Article
Geosciences, Multidisciplinary
Yuan Hong, Bo Cai, Jan M. Eberth, Alexander C. McLain
Summary: Analyzing population representative datasets for local level estimation and prediction presents statistical challenges, such as the unclear predictive benefits of post-stratification, the incorporation of sampling weights, and the difficult estimation of mean squared prediction error. This paper compares poststratified and non-post-stratified estimators and evaluates various bootstrapping methods in estimating the MSPE.
SPATIAL STATISTICS
(2022)
Article
Geography, Physical
Qiang Zhou, Zhe Zhu, George Xian, Congcong Li
Summary: Harmonic analysis of time series is important for revealing seasonal land surface dynamics using remote sensing information, but frequency selection can be difficult. The Harmonic Adaptive Penalty Operator (HAPO) is a novel regression method that addresses this issue.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Public, Environmental & Occupational Health
Te Ou Young, Li-Wei Wu, Hsin Hsiu, Tao-Chun Peng, Wei-Liang Chen
Summary: This study used harmonic index of finger photoplethysmography waveforms to distinguish different arterial pulse signals in individuals with sarcopenia, presarcopenia, dynapenia, and healthy subjects. The results showed that individuals with sarcopenia had poorer blood pressure harmonic variability and vascular elasticity compared to the other groups. This may be related to the occurrence of cardiovascular and metabolic diseases.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Mathematics
Daniel Doz, Darjo Felda, Mara Cotic
Summary: This study analyzed the factors affecting students' mathematics grades and standardized test results, including gender, socio-economic status, school type, and geographic region. The results showed that boys had higher grades than girls, students with higher socio-economic status achieved better grades, students from scientific lyceums had the highest grades, and students from vocational schools had the lowest grades. Additionally, students from Northern Italy outperformed students from Southern Italy. These findings highlight the importance of addressing equity in assessment and promoting fair opportunities for students' future career and study prospects.
Article
Biochemical Research Methods
Youpeng Yang, Qiuhong Zeng, Gaotong Liu, Shiyao Zheng, Tianyang Luo, Yibin Guo, Jia Tang, Yi Huang
Summary: Hierarchical classification is a method that breaks down large classification problems into subproblems, providing improved prediction accuracy and mitigating the impact of poor-quality data. In this study, the Cancer Hierarchy Classification Tool (CHCT) was developed to hierarchically classify primary cancer based on methylation profiles, and it demonstrated high accuracy and predictive capability for additional cancer types.
BMC BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Ying Zhang, Yuxin Song, Jin Gao, Hengyu Zhang, Ning Yang, Runqing Yang
Summary: The study extended the Hi-RRM model into a genome-wide association analysis for longitudinal data, reducing the dimensionality of repeated measurements significantly. The method improved computing efficiency through model transformation and demonstrated its statistical utility through simulation experiments.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Suhyun Hwangbo, Sungyoung Lee, Seungyeoun Lee, Heungsun Hwang, Inyoung Kim, Taesung Park
Summary: The study proposes a new approach that takes into account non-linear effects and correlations among pathways in omics data analysis. The method is validated in real and simulated datasets and demonstrates superior performance in identifying biologically meaningful pathways.
Article
Environmental Sciences
Carina Sobe, Manuela Hirschmugl, Andreas Wimmer
Summary: This study utilizes advanced analysis methods based on time series modelling using Sentinel-2 data to distinguish utilized from underutilized land in twelve study areas in Europe. By training a random forest classifier, the achieved overall accuracies per study area vary between 80.25% and 96.76%, with confidence intervals ranging between 1.77% and 6.28% at a 95% confidence level. Nearly 500,000 ha of underutilized land potentially available for agricultural bioenergy production were identified, with the majority located in Eastern Europe.
Article
Environmental Sciences
Ahmed S. Abuzaid, Hossam S. Jahin
Summary: In this study, the integration of multivariate statistical analysis with the analytical hierarchical process was used to estimate the water quality status in the northern Nile Delta in Egypt. The results indicated that water contamination was influenced by human activities and hydrochemical processes, and the water quality varied for irrigation and fish farming. The findings suggested that it is possible to reduce the time and cost for monitoring water quality, but increasing the sampling size is crucial for better performance in fish farming.
