@inbook {3302,
	title = {Chapter 11 - Zero to a trillion: Advancing Earth surface process studies with open access to high-resolution topography},
	booktitle = {Remote Sensing of Geomorphology},
	series = {Developments in Earth Surface Processes},
	volume = {23},
	year = {2020},
	pages = {317 - 338},
	publisher = {Elsevier},
	organization = {Elsevier},
	abstract = {High-resolution topography (HRT) is a powerful observational tool for studying the Earth{\textquoteright}s surface, vegetation, and urban landscapes, with broad scientific, engineering, and education-based applications. Submeter resolution imaging is possible when collected with laser and photogrammetric techniques using the ground, air, and space-based platforms. Open access to these data and a cyberinfrastructure platform that enables users to discover, manage, share, and process then increases the impact of investments in data collection and catalyzes scientific discovery. Furthermore, open and online access to data enables broad interdisciplinary use of HRT across academia and in communities such as education, public agencies, and the commercial sector. OpenTopography, supported by the US National Science Foundation, aims to democratize access to Earth science-oriented, HRT data and processing tools. We utilize cyberinfrastructure, including large-scale data management, high-performance computing, and service-oriented architectures to provide efficient web-based visualization and access to large, HRT datasets. OT colocates data with processing tools to enable users to quickly access custom data and derived products for their application, with the ultimate goal of making these powerful data easier to use. OT{\textquoteright}s rapidly growing data holdings currently include 283 lidar and photogrammetric, point cloud datasets (>1.2 trillion points) covering 236,364km2. As a testament to OT{\textquoteright}s success, more than 86,000 users have processed over 5 trillion lidar points. This use has resulted in more than 290 peer-reviewed publications across numerous academic domains including Earth science, geography, computer science, and ecology.},
	keywords = {cyberinfrastructure, Geoinformatics, Geomorphology, Surface processes, topography},
	issn = {0928-2025},
	doi = {https://doi.org/10.1016/B978-0-444-64177-9.00011-4},
	url = {http://www.sciencedirect.com/science/article/pii/B9780444641779000114},
	author = {Christopher J. Crosby and J. Ram{\'o}n Arrowsmith and Viswanath Nandigam},
	editor = {Paolo Tarolli and Simon M. Mudd}
}
@article {3399,
	title = {Measuring success for a future vision: Defining impact in science gateways/virtual research environments},
	journal = {Concurrency and Computation: Practice and Experience},
	volume = {n/a},
	year = {2020},
	abstract = {Summary Scholars worldwide leverage science gateways/virtual research environments (VREs) for a wide variety of research and education endeavors spanning diverse scientific fields. Evaluating the value of a given science gateway/VRE to its constituent community is critical in obtaining the financial and human resources necessary to sustain operations and increase adoption in the user community. In this article, we feature a variety of exemplar science gateways/VREs and detail how they define impact in terms of, for example, their purpose, operation principles, and size of user base. Further, the exemplars recognize that their science gateways/VREs will continuously evolve with technological advancements and standards in cloud computing platforms, web service architectures, data management tools and cybersecurity. Correspondingly, we present a number of technology advances that could be incorporated in next-generation science gateways/VREs to enhance their scope and scale of their operations for greater success/impact. The exemplars are selected from owners of science gateways in the Science Gateways Community Institute (SGCI) clientele in the United States, and from the owners of VREs in the International Virtual Research Environment Interest Group (VRE-IG) of the Research Data Alliance. Thus, community-driven best practices and technology advances are compiled from diverse expert groups with an international perspective to envisage futuristic science gateway/VRE innovations.},
	keywords = {futuristic vision, measuring impact, science gateways, success metrics, virtual research environments},
	doi = {https://doi.org/10.1002/cpe.6099},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.6099},
	author = {Calyam, Prasad and Wilkins-Diehr, Nancy and Miller, Mark and Brookes, Emre H. and Arora, Ritu and Chourasia, Amit and Jennewein, Douglas M. and Nandigam, Viswanath and Drew LaMar, M. and Cleveland, Sean B. and Newman, Greg and Wang, Shaowen and Zaslavsky, Ilya and Cianfrocco, Michael A. and Ellett, Kevin and Tarboton, David and Jeffery, Keith G. and Zhao, Zhiming and Gonz{\'a}lez-Aranda, Juan and Perri, Mark J. and Tucker, Greg and Candela, Leonardo and Kiss, Tamas and Gesing, Sandra}
}
@article {3354,
	title = {Emergent Challenges for Science sUAS Data Management: Fairness through Community Engagement and Best Practices Development},
	journal = {Remote Sensing},
	volume = {11},
	year = {2019},
	month = {jul},
	pages = {1797},
	doi = {10.3390/rs11151797},
	url = {https://doi.org/10.3390\%2Frs11151797},
	author = {Jane Wyngaard and Lindsay Barbieri and Andrea Thomer and Josip Adams and Don Sullivan and Christopher Crosby and Cynthia Parr and Jens Klump and Sudhir Raj Shrestha and Tom Bell}
}
@article {3262,
	title = {Analyzing high resolution topography for advancing the understanding of mass and energy transfer through landscapes: A review},
	journal = {Earth-Science Reviews},
	volume = {148},
	year = {2015},
	pages = {174 - 193},
	keywords = {Bathymetry, Change detection, Filtering, Geomorphic features, IfSAR, InSAR, LIDAR, Point cloud, Structure from Motion},
	issn = {0012-8252},
	doi = {https://doi.org/10.1016/j.earscirev.2015.05.012},
	url = {http://www.sciencedirect.com/science/article/pii/S0012825215300015},
	author = {Paola Passalacqua and Patrick Belmont and Dennis M. Staley and Jeffrey D. Simley and J Ram{\'o}n Arrowsmith and Collin A. Bode and Christopher Crosby and Stephen B. DeLong and Nancy F. Glenn and Sara A. Kelly and Dimitri Lague and Harish Sangireddy and Keelin Schaffrath and David G. Tarboton and Thad Wasklewicz and Joseph M. Wheaton}
}
@proceedings {3087,
	title = {Leveraging XSEDE HPC resources to address computational challenges with high-resolution topography data},
	year = {2014},
	address = {Atlanta, GA},
	url = {http://dl.acm.org/citation.cfm?doid=2616498.2616564},
	author = {Choonhan Youn and Viswanath Nandigam and Minh Phan and David Tarboton and Nancy Wilkins-Diehr and Chaitan Baru and Christopher J Crosby and Anand Padmanabhan and Shaowen Wang}
}
