Review
Environmental Sciences
Abdulaziz Amer Aleissaee, Amandeep Kumar, Rao Muhammad Anwer, Salman Khan, Hisham Cholakkal, Gui-Song Xia, Fahad Shahbaz Khan
Summary: Deep learning algorithms have gained popularity in remote sensing image analysis, and transformer-based architectures have been widely used in computer vision with self-attention mechanism replacing convolution operator. Inspired by this, the remote sensing community has explored vision transformers for various tasks. This survey presents a systematic review of recent transformer-based methods in remote sensing, covering different sub-areas like very high-resolution (VHR), hyperspectral (HSI), and synthetic aperture radar (SAR) imagery. The survey concludes by discussing challenges and open issues of transformers in remote sensing.
Article
Optics
Yanchi Yuan, Xue Wen, Bo Yuan, Haishu Xin, Bingyan Fang, Sihua Yang, Kedi Xiong
Summary: The mechanical properties of organisms are important for clinical disputes and disease monitoring. However, most existing elastography techniques based on contact measurements are limited in many applications. Photoacoustic remote sensing elastography (PARSE) is a non-contact and non-coherent intensity monitoring method that obtains elastic contrast information through acoustic pressure monitoring. PARSE has a greater distinction detection capability than photoacoustic remote sensing (PARS) imaging in stained bronchial sections and has the potential to become an important complementary imaging modality.
Review
Environmental Sciences
Sam Purkis, Ved Chirayath
Summary: This article discusses the wide range of remote sensing technologies currently applied in oceans, highlighting next-generation technologies that may revolutionize the field, while also pointing out significant challenges in ocean remote sensing. Despite oceans comprising over 90% of the habitable volume of Earth, their imaging resolution is far below that of the moon and Mars. At this crucial historical moment, our understanding of rapidly changing marine ecosystems is still limited by technological maturity and challenges.
ANNUAL REVIEW OF ENVIRONMENT AND RESOURCES
(2022)
Review
Environmental Sciences
Bowen Chen, Liqin Liu, Zhengxia Zou, Zhenwei Shi
Summary: This paper reviews representative methods for hyperspectral image target detection, and categorizes them into seven categories: hypothesis testing-based methods, spectral angle-based methods, signal decomposition-based methods, constrained energy minimization (CEM)-based methods, kernel-based methods, sparse representation-based methods, and deep learning-based methods. The basic principles, classical algorithms, advantages, limitations, and connections of these methods are comprehensively summarized, and critical comparisons are made on the summarized datasets and evaluation metrics. Furthermore, the future challenges and directions in the area are analyzed.
Review
Environmental Sciences
Xinglu Cheng, Yonghua Sun, Wangkuan Zhang, Yihan Wang, Xuyue Cao, Yanzhao Wang
Summary: The rapid advancement of remote sensing technology has enhanced the temporal resolution of remote sensing data, leading to the emergence of multitemporal remote sensing image classification. Deep learning methods have become prevalent in this field due to their ability to handle massive datasets. This paper provides a review and discussion on the research status and trends in multitemporal images, including retrieval statistics, dataset preparation, model overview, and application status. It also identifies current problems and proposes future prospects, aiming to help readers understand the research process and application status of this field.
Review
Environmental Sciences
Xixuan Zhou, Jinyu Wang, Fengjie Zheng, Haoyu Wang, Haitao Yang
Summary: This paper discusses the research progress related to data sources and extraction methods for remote sensing-based coastline extraction. It summarizes the suitability of data and extraction algorithms for specific coastline types, as well as the challenges and prospects in coastline data construction.
Article
Environmental Sciences
Junyu Gao, Maoguo Gong, Xuelong Li
Summary: In this paper, we propose a method named SwinCounter for object counting in remote sensing. The method addresses the issue of imbalanced object labels by introducing a Balanced MSE Loss and captures multi-scale information accurately using the attention mechanism. Experiments on the RSOC dataset demonstrate the competitiveness and superiority of the proposed method.
Article
Environmental Sciences
Feng Gao, Jie Wu, Jinghao Xiao, Xiaohui Li, Shunyi Liao, Wangyang Chen
Summary: This study proposes a method for spatializing carbon emissions based on nighttime light remote sensing and municipal electricity social sensing. By integrating nighttime light and municipal electricity consumption data, the economics-energy comprehensive index (EECI) is introduced. Carbon emissions are then spatialized at a fine scale using nighttime light, municipal electricity consumption, and EECI. The geographic detector model is applied to identify factors influencing carbon emissions. The results demonstrate the accuracy of combining remote sensing and social sensing data in depicting carbon emissions.
ENVIRONMENTAL RESEARCH
(2023)
Article
Remote Sensing
Yanfei Zhong, Xinyu Wang, Shaoyu Wang, Liangpei Zhang
Summary: This paper discusses the recent progress in Chinese spaceborne HRS, including typical satellite systems, data processing, and applications, as well as the future development trends of HRS in China.
GEO-SPATIAL INFORMATION SCIENCE
(2021)
Review
Chemistry, Analytical
Pengfei Qi, Wenqi Qian, Lanjun Guo, Jiayun Xue, Nan Zhang, Yuezheng Wang, Zhi Zhang, Zeliang Zhang, Lie Lin, Changlin Sun, Liguo Zhu, Weiwei Liu
Summary: This paper summarizes recent research advances in sensing with femtosecond laser filamentation, including fundamental physics, sensing methods, typical sensing techniques and application scenarios, and highlights the challenges in sensing and controlling filamentation in complex environments.
