NASA Prediction of Worldwide Energy Resources (POWER)

Tutorials

• About the Prediction Of Worldwide Energy Resources (POWER) Project ArcGIS StoryMap. by The POWER Project
  
• Accessing and Subsetting POWER data, from AWS S3 using Python. by The POWER Project
  

Tools & Applications

• NASA POWER NetCDF Data Download by The POWER Project
  
• POWER Application Programming Interface (API) by The POWER Project
  
• POWER Data Access Viewer (DAV) by The POWER Project
  

Publications

• A solar azimuth formula that renders circumstantial treatment unnecessary without compromising mathematical rigor: Mathematical setup, application and extension of a formula based on the subsolar point and atan2 function by Zhang, T., P. W. Stackhouse, B. Macpherson, and J. C. Mikovitz
  
• Application of a global-to-beam irradiance model to the NASA GEWEX SRB dataset: An extension of the NASA Surface meteorology and Solar Energy datasets by Zhang, T., P. W. Stackhouse, W. S. Chandler, and D. J. Westberg
  
• Application of Satellite Sensor Data and Models for Energy Management by Zell, E., J. Engel-Cox, R. Eckman, and P. Stackhouse
  
• Association between solar insolation and a history of suicide attempts in bipolar I disorder by Bauer M, et al., Stackhouse PW Jr., et al.
  
• CEOS contributions to informing energy management and policy decision making using space-based Earth observations by Eckman, R. S., and P. W. Stackhouse
  
• Enhancing Climate Resilience at NASA Centers: A Collaboration between Science and Stewardship by Rosenzweig, C., and Coauthors
  
• Evaluation of NASA satellite- and assimilation model-derived long-term daily temperature data over the continental US by White, J. W., G. Hoogenboom, P. W. Stackhouse, and J. M. Hoell
  
• Evaluation of Satellite-Based, Modeled-Derived Daily Solar Radiation Data for the Continental United States by White, J. W., G. Hoogenboom, P. W. Wilkens, P. W. Stackhouse, and J. M. Hoel
  
• Global Surface Solar Energy Anomalies Including El Nino and La Nina Years. by C. H., and Coauthors
  
• Modeling the potential for thermal concentrating solar power technologies by Zhang, Y., S. J. Smith, G. P. Kyle, and P. W. Stackhouse
  
• NASA Climatological Data for Renewable Energy Assessment by Chandler, W. S., C. H. Whitlock, and P. W. Stackhouse
  
• The Contribution of Solar Brightening to the US Maize Yield Trend by Tollenaar, T., J. Fridgen, P. Tyagi, P. W. Stackhouse Jr., and S. Kumudini
  
• Variations in seasonal solar insolation are associated with a history of suicide attempts in bipolar I disorder by Bauer, M., and Coauthors
  

2021 Amazon Last Mile Routing Research Challenge Dataset

Tools & Applications

• AWS Last Mile Route Sequence Optimization by Chen Wu, Yin Song, Verdi March, Eden Duthi
  
• Code repository used for the 2021 Amazon Routing Research Challenge (this repository is included for reference and documentation purposes only, you do not need to install it to access the data) by CAVE Lab, MIT Center for Transportation and Logistics
  

Publications

• 2021 Amazon Last Mile Routing Research Challenge: Data Set by Daniel Merchán, Jatin Arora, Julian Pachon, Karthik Konduri, Matthias Winkenbach, Steven Parks, Joseph Noszek
  
• Can language models be used for real-world urban-delivery route optimization? by Yang Liu, Fanyou Wu, Zhiyuan Liu, Kai Wang, Feiyue Wang, Xiaobo Qu
  
• Constrained Local Search for Last-Mile Routing by William Cook, Stephan Held, Keld Helsgaun
  
• Crowdkeeping in Last-Mile Delivery by Xin Wang , Okan Arslan , Erick Delage
  
• Does parking matter? The impact of parking time on last-mile delivery optimization by Sara Reed, Ann Melissa Campbell, Barrett W. Thomas
  
• Human-Centric Parcel Delivery at Deutsche Post with Operations Research and Machine Learning by Uğur Arikan , Thorsten Kranz, Baris Cem Sal, Severin Schmitt, Jonas Witt
  
• Integrating driver behavior into last-mile delivery routing - Combining machine learning and optimization in a hybrid decision support framework by Peter Dieter, Matthew Caron, Guido Schryen
  
