Author
Christopher J. Crosby
Other affiliations: United States Geological Survey, San Diego Supercomputer Center, Arizona State University ...read more
Bio: Christopher J. Crosby is an academic researcher from UNAVCO. The author has contributed to research in topics: Lidar & Cyberinfrastructure. The author has an hindex of 14, co-authored 50 publications receiving 957 citations. Previous affiliations of Christopher J. Crosby include United States Geological Survey & San Diego Supercomputer Center.
Papers published on a yearly basis
Papers
More filters
••
TL;DR: This review identifies key research questions relevant to the Earth-surface processes community within the theme of mass and energy transfer across landscapes and offers guidance on how to identify the most appropriate topographic data type for the analysis of interest.
267 citations
••
TL;DR: A 5-year effort funded by the US National Science Foundation to advance the science and applications of CyberGIS, particularly for enabling the analysis of big spatial data, computationally intensive spatial analysis and modeling (SAM), and collaborative geospatial problem-solving and decision-making, simultaneously conducted by a large number of users is introduced.
Abstract: CyberGIS – defined as cyberinfrastructure-based geographic information systems GIS – has emerged as a new generation of GIS representing an important research direction for both cyberinfrastructure and geographic information science. This study introduces a 5-year effort funded by the US National Science Foundation to advance the science and applications of CyberGIS, particularly for enabling the analysis of big spatial data, computationally intensive spatial analysis and modeling SAM, and collaborative geospatial problem-solving and decision-making, simultaneously conducted by a large number of users. Several fundamental research questions are raised and addressed while a set of CyberGIS challenges and opportunities are identified from scientific perspectives. The study reviews several key CyberGIS software tools that are used to elucidate a vision and roadmap for CyberGIS software research. The roadmap focuses on software integration and synthesis of cyberinfrastructure, GIS, and SAM by defining several key integration dimensions and strategies. CyberGIS, based on this holistic integration roadmap, exhibits the following key characteristics: high-performance and scalable, open and distributed, collaborative, service-oriented, user-centric, and community-driven. As a major result of the roadmap, two key CyberGIS modalities – gateway and toolkit – combined with a community-driven and participatory approach have laid a solid foundation to achieve scientific breakthroughs across many geospatial communities that would be otherwise impossible.
137 citations
••
23 May 2011TL;DR: The use of an SOA, and the co-location of processing and data resources are unique to the field of LIDAR topography data processing, and lays a foundation for providing an open system for hosting and providing access to data and computational tools for these important scientific data.
Abstract: High-resolution topography data acquired with LIDAR (Light Detection and Ranging) remote sensing technology have emerged as a fundamental tool for Earth science research. Because these acquisitions are often undertaken with federal and state funds at significant cost, it is important to maximize the impact of these geospatial data by providing online access to a range of potential users. The National Science Foundation-funded OpenTopography Facility hosted at the San Diego Supercomputer Center (SDSC), has developed a Geospatial Cyberinfrastructure (GCI) to enable online access to Earth science-oriented high-resolution LIDAR topography data, online processing tools, and derivative products. Leveraging high performance computational and data storage resources available at SDSC, OpenTopography provides access to terabytes of point cloud data, standard digital elevation models, and Google Earth image data, all co-located with computational resources for higher-level data processing. This paper describes the motivation, goals, and the technical details of the Services Oriented Architecture (SOA) and underlying cyberinfrastructure platform implemented by OpenTopography. The use of an SOA, and the co-location of processing and data resources are unique to the field of LIDAR topography data processing, and lays a foundation for providing an open system for hosting and providing access to data and computational tools for these important scientific data, and is an exemplar for similar large geospatial data and processing community-oriented cyberinfrastructure systems.
95 citations
••
University of Nevada, Reno1, University of Oregon2, Stockholm University3, University of Colorado Boulder4, University of Minnesota5, University of Maryland, College Park6, Hobart and William Smith Colleges7, UNAVCO8, Boise State University9, University of Houston10, Joint Institute for Nuclear Research11, Woods Hole Oceanographic Institution12, National Center for Atmospheric Research13, University of Saskatchewan14, University of Arizona15, Pennsylvania State University16, University of Texas at Austin17
TL;DR: A review of 147 peer-reviewed lidar studies highlights a lack of lidar applications for critical zone (CZ) studies as 38 % of the studies were focused in geomorphology, 18 % in hydrology, 32 % in ecology, and the remaining 12 % had an interdisciplinary focus.