JOURNAL OF CONTAMINANT HYDROLOGY
(2022)
Article
Meteorology & Atmospheric Sciences
Majid Niazkar, Reza Piraei, Gokcen Eryilmaz Turkkan, Tugce Hirca, Fabiola Gangi, Seied Hosein Afzali
Summary: This study assesses and forecasts drought conditions in the Eastern Black Sea Basin using innovative trend analysis and machine learning models. The results indicate that the accuracy of SPI prediction improves with longer SPI duration, and the optimal model and number of input variables vary for each SPI and station.
THEORETICAL AND APPLIED CLIMATOLOGY
(2023)
Article
Health Care Sciences & Services
Hui-Ching Wang, Leong-Perng Chan, Chun-Chieh Wu, Hui-Hua Hsiao, Yi-Chang Liu, Shih-Feng Cho, Jeng-Shiun Du, Ta-Chih Liu, Cheng-Hong Yang, Mei-Ren Pan, Sin-Hua Moi
Summary: This study investigated the use of a progression risk score (PRS) developed from cytoplasmic immunohistochemistry (IHC) biomarkers for risk and prognosis assessment in oral cancer patients. Results showed that PRS effectively stratified patients into high and low-risk groups, with high-risk patients demonstrating significantly increased cancer progression risk. PRS could serve as an ideal biomarker for risk stratification and progression assessment in oral cancer patients.
JOURNAL OF PERSONALIZED MEDICINE
(2021)
Article
Computer Science, Interdisciplinary Applications
Kei Hirose, Kanta Miura, Atori Koie
Summary: This article proposes a cluster-based LDA method that improves prediction accuracy through hierarchical clustering and cross-validation, while addressing computational efficiency.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2023)
Article
Allergy
Ke Deng, Xin Zhang, Ying Liu, Li Zhang, Gang Wang, Min Feng, Brian G. Oliver, Lei Wang, Philip M. Hansbro, Lin Qin, Min Xie, Zhi Hong Chen, Jodie Simpson, Jie Zhang, Wei Min Li, Gang Wang, Peter Gerard Gibson
Summary: This study focused on the heterogeneity of paucigranulocytic asthma (PGA) and identified 3 clusters, with cluster 3 showing a higher risk of severe exacerbation. The results suggest the need for novel targeted interventions for different PGA clusters.
JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY-IN PRACTICE
(2021)
Article
Psychology, Mathematical
Sebastian Gary, Wolfgang Lenhard, Alexandra Lenhard, David Herzberg
Summary: Norm scores are crucial for individual diagnostics and establishing high-quality, representative norms is challenging. Post-stratification techniques like iterative proportional fitting can enhance the overall quality of norm scores.
BEHAVIOR RESEARCH METHODS
(2023)
Article
Operations Research & Management Science
Peter Tea, Tim B. Swartz
Summary: Anticipating opponents' serve and being aware of one's own serve tendencies are essential skills in tennis. Using Bayesian hierarchical models, this paper investigates the intended serve direction of professional tennis players at Roland Garros and reveals discernible differences between men's and women's tennis, as well as individual players.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Forestry
P. Corey Green, Harold E. Burkhart, John W. Coulston, Philip J. Radtke, Valerie A. Thomas
Article
Remote Sensing
Jill M. Derwin, Valerie A. Thomas, Randolph H. Wynne, John W. Coulston, Greg C. Liknes, Stacie Bender, Christine E. Blinn, Evan B. Brooks, Bonnie Ruefenacht, Robert Benton, Mark Finco, Kevin Megown
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2020)
Article
Environmental Sciences
V. A. Thomas, R. H. Wynne, J. Kauffman, W. McCurdy, E. B. Brooks, R. Q. Thomas, J. Rakestraw
Summary: The study aims to use Landsat data to detect forest thins as an indicator of active forest management. A machine learning approach was successfully developed to identify thinned areas, with high accuracy in separating thins from clear cuts and non-harvested pines. Important predictors in the classifiers included variables related to vegetation phenology, stand-replacing disturbance, and high spatial resolution visible reflectance.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Matthew J. Sumnall, Andrew Trlica, David R. Carter, Rachel L. Cook, Morgan L. Schulte, Otavio C. Campoe, Rafael A. Rubilar, Randolph H. Wynne, Valerie A. Thomas
Summary: This study utilized ALS data from different sensor types to quantify forest structural attributes in loblolly pine plantations, with strong correlations between ALS and field measurements for canopy height and leaf area. New lidar indices were developed to predict overstory and understory leaf area more accurately, suggesting transferability of the methods across location, time, and sensor design.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Paige T. Williams, Randolph H. Wynne, Valerie A. Thomas, R. Defries
Summary: This study aims to develop a method to accurately map smallholder forest plantations in Andhra Pradesh, India, using multitemporal visible and near-infrared bands from the Sentinel-2 multispectral instruments. The results show that with high-quality training data, forest plantations can be distinguished from natural forests even when using only the Sentinel-2 VNIR bands, by incorporating multitemporal data from different years and seasons.
