Article
Chemistry, Analytical
Sureerat Makmuang, Anupun Terdwongworakul, Tirayut Vilaivan, Simon Maher, Sanong Ekgasit, Kanet Wongravee
Summary: Weedy rice is a difficult weed to manage in rice-growing regions, as it is hard to distinguish from cultivated rice. This study proposes a novel classification approach using artificial neural networks and near-infrared hyperspectral imaging to directly discriminate weedy rice. The method showed high accuracy in classifying weedy rice samples.
MICROCHEMICAL JOURNAL
(2023)
Review
Environmental Sciences
Junbo Wang, Lanying Wang, Shufang Feng, Benrong Peng, Lingfeng Huang, Sarah N. Fatholahi, Lisa Tang, Jonathan Li
Summary: This paper provides a narrative review of shoreline mapping using airborne LiDAR over the past two decades. More than 130 articles were summarized to assess the current state and challenges of this method. It was found that while there are limitations and challenges, the combination of LiDAR point cloud processing techniques, such as deep-learning algorithms, shows promise for improving shoreline extraction and mapping.
Article
Automation & Control Systems
Dominik Olszewski
Summary: The study introduces an enhanced adaptive version of SOM that preserves input data structure and captures data scattering, which has been empirically proven to be superior to other data visualization techniques.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Chemistry, Analytical
Ali Massoud, Ahmed Fahmy, Umar Iqbal, Sidney Givigi, Aboelmagd Noureldin
Summary: In the past two decades, there has been an increasing demand for real-time generation of digital surface models (DSMs), especially for aircraft landing in degraded visual environments. However, existing filtering algorithms for airborne laser scanning (ALS) data are computationally expensive and unsuitable for real-time applications. This research aims to design and implement an efficient algorithm that can be used in real-time on limited-resource embedded processors without the need for a supercomputer. The proposed algorithm effectively identifies the safest landing zone for aircraft/helicopter based on 3D LiDAR point cloud data.
Article
Engineering, Civil
Li-Chiu Chang, Wu-Han Wang, Fi-John Chang
Summary: The study compared the effectiveness of two SOM training strategies, with the S2 strategy demonstrating higher efficiency and effectiveness in constructing regional flood inundation maps.
JOURNAL OF HYDROLOGY
(2021)
Article
Geosciences, Multidisciplinary
Alanny Christiny Costa Melo, David Lopes de Castro, Stephen James Fraser, Antomat Avelino Macedo Filho
Summary: This research utilized multivariate analysis and the Self-Organizing Maps (SOM) method to analyze the magnetic and gamma-spectrometric signatures of dyke swarms in Northeast Brazil, revealing their spatial distribution and characteristics. The SOM analysis identified populations associated with the dyke swarms, reducing the ambiguity of magnetic anomaly interpretation, and these results were validated through fieldwork.
JOURNAL OF APPLIED GEOPHYSICS
(2021)
Article
Geosciences, Multidisciplinary
Hary Nugroho, Ketut Wikantika, Satria Bijaksana, Asep Saepuloh
Summary: This study investigates various strategies for addressing imbalanced data in lithological classification using RF algorithms. The oversampling approach outperforms other techniques, providing the most reliable classification results.
Article
Multidisciplinary Sciences
Luciene Sales Dagher Arce, Lucas Prado Osco, Mauro dos Santos de Arruda, Danielle Elis Garcia Furuya, Ana Paula Marques Ramos, Camila Aoki, Arnildo Pott, Sarah Fatholahi, Jonathan Li, Fabio Fernando de Araujo, Wesley Nunes Goncalves, Jose Marcato Junior
Summary: The use of deep learning approach successfully detected and geolocated the Buriti palm tree, showing improved accuracy compared to other methods and presenting potential applications for mapping individual tree species in dense forest environments.
