Yuhan "Douglas" Rao

Also known as: Yuhan (Douglas) Rao

Works (36)

Updated: April 4th, 2024 02:04

2024 article

Community-Driven Development of Tools to Improve AI-Readiness of the Open Environmental Data

Rao, Y., Redmon, R., & Khin, E. (2024, March 9).

By: Y. Rao* , R. Redmon & E. Khin

Source: ORCID
Added: March 15, 2024

2023 report

Developing Digital Twins for Earth Systems: Purpose, Requisites, and Benefits

By: Y. Rao* , R. Redmon, K. Dale, S. Haupt, A. Hopkinson, A. Bostrom, S. Boukabara, T. Geenen ...

Source: ORCID
Added: October 16, 2023

2023 article

Garbage in, garbage out: mitigating risks and maximizing benefits of AI in research

Hanson, B., Stall, S., Cutcher-Gershenfeld, J., Vrouwenvelder, K., Wirz, C., Rao, Y., & Peng, G. (2023, November 2). NATURE, Vol. 623, pp. 28–31.

By: B. Hanson *, S. Stall *, J. Cutcher-Gershenfeld *, K. Vrouwenvelder *, C. Wirz *, Y. Rao n , G. Peng *

author keywords: Computer science; Technology; Policy
Sources: ORCID, Web Of Science, NC State University Libraries
Added: November 1, 2023

2023 article

NASA TOPS Open Science 101

(2023, December 6). Zenodo.

Contributors: A. Adams, B. Almarzouq, M. Lacerda, J. Alwood, S. Alzahawi, F. Azevedo, R. Barry, N. Batalha ...

Source: ORCID
Added: February 6, 2024

2023 article

NASA TOPS Open Science 101

(2023, December 6). Zenodo.

Contributors: A. Adams, B. Almarzouq, M. Lacerda, J. Alwood, S. Alzahawi, F. Azevedo, R. Barry, N. Batalha ...

Source: ORCID
Added: February 6, 2024

2023 webpage

Opensciency - A core open science curriculum by and for the research community

Almarzouq, B., Azevedo, F., Batalha, N., Bayer, J., Bell, T., Bhogal, S., … Yehudi, Y. (2023, February 22).

By: B. Almarzouq, F. Azevedo, N. Batalha, J. Bayer, T. Bell, S. Bhogal, M. Black, S. Brown ...

Contributors: Y. Rao 

Source: ORCID
Added: March 3, 2023

2023 journal article

Socio-Environmental Determinants of Mental and Behavioral Disorders in Youth: A Machine Learning Approach

GEOHEALTH, 7(9).

By: L. Wertis *, M. Sugg *, J. Runkle n & D. Rao n

Contributors: Y. Rao n 

author keywords: machine learning; mental and behavioral disorders; distributed lag non-linear model; youths; ambient temperature; greenspace
TL;DR: Machine learning approaches are applied to identify key variables that predict MBD‐related emergency room (ER) visits in youths in select North Carolina cities among adolescent populations to inform the use of machine learning models for predicting MBD during high‐temperature events and identify variables that affect youth MBD responses during these events. (via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities (OpenAlex)
13. Climate Action (Web of Science)
Sources: ORCID, Web Of Science
Added: October 10, 2023

2023 journal article

Trustworthy Artificial Intelligence for Environmental Sciences An Innovative Approach for Summer School

BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 104(6), E1222–E1231.

By: A. McGovern *, D. Gagne *, C. Wirz *, I. Ebert-Uphoff *, A. Bostrom *, Y. Rao n , A. Schumacher*, M. Flora * ...

author keywords: KEYWORDS; Education; Artificial intelligence; Machine learning
TL;DR: The goal of this summer school was to teach a new generation of environmental scientists how to cross disciplines and develop approaches that integrate all three disciplinary perspectives and approaches in order to solve environmental science problems. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: July 31, 2023

2022 review

A review of Earth Artificial Intelligence

[Review of ]. COMPUTERS & GEOSCIENCES, 159.