Abstract: Observation and quantification of the Earth's surface is undergoing a revolutionary change due to the increased spatial resolution and extent afforded by light detection and ranging (lidar) technology. As a consequence, lidar-derived information has led to fundamental discoveries within the individual disciplines of geomorphology, hydrology, and ecology. These disciplines form the cornerstones of critical zone (CZ) science, where researchers study how interactions among the geosphere, hydrosphere, and biosphere shape and maintain the "zone of life", which extends from the top of unweathered bedrock to the top of the vegetation canopy. Fundamental to CZ science is the development of transdisciplinary theories and tools that transcend disciplines and inform other's work, capture new levels of complexity, and create new intellectual outcomes and spaces. Researchers are just beginning to use lidar data sets to answer synergistic, transdisciplinary questions in CZ science, such as how CZ processes co-evolve over long timescales and interact over shorter timescales to create thresholds, shifts in states and fluxes of water, energy, and carbon. The objective of this review is to elucidate the transformative potential of lidar for CZ science to simultaneously allow for quantification of topographic, vegetative, and hydrological processes. A review of 147 peer-reviewed lidar studies highlights a lack of lidar applications for CZ studies as 38 % of the studies were focused in geomorphology, 18 % in hydrology, 32 % in ecology, and the remaining 12 % had an interdisciplinary focus. A handful of exemplar transdisciplinary studies demonstrate lidar data sets that are well-integrated with other observations can lead to fundamental advances in CZ science, such as identification of feedbacks between hydrological and ecological processes over hillslope scales and the synergistic co-evolution of landscape-scale CZ structure due to interactions amongst carbon, energy, and water cycles. We propose that using lidar to its full potential will require numerous advances, including new and more powerful open-source processing tools, exploiting new lidar acquisition technologies, and improved integration with physically based models and complementary in situ and remote-sensing observations. We provide a 5-year vision that advocates for the expanded use of lidar data sets and highlights subsequent potential to advance the state of CZ science.
54 citations
••
TL;DR: For example, the GEON OpenTopography Portal as discussed by the authors provides a collection of light detection and ranging (lidar) topographic data for the study of landforms associated with the plate boundary faults of northern California.
Abstract: Newly acquired light detection and ranging (lidar) topographic data provide a powerful community resource for the study of landforms associated with the plate boundary faults of northern California (Figure 1). In the spring of 2007, GeoEarthScope, a component of the EarthScope Facility construction project funded by the U.S. National Science Foundation, acquired approximately 2000 square kilometers of airborne lidar topographic data along major active fault zones of northern California. These data are now freely available in point cloud (x, y, z coordinate data for every laser return), digital elevation model (DEM), and KMZ (zipped Keyhole Markup Language, for use in Google EarthTM and other similar software) formats through the GEON OpenTopography Portal (http://www.OpenTopography.org/data). Importantly, vegetation can be digitally removed from lidar data, producing high-resolution images (0.5- or 1.0-meter DEMs) of the ground surface beneath forested regions that reveal landforms typically obscured by vegetation canopy (Figure 2).
48 citations
Cited by
More filters
01 Jan 2013
TL;DR: Four rationales for sharing data are examined, drawing examples from the sciences, social sciences, and humanities: to reproduce or to verify research, to make results of publicly funded research available to the public, to enable others to ask new questions of extant data, and to advance the state of research and innovation.
Abstract: We must all accept that science is data and that data are science, and thus provide for, and justify the need for the support of, much-improved data curation. (Hanson, Sugden, & Alberts)
Researchers are producing an unprecedented deluge of data by using new methods and instrumentation. Others may wish to mine these data for new discoveries and innovations. However, research data are not readily available as sharing is common in only a few fields such as astronomy and genomics. Data sharing practices in other fields vary widely. Moreover, research data take many forms, are handled in many ways, using many approaches, and often are difficult to interpret once removed from their initial context. Data sharing is thus a conundrum. Four rationales for sharing data are examined, drawing examples from the sciences, social sciences, and humanities: (1) to reproduce or to verify research, (2) to make results of publicly funded research available to the public, (3) to enable others to ask new questions of extant data, and (4) to advance the state of research and innovation. These rationales differ by the arguments for sharing, by beneficiaries, and by the motivations and incentives of the many stakeholders involved. The challenges are to understand which data might be shared, by whom, with whom, under what conditions, why, and to what effects. Answers will inform data policy and practice. © 2012 Wiley Periodicals, Inc.