SCIENTIFIC REPORTS
(2021)
Article
Water Resources
Vahid Gholami, Hossein Sahour
Summary: This study developed a model using self-organizing map and genetic algorithm to successfully identify areas of arsenic contamination in groundwater in Iran. The factors of population density, distance from industries, and nitrate concentration were found to be most correlated with arsenic concentration in groundwater. The optimal model was used to predict arsenic concentration across the study area and presented in a groundwater arsenic concentration map, which can be used for water quality management and safeguarding public health, as well as strategic guidance for land-use planning.
EXPOSURE AND HEALTH
(2023)
Article
Environmental Sciences
Yasmine Megahed, Ahmed Shaker, Wai Yeung Yan
Summary: According to the World Health Organization, urban residents are expected to make up 70% of the global population by 2050. This study explores the effects of using traditional spectral signatures acquired by different sensors on the classification of LiDAR point clouds, achieving an overall classification accuracy of over 97% with the use of machine learning algorithms.
Article
Environmental Sciences
Michaela Novakova, Michal Gallay, Jozef Supinsky, Eric Ferre, Riccardo Asti, Michel de Saint Blanquat, Flora Bajolet, Patrick Sorriaux
Summary: This study presents an efficient and complex workflow to correct the recorded intensity of caves during laser scanning, taking into consideration various influencing factors. Demonstrated on LiDAR data acquired in a cave in the northern Pyrenees in France, the approach showed an overall accuracy of over 84% in rock surface classification based on the corrected laser intensity.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Computer Science, Artificial Intelligence
Leonardo A. Dias, Augusto M. P. Damasceno, Elena Gaura, Marcelo A. C. Fernandes
Summary: The study introduces a fully parallel architecture for SOM that significantly improves processing speed and resource efficiency.
Article
Engineering, Geological
Lukasz Janowski, Radoslaw Wroblewski, Maria Rucinska, Agnieszka Kubowicz-Grajewska, Pawel Tysiac
Summary: This study presents a novel methodological approach to assess the suitability of Airborne LiDAR Bathymetry for automatic classification and mapping of the seafloor. By using Geographic Object-Based Image Analysis and machine learning supervised classifiers, the study successfully achieved automatic mapping with an overall accuracy of up to 94% in several study sites. The method also demonstrated that the Multiresolution Index of Ridge Top Flatness can be used to quickly and automatically determine sandbar crests and ridge tops.
ENGINEERING GEOLOGY
(2022)
Article
Environmental Sciences
Hang Zhou, Gan Zhang, Junxiong Zhang, Chunlong Zhang
Summary: This paper describes a method for constructing fine rubber forest growth model map based on 3D point clouds. It accurately identifies and segments rubber trees, and generates a detailed map with trunk locations and key structural parameters. This method has important implications for forestry resource management and the enhancement of rubber tapping mechanization.
Article
Environmental Sciences
Niva Kiran Verma, David W. Lamb, Priyakant Sinha
Summary: This study successfully identified and mapped Eucalyptus tree species using remote sensing data and LiDAR technology, with improved classification accuracy. The identification of tree species is important for assessing farm tree conditions, management practices, and degradation issues.