By: Z. Sun *, L. Sandoval*, R. Crystal-Ornelas *, S. Mousavi *, J. Wang *, C. Lin *, N. Cristea *, D. Tong* ...

author keywords: Geosphere; Hydrology; Atmosphere; Artificial intelligence/machine learning; Big data; Cyberinfrastructure
UN Sustainable Development Goal Categories
14. Life Below Water (Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: February 7, 2022

2022 article

Are We at Risk of Losing the Current Generation of Climate Researchers to Data Science?

Jain, S., Mindlin, J., Koren, G., Gulizia, C., Steadman, C., Langendijk, G. S., … Rabanal, V. (2022, August). AGU ADVANCES, Vol. 3.

By: S. Jain *, J. Mindlin *, G. Koren *, C. Gulizia *, C. Steadman *, G. Langendijk *, M. Osman *, M. Abid *, Y. Rao n , V. Rabanal*

author keywords: climate model data; early career researchers; CMIP; climate science; climate research
UN Sustainable Development Goal Categories
13. Climate Action (Web of Science)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: July 26, 2022

2022 journal article

Bias of area counted from sub-pixel map: Origin and correction

SCIENCE OF REMOTE SENSING, 6.

By: Q. Dong *, X. Chen *, J. Chen *, D. Yin *, C. Zhang*, F. Xu *, Y. Rao n , M. Shen *, Y. Chen *, A. Stein *

author keywords: Land cover/land use; Sub-pixel mapping; Area bias correction; Small sample size; Abundance-dependent error; Probability distribution of abundances
UN Sustainable Development Goal Categories
13. Climate Action (Web of Science)
15. Life on Land (Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: July 31, 2023

2022 journal article

ClimateBench v1.0: A Benchmark for Data-Driven Climate Projections

JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 14(10).

By: D. Watson-Parris *, Y. Rao n , D. Olivie*, O. Seland *, P. Nowack *, G. Camps-Valls *, P. Stier*, S. Bouabid * ...

author keywords: climate; emulation; precipitation; machine learning
UN Sustainable Development Goal Categories
13. Climate Action (Web of Science; OpenAlex)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: October 31, 2022

2022 article

Earth and Space Science Informatics Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

Hills, D. J., Damerow, J. E., Ahmmed, B., Catolico, N., Chakraborty, S., Coward, C. M., … Yao, T. (2022, April). EARTH AND SPACE SCIENCE, Vol. 9.

By: D. Hills *, J. Damerow*, B. Ahmmed *, N. Catolico *, S. Chakraborty *, C. Coward *, R. Crystal-Ornelas *, W. Duncan * ...

TL;DR: The challenge is to coordinate the development of standards, curation practices, and tools that enable integrating and reusing multiple data types, software, multi‐scale models, and machine learning approaches across disciplines in a way that is as open and/or FAIR as ethically possible. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: May 2, 2022

2022 speech

Trustworthy Artificial Intelligence for Environmental Science (TAI4ES) Summer School 2022

McGovern, A., Gagne, D., Ebert-Uphoff, I., Bostrom, A., Wirz, C., Rao, D., … Haynes, K. (2022, June).

By: A. McGovern, D. Gagne, I. Ebert-Uphoff, A. Bostrom, C. Wirz, D. Rao, A. Schumacher, M. Flora ...

Contributors: Y. Rao 

Source: ORCID
Added: March 9, 2023

2022 article

Warming does not delay the start of autumnal leaf coloration but slows its progress rate

Jiang, N., Shen, M., Ciais, P., Campioli, M., Penuelas, J., Korner, C., … Zhao, W. (2022, August 14). GLOBAL ECOLOGY AND BIOGEOGRAPHY, Vol. 8.

