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
  

Low Altitude Disaster Imagery (LADI) Dataset

Tutorials

• LADI v1 Tutorials by Andrew Weinert, Jianyu Mao, Kiana Harris, Nae-Rong Chang, Caleb Pennell, Yiming Ren, Ryan Earley, Nadia Dimitrova
  
• LADI v2 Overview by Jeffrey Liu, Sam Scheele, Katherine Picchione
  

Tools & Applications

• NIST TRECVID 2020 - Disaster Scene Description and Indexing (DSDI) by TREC Video Retrieval Evaluation (TRECVID)
  
• Remote Sensing for Disaster Response Course by Beaver Works Summer Institute
  

Publications

• Accelerate disaster response with computer vision for satellite imagery using Amazon SageMaker and Amazon Augmented AI by Vamshi Krishna Enabothala, Morgan Dutton, and Sandeep Verma
  
• An overview on the evaluated video retrieval tasks at TRECVID 2022 by George Awad, Keith Curtis, Asad Butt, Jonathan Fiscus, Afzal Godil, Yooyoung Lee, Andrew Delgado, Eliot Godard, Lukas Diduch, Jeffrey Liu, Yvette Graham, Georges Quenot
  
• Evaluating Multiple Video Understanding and Retrieval Tasks at TRECVID 2021 by George Awad, Asad Butt, Keith Curtis, Jonathan G. Fiscus, Afzal A. Godil, Yooyoung Lee, Andrew Delgado, Eliot Godard, Baptiste Chocot, Lukas Diduch, Jeffrey Liu, Yvette Graham, Gareth Jones, Georges Quenot
  
• Large Scale Organization and Inference of an Imagery Dataset for Public Safety by Jeffrey Liu, David Strohschein, Siddharth Samsi, Andrew Weinert
  
• Train and Deploy an Image Classifier for Disaster Response by Jianyu Mao, Kiana Harris, Nae-Rong Chang, Caleb Pennell, Yiming Ren
  
• TRECVID 2020: A comprehensive campaign for evaluating video retrieval tasks across multiple application domains by George Awad, Asad A. Butt, Keith Curtis, Jonathan Fiscus, Afzal Godil, Yooyoung Lee, Andrew Delgado, Jesse Zhang, Eliot Godard, Baptiste Chocot, Lukas Diduch, Jeffrey Liu, Alan F. Smeaton, Yvette Graham, Gareth J. F. Jones, Wessel Kraaij, Georges Quenot
  
• Video Testing at the FirstNet Innovation and Test Lab Using a Public Safety Dataset by Chris Budny, Jeffrey Liu, Andrew Weinert
  

nuScenes

Tutorials

• nuImages devkit tutorial by Motional
  
  
• nuScenes CAN bus tutorial by Motional
  
  
• nuScenes devkit tutorial by Motional
  
  
• nuScenes lidarseg and panoptic tutorial by Motional
  
  
• nuScenes Map Expansion Tutorial by Motional
  
  
• nuScenes prediction tutorial by Motional
  
  

Tools & Applications

• nuScenes devkit by Motional
  

Publications

• nuScenes: A multimodal dataset for autonomous driving by Holger Caesar, Varun Bankiti, Alex H. Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, Oscar Beijbom
  
• Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking by Whye Kit Fong, Rohit Mohan, Juana Valeria Hurtado, Lubing Zhou, Holger Caesar, Oscar Beijbom, Abhinav Valada
  

Scottish Public Sector LiDAR Dataset

Tutorials

• LiDAR Tutorial using QGIS by Michal Michalski
  
• LiDAR Tutorial using R by Michal Michalski
  

Tools & Applications

• Scottish Remote Sensing Portal by Scottish Government and Joint Nature Conservation Committee (JNCC)
  

Publications

• Large area archaeological survey in the age of big data and machine learning by Dave Cowley, George Geddes, Łukasz Banaszek, Kirsty Millican and Iris Kramer
  
• Making LiGHT Work of Large Area Survey? Developing Approaches to Rapid Archaeological Mapping and the Creation of Systematic National-scaled Heritage Data by Dave Cowley, Łukasz Banaszek, George Geddes, Angela Gannon, Mike Middleton and Kirsty Millican
  
• New light on medieval settlement in lowland Scotland by Dave Cowley and Piers Dixon
  
• Towards National Archaeological Mapping. Assessing Source Data and Methodology - A Case Study from Scotland by Łukasz Banaszek, Dave Cowley and Mike Middleton
  

nuPlan

Tutorials

• nuPlan Advacned Model Training by Motional
  
  
• nuPlan Framework by Motional
  
  
• nuPlan Planner Tutorial by Motional
  
  
• nuPlan Scenario Visualization by Motional
  
  
• nuPlan Sensor Data Tutorial by Motional
  
  

Tools & Applications

• nuPlan devkit by Motional
  

Publications

• NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles by Holger Caesar, Juraj Kabzan, Kok Seang Tan, Whye Kit Fong, Eric Wolff, Alex Lang, Luke Fletcher, Oscar Beijbom, Sammy Omari
  

New York City Taxi and Limousine Commission (TLC) Trip Record Data

Tutorials

• Build a Real-time Stream Processing Pipeline with Apache Flink on AWS by Steffen Hausmann
  
• Build and run streaming applications with Apache Flink and Amazon Kinesis Data Analytics for Java Applications by Steffen Hausmann
  
• Deep Dive on Flink & Spark on Amazon EMR by Keith Steward
  
• Exploring data with Python and Amazon S3 Select by Manav Sehgal
  
• Machine learning on distributed Dask using Amazon SageMaker and AWS Fargate by Ram Vittal
  