GEOCARTO INTERNATIONAL
(2022)
Article
Chemistry, Multidisciplinary
Alessandro Novellino, Samantha L. Engwell, Stephen Grebby, Simon Day, Michael Cassidy, Amber Madden-Nadeau, Sebastian Watt, David Pyle, Mirzam Abdurrachman, Muhammad Edo Marshal Nurshal, David R. Tappin, Idham Andri Kurniawan, James Hunt
APPLIED SCIENCES-BASEL
(2020)
Article
Geochemistry & Geophysics
Stephanos P. Kilias, Magnus Ivarsson, Ernest Chi Fru, Jayne E. Rattray, Hakan Gustafsson, Jonathan Naden, Kleopatra Detsi
Editorial Material
Chemistry, Multidisciplinary
Alessandro Novellino, Stephen Grebby
APPLIED SCIENCES-BASEL
(2020)
Article
Geosciences, Multidisciplinary
Christopher M. Yeomans, Robin K. Shail, Stephen Grebby, Vesa Nykanen, Maarit Middleton, Paul A. J. Lusty
GEOSCIENCE FRONTIERS
(2020)
Article
Energy & Fuels
Gaoyuan Yan, Zhengyuan Qin, Stuart Marsh, Stephen Grebby, Yi Mou, Lijuan Song, Chenchen Zhang
Summary: The study found that the pore size distribution of micropores and meso-macropores in shale samples exhibit typical multifractal behavior. The overall distribution heterogeneity of meso-macropores is mainly affected by the distribution of pores in the low-value area of pore volume, while the overall distribution heterogeneity of micropores is affected by the distribution of the high-value area of the pore volume. Additionally, the single fractal dimension calculated using the Frenkel-Halsey-Hill model has a negative correlation with the multifractal parameters, implying that the physical meaning of the two models is obviously different.
Article
Environmental Sciences
Vivek Agarwal, Amit Kumar, David Gee, Stephen Grebby, Rachel L. Gomes, Stuart Marsh
Summary: Groundwater variation can cause significant land surface movement, with different rates observed in London and NCT-Delhi. Over extraction of groundwater results in land subsidence, while groundwater recharge leads to land uplift. This study compares C-band PSInSAR-derived land subsidence response to observed groundwater change for London and NCT-Delhi, providing insights for resource management and safety implications.
Article
Chemistry, Multidisciplinary
Stephen Grebby, Andrew Sowter, David Gee, Ahmed Athab, Betsabe De la Barreda-Bautista, Renoy Girindran, Stuart Marsh
Summary: The combination of satellite passes and advanced InSAR techniques facilitates the remote monitoring of ground motion hazards in high mountain areas, despite the challenges of terrain complexity and coverage issues. The study shows that with a judicious selection of ascending and descending satellite passes, 88% of the land surface can be surveyed, and advanced InSAR techniques can provide near-complete coverage of ground motion measurements.
APPLIED SCIENCES-BASEL
(2021)
Article
Environmental Sciences
Zhengyuan Qin, Vivek Agarwal, David Gee, Stuart Marsh, Stephen Grebby, Yong Chen, Ningkang Meng
Summary: Underground coal mining activities can lead to significant ground movement, causing damage to local infrastructure. Monitoring such ground movement is crucial for safety and economy. A study in Fangezhuang coalfield in Tangshan, China used FDM 3D model and InSAR method to monitor ground movement in 2016, showing that subsidence mainly occurred in a specific mining panel and fault area. This study highlights the importance of monitoring mining induced ground movement in fault dominant areas to improve safety and prevent damage.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2021)
Article
Energy & Fuels
Junjian Zhang, Qinhong Hu, Xiangchun Chang, Zhengyuan Qin, Xiaoyang Zhang, Stuart Marsh, Stephen Grebby, Vivek Agarwal
Summary: Determining water occurrence in pore-fracture systems under specific water saturation is important for understanding the correlation between water content and porosity/permeability of coal reservoirs. This study used simulation experiments and NMR techniques to investigate the micro-occurrence and migration of water in the coal samples. The results show that the structure parameters of the pore-fracture system affect water micro-occurrence, and multifractal parameters are correlated with coal sample characteristics.
Review
Environmental Sciences
Anna Klimkowska, Stefano Cavazzi, Richard Leach, Stephen Grebby
Summary: Urban environments with complex and diverse architecture require comprehensive reconstruction and representation. In this review, the focus is on the detection and reconstruction of facade openings in buildings, which remains a challenging task with limitations in automation and data incompleteness. Future research opportunities include the exploration of deep-learning methods and the availability of diverse benchmark datasets.