By: N. Jiang *, M. Shen *, P. Ciais*, M. Campioli *, J. Penuelas*, C. Korner *, R. Cao *, S. Piao * ...

author keywords: autumnal leaf senescence; global warming; leaf coloration onset; Northern Hemisphere; photoperiod
UN Sustainable Development Goal Categories
13. Climate Action (Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: August 29, 2022

2021 report

A science paradigm shift is needed for Earth and Environmental Systems Sciences (EESS) to integrate Knowledge-Guided Artificial Intelligence (KGAI) and lead new EESS-KGAI theories

By: N. Voisin*, A. Bennett, Y. Fang, G. Nearing, B. Nijssen & Y. Rao 

TL;DR: A science paradigm shift is needed for Earth and Environmental Systems Sciences (EESS) to integrate Knowledge-Guided Artificial Intelligence (KGAI) and lead new EESS-K GAI theories. (via Semantic Scholar)
Source: ORCID
Added: March 9, 2023

2021 journal article

Adopting "Difference-in-Differences" Method to Monitor Crop Response to Agrometeorological Hazards with Satellite Data: A Case Study of Dry-Hot Wind

REMOTE SENSING, 13(3).

By: S. Wang *, Y. Rao n , J. Chen *, L. Liu * & W. Wang *

author keywords: remote sensing; vegetation indices; winter wheat; heat stress; spectral response; shape model fitting; damage assessment
TL;DR: A general difference-in-differences (DID) framework to monitor crop response to agrometeorological hazards at near real-time using widely accessible remotely sensed vegetation indices (VIs) is presented and can improve the crop yield forecast. (via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action (Web of Science)
15. Life on Land (Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: March 1, 2021

2020 journal article

Can changes in autumn phenology facilitate earlier green-up date of northern vegetation?

AGRICULTURAL AND FOREST METEOROLOGY, 291.

By: M. Shen *, N. Jiang *, D. Peng*, Y. Rao n , Y. Huang *, Y. Fu *, W. Yang *, X. Zhu * ...

author keywords: Autumn phenology; Legacy effect; Climate change; Northern hemisphere; Phenological sequence; Spring phenology
UN Sustainable Development Goal Categories
13. Climate Action (Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: August 24, 2020

2020 journal article

Response of winter wheat to spring frost from a remote sensing perspective: Damage estimation and influential factors

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 168, 221–235.

By: S. Wang *, J. Chen *, Y. Rao n , L. Liu *, W. Wang * & Q. Dong *

author keywords: Spring frost; Winter wheat; Damage assessment; Remote sensing; North China
UN Sustainable Development Goal Categories
13. Climate Action (Web of Science)
15. Life on Land (Web of Science)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: September 28, 2020

2020 journal article

Short-term effects of specific humidity and temperature on COVID-19 morbidity in select US cities

SCIENCE OF THE TOTAL ENVIRONMENT, 740.

By: J. Runkle n, M. Sugg *, R. Leeper  n, Y. Rao n , J. Matthews n & J. Rennie n

author keywords: COVID-19 morbidity; Distributed lag non-linear model; Time-stratified case-crossover; Weather; Seasonality
MeSH headings : Betacoronavirus; COVID-19; Cities; Coronavirus Infections / mortality; Humans; Humidity; Pandemics; Pneumonia, Viral / mortality; SARS-CoV-2; Temperature
TL;DR: The results suggest that weather should be considered in infectious disease modeling efforts and future work is needed over a longer time period and across different locations to clearly establish the weather-COVID19 relationship. (via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities (OpenAlex)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: September 14, 2020

2019 journal article

Enterprise LST Algorithm Development and Its Evaluation with NOAA 20 Data

Remote Sensing, 11(17), 2003.

By: Y. Liu *, Y. Yu*, P. Yu *, H. Wang * & Y. Rao* 

author keywords: land surface temperature (LST); enterprise algorithm; VIIRS; NOAA 20; split window
TL;DR: This research focuses on the enterprise LST algorithm design, development and its evaluations with the National Oceanic and Atmospheric Administration’s (NOAA) 20 (N20) Visible Infrared Imaging Radiometer Suite (VIIRS) data available since 5 January 2018. (via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action (OpenAlex)
Source: ORCID
Added: January 3, 2023

2019 journal article

Estimating daily average surface air temperature using satellite land surface temperature and top-of-atmosphere radiation products over the Tibetan Plateau

Remote Sensing of Environment, 234, 111462.