LAND DEGRADATION & DEVELOPMENT
(2021)
Article
Remote Sensing
Matthew J. Sumnall, Timothy J. Albaugh, David R. Carter, Rachel L. Cook, W. Cully Hession, Otavio C. Campoe, Rafael A. Rubilar, Randolph H. Wynne, Valerie A. Thomas
Summary: This study investigated the effect of pulse density on the estimation of forest characteristics using airborne laser scanning. The results showed that higher pulse densities led to greater accuracy in delineating individual tree crowns, while lower pulse densities resulted in decreased accuracy. The planting stem density also affected the accuracy of crown delineation. The estimation of tree height was largely unaffected by changes in tree density, while the estimation of crown horizontal diameter varied with both pulse and stem density.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)
Article
Biodiversity Conservation
Vasiliy T. Lakoba, Daniel Z. Atwater, Valerie E. Thomas, Brian D. Strahm, Jacob N. Barney
Summary: Johnsongrass, an invasive species, has undergone niche shifts in North America, with both agricultural and non-agricultural populations showing a slight shift towards colder climates. Agriculture plays a key role in providing suitable environments for Johnsongrass in otherwise suboptimal climates. Predictions show climatic suitability for Johnsongrass is expected to increase in the Upper Midwest and Great Plains by 2100.
GLOBAL ECOLOGY AND CONSERVATION
(2021)
Article
Environmental Sciences
Ryley C. Harris, Lisa M. Kennedy, Thomas J. Pingel, Valerie A. Thomas
Summary: This study demonstrates the use of drone-produced orthoimagery for assessing forest health and provides valuable information on stand mortality patterns and canopy gaps. The adoption of drone-based monitoring is important for conservation management.
Article
Forestry
Laura Buntrock, Valerie A. Thomas, Brian D. Strahm, Tom Fox, Robert Harrison, Austin Himes, Kim Littke
Summary: Patterns in foliar nitrogen stable isotope ratios have been studied to understand terrestrial nitrogen cycles and forest ecosystem productivity. This study focuses on examining the relationship between site index, foliar nitrogen concentration, foliar nitrogen stable isotope ratios, and spectral reflectance for managed Douglas-fir and loblolly pine plantations. The results show that foliar nitrogen stable isotope ratios and foliar nitrogen concentration are not well correlated for these tree species. However, multiple linear regression models suggest a strong predictive ability of spectroscopy data to quantify foliar nitrogen stable isotope ratios, with some models explaining more than 65% of the variance. Additionally, moderate to strong explanations of variance were found between site index and foliar nitrogen stable isotope ratios, as well as reflectance and site index in the Douglas-fir data set. Therefore, the development of relationships between foliar spectral reflectance, nitrogen stable isotope ratios, and measures of site productivity can aid in mapping canopy nitrogen stability for managed forests using remote sensing techniques.
Article
Forestry
Rachel L. Hammer, John R. Seiler, John A. Peterson, Valerie A. Thomas
Summary: Accurately predicting soil respiration (R-s) is crucial due to its impact on forest ecosystem productivity. This study investigated the effects of soil temperature, moisture, and vegetation composition on R-s. The results showed that soil temperature and moisture explained 82% of the variation in R-s. Monthly R-s rates varied among vegetation types, with cinnamon fern plots having higher rates in summer and hemlock plots having higher rates in dormant months.
Proceedings Paper
Geography, Physical
K. F. Huemmrich, P. E. K. Campbell, D. J. Harding, K. J. Ranson, R. Wynne, V Thomas, E. M. Middleton
Summary: This study successfully developed and tested multiple algorithms using data from the DLR Earth Sensing Imaging Spectrometer (DESIS) to remotely retrieve ecosystem productivity based on spectral reflectance. The algorithms demonstrated good accuracy across different locations, years, and times of observation.
1ST DESIS USER WORKSHOP - IMAGING SPECTROMETER SPACE MISSION, CALIBRATION AND VALIDATION, APPLICATIONS, METHODS
(2022)
Article
Forestry
Stella Z. Schons, Haripriya Gudimenda, Gregory S. Amacher, Kelly M. Cobourn, Randolph H. Wynne, Valerie A. Thomas
FOREST PRODUCTS JOURNAL
(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)