• Optimizing data for analysis with Amazon Athena and AWS Glue by Manav Sehgal
  

Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter Data Set

Tutorials

• Jupyter Notebook to access and visualize global mosaics of the global data set by Josef Kellndorfer
  
• Jupyter Notebook to access and visualize sub regions of the global data set by Josef Kellndorfer
  

Publications

• Generating Global Temporal Coherence Maps from one year of Sentinel-1 C-band data, ESA Fringe 2021 Poster (Youtube) by Oliver Cartus, Josef Kellndorfer, Shadi Oveisgharan, Batu Osmanoglu, Paul Rosen, Urs Wegmüller
  
• Global seasonal Sentinel-1 interferometric coherence and backscatter data set by Josef Kellndorfer, Oliver Cartus, Marco Lavalle, Christophe Magnard, Pietro Milillo, Shadi Oveisgharan, Batu Osmanoglu, Paul A. Rosen, Urs Wegmüller
  
• Webinar: The new era of SAR Time Series Analysis and Visualization: Cloud meets Big SAR Data. IEEE GRSS Bay Area Chapter (Dec. 3rd 2021) by Josef Kellndorfer
  

Normalized Difference Urban Index (NDUI)

Tutorials

• An example of using ndui data with AWS sagemaker tools by Yifang Wang
  Amazon EC2
• Automated extraction of urban built-up areas with NDUI using Python and Google Earth Engine by Yifang Wang
  Amazon EC2

Tools & Applications

• Global DMSP images Correction by Yifang Wang
  

Publications

• A Robust Method to Generate a Consistent Time Series From DMSP/OLS Nighttime Light Data by Qingling Zhang and Bhartendu Pandey and Keren C.Seto
  
• Building a Better Urban Picture:Combining Day and Night Remote Sensing Imagery by Qingling Zhang and Bin Li and David Thau & Rebecca Moore
  

Prefeitura Municipal de São Paulo (PMSP) LiDAR Point Cloud

Tools & Applications

• Entwine by Hobu, Inc.
  
• Fusion by US Department of Agriculture - Forest Service
  
• LAStools by rapidlasso GmbH, GERMANY
  
• PDAL - Point Data Abstraction Library by PDAL Contributors
  

Publications

• Describing the Vertical Structure of Informal Settlements on the Basis of LiDAR Data – A Case Study for Favelas (Slums) in Sao Paulo City by S. C. L. Ribeiro, M. Jarzabek-Rychard, J. P. Cintra, H.-G. Maas
  

Sanborn Maps Data Package

Tutorials

• Fire Insurance Maps at the Library of Congress: A Resource Guide by Julie Stoner, Reference Librarian, Geography and Map Division, Library of Congress
  
• README data cover sheet by Library of Congress
  
• Sanborn Map Data Python Tutorial (Jupyter notebook) by Library of Congress
  

Tools & Applications

• Sanborn Atlas Volume Finder by Julie Stoner and Meagan Snow, Geography and Map Division, Library of Congress
  

Publications

• Introduction to the Collection by Walter W. Ristow
  

CanElevation - LiDAR Point Clouds

Tutorials

• How to generate a digital elevation model (DEM) from a lidar point cloud in COPC LAZ format | Comment générer un modèle numérique d'élévation (MNE) à partir d'un nuage de point lidar en format COPC LAZ by NRCan
  
  
• Identify projects and lidar tiles covering a region of interest | Déterminer les projets et les tuiles lidars couvrant une région d'intérêt by NRCan
  
  
• Using the LiDAR Point Clouds - CanElevation Series product in QGIS | Utilisation du produit Nuages de points lidar - Série CanÉlévation dans QGIS by NRCan
  

Multiview Extended Video with Activities (MEVA)

Publications

• ActEV: Activities in Extended Video by National Institute of Standards and Technology (NIST)
  
• MEVA: A Large-Scale Multiview, Multimodal Video Dataset for Activity Detection by Kellie Corona, Katie Osterdahl, Roderic Collins, Anthony Hoogs
  
• TinyAction Challenge: Recognizing Real-world Low-resolution Activities in Videos by Praveen Tirupattur, Aayush J Rana, Tushar Sangam, Shruti Vyas, Yogesh S Rawat, Mubarak Shah
  

Aurora Multi-Sensor Dataset

Tutorials

• Introduction to Visualizing Sensor Types (Jupyter notebook) by Andrei Bârsan (note: Aurora makes no representations as to the accuracy or functionality of the tutorial)
  Amazon SageMaker Studio Lab

Publications

• "Pit30M: A benchmark for global localization in the age of self-driving cars", in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 4477-4484) by Martinez, J., Doubov, S., Fan, J., Bârsan, I. A., Wang, S., Máttyus, G., Urtasun, R.
  

Ford Multi-AV Seasonal Dataset

Tutorials

• Autonomous Driving Data Service (ADDS) by Ajay Vohra, Amazon
  Amazon EKSAmazon RedshiftAmazon S3Amazon FSx
• Ford AV Dataset Tutorial by Ford Motor Company
  

Nighttime-Fire-Flare

Publications

• NASA SMD AI Workshop Report by SMD Artificial Intelligence Machine Learning (AI/ML) Working Group
  
• Potentially underestimated gas flaring activities—a new approach to detect combustion using machine learning and NASA's Black Marble product suite by Srija Chakraborty, Tomohiro Oda, Virginia Kalb, Zhuosen Wang, Miguel O Román
  

Geosnap Data, Center for Geospatial Sciences

Tools & Applications

• Geosnap User Guide by Eli Knaap