By: Y. Rao* , S. Liang *, D. Wang *, Y. Yu*, Z. Song, Y. Zhou *, M. Shen *, B. Xu *

UN Sustainable Development Goal Categories
13. Climate Action (OpenAlex)
Source: ORCID
Added: March 9, 2023

2018 journal article

A practical sampling method for assessing accuracy of detected land cover/land use change: Theoretical analysis and simulation experiments

ISPRS Journal of Photogrammetry and Remote Sensing, 144, 379–389.

By: Y. Li *, J. Chen * & Y. Rao* 

author keywords: Land use land cover change; Accuracy assessment; Transition accuracy; Sample design
TL;DR: This study provides an iterative sampling framework to ensure that the precision of the estimated overall transition accuracy meets the users’ predefined requirement and it is robust against different properties of classification results and target landscapes. (via Semantic Scholar)
UN Sustainable Development Goal Categories
15. Life on Land (OpenAlex)
Source: ORCID
Added: January 3, 2023

2018 journal article

Land Surface Air Temperature Data Are Considerably Different Among BEST‐LAND, CRU‐TEM4v, NASA‐GISS, and NOAA‐NCEI

Journal of Geophysical Research: Atmospheres, 123(11), 5881–5900.

By: Y. Rao* , S. Liang * & Y. Yu*

author keywords: land surface air temperature; intercomparison; surface warming; warming hiatus
UN Sustainable Development Goal Categories
13. Climate Action (OpenAlex)
Source: ORCID
Added: January 3, 2023

2016 journal article

A Simple Method for Detecting Phenological Change From Time Series of Vegetation Index

IEEE Transactions on Geoscience and Remote Sensing, 54(6), 3436–3449.

By: J. Chen *, Y. Rao* , M. Shen *, C. Wang *, Y. Zhou *, L. Ma *, Y. Tang *, . Yang *

author keywords: Cross-correlogram spectral matching (CCSM); moderate resolution imaging spectroradiometer (MODIS); phenological change; start of season (SOS); vegetation index (VI)
TL;DR: Compared with non-CCSM methods, CCSM-P is more accurate and less dependent on prior knowledge (thresholds or predefined functions), which indicates its effectiveness and applicability for detecting year-to-year variations and long-term change trends in phenology, and should facilitate more reliable assessments of phenological changes in climate change studies. (via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action (OpenAlex)
Source: ORCID
Added: January 3, 2023

2016 journal article

Land cover change detection by integrating object-based data blending model of Landsat and MODIS

Remote Sensing of Environment, 184, 374–386.

By: M. Lu, J. Chen *, H. Tang *, Y. Rao* , P. Yang * & W. Wu *

author keywords: Change detection; Object-based; Data blending; NDVI gradient difference; NDVI time series
TL;DR: The approach proposed in this study can effectively detect change areas when Landsat images are acquired from different seasons and is more suitable for change detection application compared with the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and NDVI Linear Mixing Growth Model (NDVI-LMGM). (via Semantic Scholar)
UN Sustainable Development Goal Categories
15. Life on Land (OpenAlex)
Source: ORCID
Added: January 3, 2023

2015 journal article

A method for screening climate change-sensitive infectious diseases

International Journal of Environmental Research and Public Health, 12(1), 767–783.