Article
Multidisciplinary Sciences
Rui Zhao, Ping Fu, Yan Zhou, Xiangming Xiao, Stephen Grebby, Guoqing Zhang, Jinwei Dong
Summary: Lake systems on the Tibetan Plateau play a vital role in providing and storing fresh water, but previous studies lack sufficient temporal information. This study presents a new dataset of annual lake maps from 1991 to 2018, revealing concentration of lakes in the Inner basin and overall increasing trends in both lake area and number.
Article
Water Resources
C. I. Kelly, C. M. Hancock, S. Grebby, S. Marsh, V. G. Ferreira, N. A. S. Hamm
Summary: This study focuses on the influence of climate on water availability in the Upper East Region of Ghana. The researchers found strong correlations between different precipitation and GRACE products, but not between different evapotranspiration products. They also observed an increase in TWSA and a decrease in TWCA, with no significant trend in precipitation and evapotranspiration. The study highlights the increasing water storage trend in the region and confirms the usability of GRACE for water management.
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2022)
Article
Environmental Sciences
David Gee, Andrew Sowter, Ahmed Athab, Stephen Grebby, Zhenming Wu, Kateryna Boiko
Summary: The rise of minewater after coalfield abandonment can result in significant changes in hydrogeological conditions, necessitating monitoring to prevent groundwater contamination and surface flooding. This study presents a method using SAR measurements to remotely monitor the rise of minewater in near real-time. The approach is validated in the Horlivka mining agglomeration, Ukraine, revealing a potential environmental catastrophe with potentially radioactive minewater reaching the natural water table between May and August of 2024 due to military conflicts in Donbas.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Engineering, Geological
Cristina Andra Vrinceanu, Stephen Grebby, Stuart Marsh
Summary: Synthetic aperture radar (SAR) is commonly used for objective identification of petroleum slicks, but the speckle effect can degrade the image quality. This study evaluates different despeckling methods applied to SAR images with oil slicks, using Copernicus Sentinel-1 images. Filters employing local statistics in the spatial domain show consistent desired effects, while the SAR-BM3D algorithm is effective but computationally demanding.
QUARTERLY JOURNAL OF ENGINEERING GEOLOGY AND HYDROGEOLOGY
(2023)
Article
Environmental Sciences
David Gee, Luke Bateson, Stephen Grebby, Alessandro Novellino, Andrew Sowter, Lee Wyatt, Stuart Marsh, Roy Morgenstern, Ahmed Athab
REMOTE SENSING OF ENVIRONMENT
(2020)
Article
Environmental Sciences
Ruonan Chen, Liangyun Liu, Xinjie Liu, Zhunqiao Liu, Lianhong Gu, Uwe Rascher
Summary: This study presents methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Daniel L. Goldberg, Madankui Tao, Gaige Hunter Kerr, Siqi Ma, Daniel Q. Tong, Arlene M. Fiore, Angela F. Dickens, Zachariah E. Adelman, Susan C. Anenberg
Summary: A novel method is applied in this study to directly use satellite data to evaluate the spatial patterns of urban NOx emissions inventories. The results show that the 108 spatial surrogates used by NEMO are generally appropriate, but there may be underestimation in areas with dense intermodal facilities and overestimation in wealthy communities.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Zhuoyue Hu, Xiaoyan Li, Liyuan Li, Xiaofeng Su, Lin Yang, Yong Zhang, Xingjian Hu, Chun Lin, Yujun Tang, Jian Hao, Xiaojin Sun, Fansheng Chen
Summary: This paper proposes a whisk-broom imaging method using a long-linear-array detector and high-precision scanning mirror to achieve high-resolution and wide-swath thermal infrared data. The method has been implemented in the SDGs satellite and has shown promising test results.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Dandan Wang, Leiqiu Hu, James A. Voogt, Yunhao Chen, Ji Zhou, Gaijing Chang, Jinling Quan, Wenfeng Zhan, Zhizhong Kang
Summary: This study evaluates different schemes for determining model coefficients to quantify and correct the anisotropic impact from remote sensing LST for urban applications. The schemes have consistent results and accurately estimate parameter values, facilitating the broadening of parametric models.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jamie Tolan, Hung - Yang, Benjamin Nosarzewski, Guillaume Couairon, Huy V. Vo, John Brandt, Justine Spore, Sayantan Majumdar, Daniel Haziza, Janaki Vamaraju, Theo Moutakanni, Piotr Bojanowski, Tracy Johns, Brian White, Tobias Tiecke, Camille Couprie
