Frontiers in Big Data | Data-driven Climate Sciences

Original Research

Published on 15 Feb 2022

Daily Spatial Complete Soil Moisture Mapping Over Southeast China Using CYGNSS and MODIS Data

in Data-driven Climate Sciences

Ting Yang
Zhigang Sun
Jundong Wang
Sen Li

Frontiers in Big Data

doi 10.3389/fdata.2021.777336

2,956 views
3 citations

Original Research

Published on 10 Feb 2022

Development of a Machine Learning Approach for Local-Scale Ozone Forecasting: Application to Kennewick, WA

in Data-driven Climate Sciences

Kai Fan
Ranil Dhammapala
Kyle Harrington
Ryan Lamastro
Brian Lamb
Yunha Lee

Frontiers in Big Data

doi 10.3389/fdata.2022.781309

2,952 views
7 citations

Original Research

Published on 04 Feb 2022

Runoff Forecasting Using Machine-Learning Methods: Case Study in the Middle Reaches of Xijiang River

in Data-driven Climate Sciences

Lu Xiao
Ming Zhong
Dawei Zha

Frontiers in Big Data

doi 10.3389/fdata.2021.752406

3,746 views
10 citations

Original Research

Published on 21 Dec 2021

DroughtCast: A Machine Learning Forecast of the United States Drought Monitor

in Data-driven Climate Sciences

Colin Brust
John S. Kimball
Marco P. Maneta
Kelsey Jencso
Rolf H. Reichle

Frontiers in Big Data

doi 10.3389/fdata.2021.773478

10,464 views
21 citations

Original Research

Published on 25 Oct 2021

Automated Analysis of the US Drought Monitor Maps With Machine Learning and Multiple Drought Indicators

in Data-driven Climate Sciences

Pouyan Hatami Bahman Beiglou
Lifeng Luo
Pang-Ning Tan
Lisi Pei

Frontiers in Big Data

doi 10.3389/fdata.2021.750536

3,083 views
3 citations

Methods

Published on 18 Oct 2021

Testing a Generalizable Machine Learning Workflow for Aquatic Invasive Species on Rainbow Trout (Oncorhynchus mykiss) in Northwest Montana

in Data-driven Climate Sciences

S. Carter
C. B. van Rees
B. K. Hand
C. C. Muhlfeld
G. Luikart
J. S. Kimball

Frontiers in Big Data

doi 10.3389/fdata.2021.734990

4,405 views
9 citations

Original Research

Published on 24 Aug 2021

Benchmarking of Data-Driven Causality Discovery Approaches in the Interactions of Arctic Sea Ice and Atmosphere

in Data-driven Climate Sciences

Yiyi Huang
Matthäus Kleindessner
Alexey Munishkin
Debvrat Varshney
Pei Guo
Jianwu Wang

Frontiers in Big Data

doi 10.3389/fdata.2021.642182

6,478 views
16 citations

Original Research

Published on 26 Jul 2021

Comparative Analysis of Energy Use and Greenhouse Gas Emission of Diesel and Electric Trucks for Food Distribution in Gowanus District of New York City

in Data-driven Climate Sciences

Raghul Elangovan
Ondrea Kanwhen
Ziqian Dong
Ahmed Mohamed
Roberto Rojas-Cessa

Frontiers in Big Data

doi 10.3389/fdata.2021.693820

7,396 views
11 citations

Original Research

Published on 22 Jun 2021

Using 3D CityGML for the Modeling of the Food Waste and Wastewater Generation—A Case Study for the City of Montréal

in Data-driven Climate Sciences

Reiner Braun
Rushikesh Padsala
Tahereh Malmir
Soufia Mohammadi
Ursula Eicker

Frontiers in Big Data

doi 10.3389/fdata.2021.662011

5,584 views
12 citations

Original Research

Published on 05 May 2021

Iowa Urban FEWS: Integrating Social and Biophysical Models for Exploration of Urban Food, Energy, and Water Systems

in Data-driven Climate Sciences

Jan Thompson
Baskar Ganapathysubramanian
Wei Chen
Michael Dorneich
Philip Gassman
Caroline Krejci
Matthew Liebman
Ajay Nair
Ulrike Passe
Nicholas Schwab

Frontiers in Big Data

doi 10.3389/fdata.2021.662186

4,656 views
14 citations

Original Research

Published on 18 Jan 2021

Monitoring Crop Status in the Continental United States Using the SMAP Level-4 Carbon Product

in Data-driven Climate Sciences

Patrick M. Wurster
Marco Maneta
John S. Kimball
K. Arthur Endsley
Santiago Beguería