By: Y. Wang *, Y. Rao* , X. Wu *, H. Zhao * & J. Chen *

Contributors: Y. Wang *, Y. Rao* , X. Wu *, H. Zhao * & J. Chen *

author keywords: climate change; infectious diseases; climate change-sensitive diseases; relative sensitivity; screening method
MeSH headings : Child; Child, Preschool; China / epidemiology; Climate Change; Communicable Diseases / epidemiology; Humans; Infant; Infant, Newborn; Malaria / epidemiology; Mass Screening; Schistosomiasis / epidemiology; Temperature
TL;DR: This research shows that absolute humidity has a critical influence on many observed infectious diseases in Anhui Province, including dysentery, hand, foot and mouth disease, hepatitis A, hemorrhagic fever, typhoid fever, malaria, meningitis, influenza and schistosomiasis. (via Semantic Scholar)
Source: ORCID
Added: January 3, 2023

2015 conference paper

A quantitative assessment of multiple scattering in plant-soil mixtures and the implications on nonlinear spectral unmixing models

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

By: J. Wang *, X. Cao *, J. Chen *, D. Liu * & Y. Rao* 

TL;DR: A Monte Carlo ray-tracing model is applied to test the correlations between multiple scattering reflectances and endmember products in the Bilinear Model, and the correlations are found linear, proving the rationality of this approximation. (via Semantic Scholar)
UN Sustainable Development Goal Categories
15. Life on Land (OpenAlex)
Source: ORCID
Added: January 3, 2023

2015 journal article

An improved method for producing high spatial-resolution NDVI time series datasets with multi-temporal MODIS NDVI data and Landsat TM/ETM+ images

Remote Sensing, 7(6), 7865–7891.

By: Y. Rao* , X. Zhu *, J. Chen * & J. Wang *

Contributors: Y. Rao* , X. Zhu *, J. Chen * & J. Wang *

author keywords: NDVI time series; linear mixing model; MODIS; Landsat TM/ETM; data fusion
TL;DR: Comparisons between NDVI-LMGM and current methods show that the proposed method is more accurate and efficient than current methods and will benefit land surface process research, which requires a dense NDVI time-series dataset with high spatial resolution. (via Semantic Scholar)
UN Sustainable Development Goal Categories
15. Life on Land (OpenAlex)
Source: ORCID
Added: January 3, 2023

2015 journal article

Identification of climate factors related to human infection with avian influenza A H7N9 and H5N1 viruses in China

Scientific Reports, 5.

By: J. Li *, Y. Rao* , Q. Sun*, X. Wu *, J. Jin *, Y. Bi *, J. Chen *, F. Lei * ...

Contributors: J. Li *, Y. Rao* , Q. Sun*, X. Wu *, J. Jin *, Y. Bi *, J. Chen *, F. Lei * ...

MeSH headings : Algorithms; Atmospheric Pressure; China / epidemiology; Climate; Disease Outbreaks / prevention & control; Geography; Host-Pathogen Interactions; Humans; Humidity; Influenza A Virus, H5N1 Subtype / physiology; Influenza A Virus, H7N9 Subtype / physiology; Influenza, Human / epidemiology; Influenza, Human / virology; Models, Theoretical; Risk Assessment; Risk Factors; Species Specificity; Temperature
TL;DR: Analysis of human influenza infections in China revealed integrated predictive meteorological factors rooted in statistic data that enable the establishment of preventive actions and precautionary measures against future outbreaks and proposes a risky window for H7N9 infection and H5N1 infection. (via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action (OpenAlex)
Source: ORCID
Added: January 3, 2023

2015 journal article

Temperature sensitivity of spring vegetation phenology correlates to within-spring warming speed over the Northern Hemisphere

Ecological Indicators, 50, 62–68.

By: C. Wang *, R. Cao *, J. Chen *, Y. Rao*  & Y. Tang *

Contributors: C. Wang *, R. Cao *, J. Chen *, Y. Rao*  & Y. Tang *

author keywords: Climate change; NDVI time series; Spring vegetation phenology; Spring temperature; Temperature sensitivity
Source: ORCID
Added: January 3, 2023

2014 journal article

A combination of TsHARP and thin plate spline interpolation for spatial sharpening of thermal imagery

Remote Sensing, 6(4), 2845–2863.