• Inverse Optimization for Routing Problems by Pedro Zattoni Scroccaro, Piet van Beek, Peyman Mohajerin Esfahani, Bilge Atasoy
  
• Learn global and optimize local A data-driven methodology for last-mile routing by Mayukh Ghosh, Alex Kuiper, Roshan Mahes, Donato Maragno
  
• Machine Learning for Data-Driven Last-Mile Delivery Optimization by Sami Serkan Özarik, Paulo da Costa, Alexandre M. Florio
  
• Making opportunity sales in attended home delivery by Çelen Naz Ötken, Bariş Yildiz, Okan Arslan, Gilbert Laporte
  
• Planning robust drone-truck delivery routes under road traffic uncertainty by Yu Yang, Chiwei Yan, Yufeng Cao, Roberto Roberti
  
• Predicting drivers route trajectories in last-mile delivery using a pair-wise attention-based pointer neural network by Baichuan Mo, Qingyi Wang, Xiaotong Guo, Matthias Winkenbach, Jinhua Zhao
  
• Probability estimation and structured output prediction for learning preferences in last mile delivery by Rocsildes Canoy, Victor Bucarey, Jayanta Mandi, Maxime Mulamba, Yves Molenbruch, Tias Guns
  
• The Driver-Aide Problem Coordinated Logistics for Last-Mile Delivery by S. Raghavan , Rui Zhang
  

Speedtest by Ookla Global Fixed and Mobile Network Performance Maps

Tutorials

• Bootstrapping Dask on 1000 cores with AWS Fargate by Imri Paran
  AWS FargateAmazon EKS
• How to deliver performant GIS desktop applications with Amazon AppStream 2.0 by Ethan Fahy and Spencer DeBrosse
  Amazon AppStream 2.0Amazon RDS
• Launching Lonboard - A Python library for extremely fast geospatial vector data visualization in Jupyter by Kyle Barron
  
• New Year, Great Data: The Best Ookla Open Data Projects We’ve Seen So Far by Katie Jolly
  

iSDAsoil

Tutorials

• iSDAsoil Python tutorial by Matt Miller
  AWS CloudFormationAmazon SageMaker

Tools & Applications

• iSDAsoil homepage - view soil property maps online by iSDA
  
• iSDAsoil liming demo app on Observable by Jamie Collinson
  

Publications

• African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning by Tomislav Hengl, Matthew A. E. Miller, Josip Križan, Keith D. Shepherd, Andrew Sila, Milan Kilibarda, Ognjen Antonijević, Luka Glušica, Achim Dobermann, Stephan M. Haefele, Steve P. McGrath, Gifty E. Acquah, Jamie Collinson, Leandro Parente, Mohammadreza Sheykhmousa, Kazuki Saito, Jean-Martial Johnson, Jordan Chamberlin, Francis B. T. Silatsa, Martin Yemefack, John Wendt, Robert A. MacMillan, Ichsani Wheeler & Jonathan Crouch
  

NIFS Large Helical Device (LHD) Experiment

Tutorials

• Data handling in the LHD experiments -- Guide for the collaborator (pdf) by Satoshi Ohdachi
  

Tools & Applications

• How to retrieve diagnostic raw data and/or primarily processed data using "Retrieve" by NIFS LABCOM
  

Publications

• Data Acquisition and Management System of LHD by Hideya Nakanishi, et al.
  

EMBER Open Datasets

Tutorials

• Get To Know A Dataset - EMBER by EMBER Team
  
  

Publications

• Mapping the landscape of social behavior by Ugne Klibaite, Tianqing Li, Diego Aldarondo, Jumana F Akoad, Bence P Ölveczky, Timothy W Dunn.
  

Legal Entity Identifier (LEI) and Legal Entity Reference Data (LE-RD)

Publications

• AWS hosts new open dataset to help businesses identify climate finance risks and investments by AWS Public Sector Blog Team
  

Mars Spectrometry 2: Gas Chromatography for the Sample Analysis at Mars Data (SAM) Instrument

Publications

• Mars Spectrometry: Mars Spectrometry 2 (Challenge Results) by DrivenData team and NASA partners
  

Mars Spectrometry: Detect Evidence for Past Habitability

Publications

• Mars Spectrometry: Detect Evidence for Past Habitability (Challenge Results) by DrivenData team and NASA partners