634 citations
•
TL;DR: In this article, the Earth system has entered a new geological epoch, spatially explicit global estimates of human populations and their use of land were analysed across the Holocene for their potential to induce irreversible novel transformation of the terrestrial biosphere.
Abstract: Human populations and their use of land have transformed most of the terrestrial biosphere into anthropogenic biomes (anthromes), causing a variety of novel ecological patterns and processes to emerge. To assess whether human populations and their use of land have directly altered the terrestrial biosphere sufficiently to indicate that the Earth system has entered a new geological epoch, spatially explicit global estimates of human populations and their use of land were analysed across the Holocene for their potential to induce irreversible novel transformation of the terrestrial biosphere. Human alteration of the terrestrial biosphere has been significant for more than 8000 years. However, only in the past century has the majority of the terrestrial biosphere been transformed into intensively used anthromes with predominantly novel anthropogenic ecological processes. At present, even were human populations to decline substantially or use of land become far more efficient, the current global extent, duration, type and intensity of human transformation of ecosystems have already irreversibly altered the terrestrial biosphere at levels sufficient to leave an unambiguous geological record differing substantially from that of the Holocene or any prior epoch. It remains to be seen whether the anthropogenic biosphere will be sustained and continue to evolve.
578 citations
•
561 citations
••
19 May 2016TL;DR: In this article, the authors present a review of the state of the art on using Structure-from-Motion (SfM) workflows in geomorphometry and give an overview of terms and fields of application.
Abstract: . Photogrammetry and geosciences have been closely linked since the late 19th century due to the acquisition of high-quality 3-D data sets of the environment, but it has so far been restricted to a limited range of remote sensing specialists because of the considerable cost of metric systems for the acquisition and treatment of airborne imagery. Today, a wide range of commercial and open-source software tools enable the generation of 3-D and 4-D models of complex geomorphological features by geoscientists and other non-experts users. In addition, very recent rapid developments in unmanned aerial vehicle (UAV) technology allow for the flexible generation of high-quality aerial surveying and ortho-photography at a relatively low cost. The increasing computing capabilities during the last decade, together with the development of high-performance digital sensors and the important software innovations developed by computer-based vision and visual perception research fields, have extended the rigorous processing of stereoscopic image data to a 3-D point cloud generation from a series of non-calibrated images. Structure-from-motion (SfM) workflows are based upon algorithms for efficient and automatic orientation of large image sets without further data acquisition information, examples including robust feature detectors like the scale-invariant feature transform for 2-D imagery. Nevertheless, the importance of carrying out well-established fieldwork strategies, using proper camera settings, ground control points and ground truth for understanding the different sources of errors, still needs to be adapted in the common scientific practice. This review intends not only to summarise the current state of the art on using SfM workflows in geomorphometry but also to give an overview of terms and fields of application. Furthermore, this article aims to quantify already achieved accuracies and used scales, using different strategies in order to evaluate possible stagnations of current developments and to identify key future challenges. It is our belief that some lessons learned from former articles, scientific reports and book chapters concerning the identification of common errors or "bad practices" and some other valuable information may help in guiding the future use of SfM photogrammetry in geosciences.
389 citations
••
University of Idaho1, Heidelberg University2, University of Lausanne3, Carnegie Institution for Science4, University of Colorado Boulder5, University of Houston6, University of Zurich7, Cold Regions Research and Engineering Laboratory8, California Institute of Technology9, Vienna University of Technology10, Goddard Space Flight Center11, Bavarian Forest National Park12, University of Würzburg13
TL;DR: In this paper, the authors review recent advances based on repeat lidar collections and analysis of LRI data to highlight novel applications of lidar remote sensing beyond 3D, and outline the potential and current challenges of time and LRI information from lidar sensors to expand the scope of research applications.
235 citations