Article
Environmental Sciences
Shaoyan Fan, Ziang Cui, Xuedi Chen, Xinyuan Liu, Fei Xing, Zheng You
Summary: CubeSats have extensive applications in remote sensing, but magnetic field measurement failures can compromise attitude control. To address this issue, we propose a dynamics-sensing, magnetic, fault-tolerant attitude control method that achieves attitude control without a magnetometer and restores remote sensing capabilities.
Article
Computer Science, Software Engineering
Hyung-il Kim, Boram Yoon, Seo Young Oh, Woontack Woo
Summary: In this paper, a prototype system for sharing a user's hand force in MR remote collaboration on physical tasks is presented. The system uses a wearable sEMG sensor to estimate hand force and visualizes it for the expert. A user study demonstrates that sensing and sharing hand force improves the expert's awareness, perception, and social presence in the collaboration.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2023)
Article
Environmental Sciences
Donatella Occorsio, Giuliana Ramella, Woula Themistoclakis
Summary: In this study, a framework was proposed to assess recent image resizing methods for remote sensing applications. Extensive experiments were conducted on multiple public remote sensing image datasets and two new datasets included in the framework to evaluate the performance of each method in terms of image quality and statistical measures.
Article
Geochemistry & Geophysics
[Anonymous]
Summary: This issue of the publication presents the institutional listings for GRSS.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Geosciences, Multidisciplinary
Cheng Liu, Chengzhi Xing, Qihou Hu, Shanshan Wang, Shaohua Zhao, Meng Gao
Summary: This article reviews the recent advances in hyperspectral remote sensing techniques and discusses the future application prospects in air pollution monitoring. It recommends the use of a multi-means joint hyperspectral stereoscopic remote sensing monitoring mode for effective monitoring and regulation of air pollution.
EARTH-SCIENCE REVIEWS
(2022)
Article
Environmental Sciences
Adrian Chappell, Nicholas P. Webb, Juan Pablo Guerschman, Dean T. Thomas, Gonzalo Mata, Rebecca N. Handcock, John F. Leys, Harry J. Butler
REMOTE SENSING OF ENVIRONMENT
(2018)
Article
Agronomy
Randall J. Donohue, Roger A. Lawes, Gonzalo Mata, David Gobbett, Jackie Ouzman
FIELD CROPS RESEARCH
(2018)
Article
Agronomy
Yang Chen, Randall J. Donohue, Tim R. McVicar, Francois Waldner, Gonzalo Mata, Noboru Ota, Alireza Houshmandfar, Kavina Dayal, Roger A. Lawes
AGRICULTURAL AND FOREST METEOROLOGY
(2020)
Article
Environmental Sciences
Francois Waldner, Foivos I. Diakogiannis, Kathryn Batchelor, Michael Ciccotosto-Camp, Elizabeth Cooper-Williams, Chris Herrmann, Gonzalo Mata, Andrew Toovey
Summary: DECODE is a method that automatically extracts accurate field boundary data from satellite imagery using deep learning, with high accuracy and transferability. The method demonstrated superior performance and scalability in the Australian grains zone.
Review
Agriculture, Multidisciplinary
R. Lawes, Z. Hochman, E. Jakku, R. Butler, J. Chai, Y. Chen, F. Waldner, G. Mata, R. Donohue
Summary: The Australian dryland grain-cropping landscape requires a large amount of agricultural information that cannot be fulfilled by international crop-monitoring systems. To address this, an integrated analytics system combining satellite-based crop-mapping, crop-modelling, and data-delivery techniques was developed. This system can generate crop information on-demand and deliver it through an application programming interface. End-users are now using crop-monitoring data, highlighting the need for a vertically integrated data supply chain to further develop crop-monitoring technology.
CROP & PASTURE SCIENCE
(2023)
Article
Agriculture, Dairy & Animal Science
Dean T. Thomas, Andrew F. Toovey, Elizabeth Hulm, Gonzalo Mata
Summary: Modern crop stubbles serve as an important source of feed for sheep in summer, but their feeding value can vary significantly due to Genetics x Environment x Management interactions and chaff management at harvest. Sheep with lower body condition scores tend to gain more weight on stubbles, highlighting the importance of ewe condition in feed efficiency.
ANIMAL PRODUCTION SCIENCE
(2021)
Article
Agriculture, Dairy & Animal Science
SM Liu, A Murray, AC Schlink, G Mata, DG Masters
Article
Agriculture, Dairy & Animal Science
DG Masters, C Scrivener, G Mata, L Hygate
ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES
(2000)
Article
Agriculture, Dairy & Animal Science
G Mata, DG Masters, S Liu, SK Gulati
ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES
(2000)
Article
Agriculture, Dairy & Animal Science
G Mata, DG Masters, J Ive
ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES
(2000)
Article
Agriculture, Dairy & Animal Science
SM Liu, DG Masters, G Mata, C Wielinga, SK Gulati
ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES
(2000)
Article
Agriculture, Multidisciplinary
DG Masters, G Mata, CK Revell, RH Davidson, HC Norman, BJ Nutt, V Solah
AUSTRALIAN JOURNAL OF EXPERIMENTAL AGRICULTURE
(2006)
Article
Agriculture, Multidisciplinary
DG Masters, G Mata, SM Liu, AC Schlink
AUSTRALIAN JOURNAL OF EXPERIMENTAL AGRICULTURE
(2002)
Article
Agriculture, Dairy & Animal Science
G Mata, P Schroder, DG Masters
WOOL TECHNOLOGY AND SHEEP BREEDING
(2002)