Summary: Vegetation structure mapping is crucial for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. This study presents the first high-resolution canopy height maps for California and Sao Paulo, achieved through the use of very high resolution satellite imagery and aerial lidar data. The maps provide valuable tools for forest structure assessment and land use monitoring.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Regina Eckert, Steffen Mauceri, David R. Thompson, Jay E. Fahlen, Philip G. Brodrick
Summary: In this paper, a mathematical framework is proposed to improve the retrieval of surface reflectance and atmospheric parameters by leveraging the expected spatial smoothness of the atmosphere. Experimental results show that this framework can reduce the surface reflectance retrieval error and surface-related biases.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Chongya Jiang, Kaiyu Guan, Yizhi Huang, Maxwell Jong
Summary: This study presents the Field Rover method, which uses vehicle-mounted cameras to collect ground truth data on crop harvesting status. The machine learning approach and remote sensing technology are employed to upscale the results to a regional scale. The accuracy of the remote sensing method in predicting crop harvesting dates is validated through comparison with satellite data.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Oksana V. Lunina, Anton A. Gladkov, Alexey V. Bochalgin
Summary: In this study, an unmanned aerial vehicle (UAV) was used to detect and map surface discontinuities with displacements of a few centimeters, indicating the presence of initial geological deformations. The study found that sediments of alluvial fans are susceptible to various tectonic and exogenous deformational processes, and the interpretation of ultra-high resolution UAV images can help recognize low-amplitude brittle deformations at an early stage. UAV surveys are critical for discerning neotectonic activity and its related hazards over short observation periods.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Feng Zhao, Weiwei Ma, Jun Zhao, Yiqing Guo, Mateen Tariq, Juan Li
Summary: This study presents a data-driven approach to reconstruct the terrestrial SIF spectrum using measurements from the TROPOMI instrument on Sentinel-5 precursor mission. The reconstructed SIF spectrum shows improved spatiotemporal distributions and demonstrates consistency with other datasets, indicating its potential for better understanding of the ecosystem function.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Stephen Stehman, John E. Wagner
Summary: This article investigates optimal sample allocation in stratified random sampling for estimation of accuracy and proportion of area in applications where the target class is rare. The study finds that precision of estimated accuracy has a stronger impact on sample allocation than estimation of proportion of area, and the trade-offs among these estimates become more pronounced as the target class becomes rarer. The results provide quantitative evidence to guide sample allocation decisions in specific applications.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jingyao Zheng, Tianjie Zhao, Haishen Lu, Defu Zou, Nemesio Rodriguez-Fernandez, Arnaud Mialon, Philippe Richaume, Jianshe Xiao, Jun Ma, Lei Fan, Peilin Song, Yonghua Zhu, Rui Li, Panpan Yao, Qingqing Yang, Shaojie Du, Zhen Wang, Zhiqing Peng, Yuyang Xiong, Zanpin Xing, Lin Zhao, Yann Kerr, Jiancheng Shi
Summary: Soil moisture and freeze/thaw (F/T) play a crucial role in water and heat exchanges at the land-atmosphere interface. This study reports the establishment of a wireless sensor network for soil moisture and temperature over the permafrost region of Tibetan Plateau. Satellite-based surface soil moisture (SSM) and F/T products were evaluated using ground-based measurements. The results show the reliability of L-band passive microwave SSM and F/T products, while existing F/T products display earlier freezing and later thawing, leading to unsatisfactory accuracy.
REMOTE SENSING OF ENVIRONMENT
(2024)