Frontiers in Big Data

doi 10.3389/fdata.2020.597720

5,193 views
3 citations

Original Research

Published on 28 Oct 2020

Ensemble Machine Learning Approach Improves Predicted Spatial Variation of Surface Soil Organic Carbon Stocks in Data-Limited Northern Circumpolar Region

in Data-driven Climate Sciences

Umakant Mishra
Sagar Gautam
William J. Riley
Forrest M. Hoffman

Frontiers in Big Data

doi 10.3389/fdata.2020.528441

6,342 views
33 citations

Original Research

Published on 03 Jun 2020

Deep Learning Optimizes Data-Driven Representation of Soil Organic Carbon in Earth System Model Over the Conterminous United States

in Data-driven Climate Sciences

Feng Tao
Zhenghu Zhou
Yuanyuan Huang
Qianyu Li
Xingjie Lu
Shuang Ma
Xiaomeng Huang
Yishuang Liang
Gustaf Hugelius
Lifen Jiang

Frontiers in Big Data

doi 10.3389/fdata.2020.00017

12,285 views
38 citations

Original Research

Published on 09 Apr 2020

Agricultural Drought Monitoring via the Assimilation of SMAP Soil Moisture Retrievals Into a Global Soil Water Balance Model

in Data-driven Climate Sciences

Iliana E. Mladenova
John D. Bolten
Wade Crow
Nazmus Sazib
Curt Reynolds

Frontiers in Big Data

doi 10.3389/fdata.2020.00010

14,222 views
55 citations

Original Research

Published on 28 Jan 2020

Tropical Cyclone Track Forecasting Using Fused Deep Learning From Aligned Reanalysis Data

in Data-driven Climate Sciences

Sophie Giffard-Roisin
Mo Yang
Guillaume Charpiat
Christina Kumler Bonfanti
Balázs Kégl
Claire Monteleoni

Frontiers in Big Data

doi 10.3389/fdata.2020.00001

29,865 views
76 citations

Original Research

Published on 23 Jan 2020

Spatial Pattern and Environmental Drivers of Acid Phosphatase Activity in Europe

in Data-driven Climate Sciences

Yan Sun
Daniel S. Goll
Philippe Ciais
Shushi Peng
Olga Margalef
Dolores Asensio
Jordi Sardans
Josep Peñuelas

Frontiers in Big Data

doi 10.3389/fdata.2019.00051

6,588 views
18 citations

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Articles

Daily Spatial Complete Soil Moisture Mapping Over Southeast China Using CYGNSS and MODIS Data

Development of a Machine Learning Approach for Local-Scale Ozone Forecasting: Application to Kennewick, WA

Runoff Forecasting Using Machine-Learning Methods: Case Study in the Middle Reaches of Xijiang River

DroughtCast: A Machine Learning Forecast of the United States Drought Monitor

Automated Analysis of the US Drought Monitor Maps With Machine Learning and Multiple Drought Indicators

Testing a Generalizable Machine Learning Workflow for Aquatic Invasive Species on Rainbow Trout (Oncorhynchus mykiss) in Northwest Montana

Benchmarking of Data-Driven Causality Discovery Approaches in the Interactions of Arctic Sea Ice and Atmosphere

Comparative Analysis of Energy Use and Greenhouse Gas Emission of Diesel and Electric Trucks for Food Distribution in Gowanus District of New York City

Using 3D CityGML for the Modeling of the Food Waste and Wastewater Generation—A Case Study for the City of Montréal

Iowa Urban FEWS: Integrating Social and Biophysical Models for Exploration of Urban Food, Energy, and Water Systems

Monitoring Crop Status in the Continental United States Using the SMAP Level-4 Carbon Product

Ensemble Machine Learning Approach Improves Predicted Spatial Variation of Surface Soil Organic Carbon Stocks in Data-Limited Northern Circumpolar Region

Deep Learning Optimizes Data-Driven Representation of Soil Organic Carbon in Earth System Model Over the Conterminous United States

Agricultural Drought Monitoring via the Assimilation of SMAP Soil Moisture Retrievals Into a Global Soil Water Balance Model

Tropical Cyclone Track Forecasting Using Fused Deep Learning From Aligned Reanalysis Data

Spatial Pattern and Environmental Drivers of Acid Phosphatase Activity in Europe