of method. In addition, we also explain the advantages and disadvantages of each method. Finally, we propose future research directions.

scholarly journals A Review of Dynamic Balancing for Robotic Mechanisms

Robotica ◽  
2020 ◽  
Vol 39 (1) ◽  
pp. 55-71 ◽  
Author(s):  
Bin Wei ◽  
Dan Zhang
Keyword(s):  
Future Research ◽  
Dynamic Balancing ◽  
Advantages And Disadvantages

SUMMARYThe authors summarize the main dynamic balancing methods of robotic mechanisms in this paper. The majority of dynamic balancing methods have been presented, and there may be other dynamic balancing methods that are not included in this paper. Each of the balancing methods is reviewed and discussed. The advantages and disadvantages of each method are presented and compared. The goal of this paper is to provide an overview of recent research in balancing. The authors hope that this study can provide an informative reference for future research in the direction of dynamic balancing of robotic mechanisms.

Sign in / Sign up

Export Citation Format

Share Document