By: X. Chen *, W. Li *, J. Chen *, Y. Rao*  & Y. Yamaguchi*

Contributors: X. Chen *, W. Li *, J. Chen *, Y. Rao*  & Y. Yamaguchi*

author keywords: thermal sharpening; land surface temperature; TsHARP; thin plate spline; error estimation
TL;DR: This paper proposes to combine the TsHarp and TPS methods to enhance the advantages of each and shows that the proposed combined method performs more robustly and accurately than TsHARP. (via Semantic Scholar)
UN Sustainable Development Goal Categories
15. Life on Land (OpenAlex)
Source: ORCID
Added: January 3, 2023

2014 journal article

A simple error estimation method for linear-regression-based thermal sharpening techniques with the consideration of scale difference

Geo-Spatial Information Science, 17(1), 54–59.

By: X. Chen *, W. Li *, J. Chen *, W. Zhan * & Y. Rao* 

author keywords: thermal sharpening; error estimation; linear regression; equivalent random sample size
TL;DR: An improved error estimation method based on classical linear regression theory for the linear-regression-based TSP techniques with the consideration of the scale difference is developed, which employs a novel term named equivalent random sample size to reflect thescale difference. (via Semantic Scholar)
Source: ORCID
Added: January 3, 2023

2014 journal article

Earlier vegetation green-up has reduced spring dust storms

Scientific Reports, 4.

By: B. Fan *, L. Guo *, N. Li *, J. Chen *, H. Lin*, X. Zhang *, M. Shen *, Y. Rao* , C. Wang *, L. Ma *

Contributors: B. Fan *, L. Guo *, N. Li *, J. Chen *, H. Lin*, X. Zhang *, M. Shen *, Y. Rao* , C. Wang *, L. Ma *

TL;DR: The relationships between recorded spring dust storm outbreaks and satellite-derived vegetation green-up date in Inner Mongolia, Northern China from 1982 to 2008 are examined to investigate the impacts of vegetation spring growth on dust storms, finding a significant dampening effect of advanced vegetation growth on spring dust storms. (via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action (OpenAlex)
Source: ORCID
Added: January 3, 2023

2013 conference paper

Quantitative assessment of the different methods addressing the endmember variability

International Geoscience and Remote Sensing Symposium (IGARSS), 3317–3320.

By: Y. Rao* , J. Chen *, X. Chen * & J. Wang *

Contributors: Y. Rao* , J. Chen *, X. Chen * & J. Wang *

author keywords: SMA; endmember variability; simulated data; quantitative
TL;DR: The comparison result shows that MESMA seems to be the best in unmixing accuracy, however, sensitive to noise and large computation loads also made M ESMA less satisfactory, while other methods could supersede MESma at specific situations. (via Semantic Scholar)
Source: ORCID
Added: January 3, 2023

journal article

混合像元分解技术及其进展

遥感学报, 20(5), 1102. http://www.jors.cn/jrs/ch/reader/view_abstract.aspx?file_no=r16169&flag=1

Yuhan "Douglas" Rao

www.jors.cn
Source: ORCID
Added: January 3, 2023

Employment

Updated: March 2nd, 2023 06:23

2022 - present

North Carolina State University Asheville, North Carolina, US
Research Scientist North Carolina Institute for Climate Studies

2019 - 2022

North Carolina State University Asheville, North Carolina, US
Postdoctoral Research Scholar North Carolina Institute for Climate Studies

2015 - 2019

University of Maryland, College Park College Park, Maryland, US
Graduate Research Assistant Earth System Science Interdisciplinary Center

Education

Updated: January 3rd, 2023 15:59

2014 - 2019

University of Maryland College Park, Maryland, US
Ph.D. (Geographical Sciences) Department of Geographical Sciences

2011 - 2014

Beijing Normal University Beijing, Beijing, CN
Master of Engineering (Cartography and Geo-information Engineering) Academy of Disaster Reduction and Emergency Management

2007 - 2011

Beijing Normal University Beijing, Beijing, CN
Bachelor of Science (Statistics) School of Mathematical Sciences

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