Journal ArticleDOI
Climate Engine: Cloud Computing and Visualization of Climate and Remote Sensing Data for Advanced Natural Resource Monitoring and Process Understanding
Justin L. Huntington,Katherine C. Hegewisch,B. Daudert,C. Morton,John T. Abatzoglou,Daniel J. McEvoy,Tyler A. Erickson +6 more
TLDR
Climate Engine is a web-based application that overcomes many computational barriers that users face by employing Google’s parallel cloud-computing platform, Google Earth Engine, to process, visualize, download, and share climate and remote sensing datasets in real time.Abstract:
The paucity of long-term observations, particularly in regions with heterogeneous climate and land cover, can hinder incorporating climate data at appropriate spatial scales for decision-making and scientific research. Numerous gridded climate, weather, and remote sensing products have been developed to address the needs of both land managers and scientists, in turn enhancing scientific knowledge and strengthening early-warning systems. However, these data remain largely inaccessible for a broader segment of users given the computational demands of big data. Climate Engine (http://ClimateEngine.org) is a web-based application that overcomes many computational barriers that users face by employing Google’s parallel cloud-computing platform, Google Earth Engine, to process, visualize, download, and share climate and remote sensing datasets in real time. The software application development and design of Climate Engine is briefly outlined to illustrate the potential for high-performance processing of...read more
Citations
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Journal ArticleDOI
Current status of Landsat program, science, and applications
Michael A. Wulder,Thomas R. Loveland,David P. Roy,Christopher J. Crawford,Jeffrey G. Masek,Curtis E. Woodcock,Richard G. Allen,Martha C. Anderson,Alan Belward,Warren B. Cohen,John L. Dwyer,Angela Erb,Feng Gao,Patrick Griffiths,Dennis L. Helder,Txomin Hermosilla,Txomin Hermosilla,James D. Hipple,Patrick Hostert,M. Joseph Hughes,Justin L. Huntington,David M. Johnson,Robert E. Kennedy,Ayse Kilic,Zhan Li,Leo Lymburner,Joel McCorkel,Nima Pahlevan,Ted Scambos,Crystal B. Schaaf,John R. Schott,Yongwei Sheng,James C. Storey,Eric Vermote,James E. Vogelmann,Joanne C. White,Randolph H. Wynne,Zhe Zhu,Zhe Zhu +38 more
TL;DR: The programmatic developments and institutional context for the Landsat program and the unique ability of Landsat to meet the needs of national and international programs are described and the key trends in Landsat science are presented.
Journal ArticleDOI
Google Earth Engine Applications Since Inception: Usage, Trends, and Potential
Lalit Kumar,Onisimo Mutanga +1 more
TL;DR: Analysis of published literature showed that a total of 300 journal papers were published between 2011 and June 2017 that used GEE in their research, spread across 158 journals; Landsat was the most widely used dataset; it is the biggest component of the GEE data portal.
Journal ArticleDOI
Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review
Meisam Amani,Arsalan Ghorbanian,Seyed Ali Ahmadi,Mohammad Kakooei,Armin Moghimi,S. Mohammad Mirmazloumi,Sayyed Hamed Alizadeh Moghaddam,Sahel Mahdavi,Masoud Ghahremanloo,Saeid Parsian,Qiusheng Wu,Brian Brisco +11 more
TL;DR: This study aims to comprehensively explore different aspects of the GEE platform, including its datasets, functions, advantages/limitations, and various applications, and observed that Landsat and Sentinel datasets were extensively utilized by GEE users.
Journal ArticleDOI
Satellite Remote Sensing for Water Resources Management: Potential for Supporting Sustainable Development in Data-Poor Regions
Justin Sheffield,Eric F. Wood,Ming Pan,Hylke E. Beck,Gabriele Coccia,Aleix Serrat-Capdevila,Koen Verbist +6 more
TL;DR: In this article, the authors review data needs for water resources management (WRM) and the role that satellite remote sensing can play to fill gaps and enhance water resources, focusing on the Latin American and Caribbean.
Journal ArticleDOI
Google Earth Engine, Open-Access Satellite Data, and Machine Learning in Support of Large-Area Probabilistic Wetland Mapping
TL;DR: This work developed a workflow for predicting the probability of wetland occurrence using a boosted regression tree machine-learning framework applied to digital topographic and EO data, and demonstrates the central role of high-quality topographic variables for modeling wetland distribution at regional scales.
References
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Journal ArticleDOI
High-Resolution Global Maps of 21st-Century Forest Cover Change
Matthew C. Hansen,Peter Potapov,Rebecca Moore,M. Hancher,Svetlana Turubanova,Alexandra Tyukavina,David Thau,Stephen V. Stehman,Scott J. Goetz,Thomas R. Loveland,Anil Kommareddy,A. Egorov,Louise Chini,Christopher O. Justice,John R. Townshend +14 more
TL;DR: Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally, and boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms.
Journal ArticleDOI
Google Earth Engine: Planetary-scale geospatial analysis for everyone
TL;DR: Google Earth Engine is a cloud-based platform for planetary-scale geospatial analysis that brings Google's massive computational capabilities to bear on a variety of high-impact societal issues including deforestation, drought, disaster, disease, food security, water management, climate monitoring and environmental protection.
Journal ArticleDOI
The NCEP Climate Forecast System Reanalysis
Suranjana Saha,Shrinivas Moorthi,Hua-Lu Pan,Xingren Wu,Jiande Wang,Sudhir Nadiga,Patrick Tripp,Robert Kistler,John S. Woollen,David Behringer,Haixia Liu,Diane Stokes,Robert Grumbine,George Gayno,Jun Wang,Yu-Tai Hou,Hui-ya Chuang,Hann-Ming Henry Juang,Joe Sela,Mark Iredell,Russ Treadon,Daryl T. Kleist,Paul van Delst,Dennis Keyser,John Derber,Michael Ek,Jesse Meng,Helin Wei,Rongqian Yang,Stephen J. Lord,Huug van den Dool,Arun Kumar,Wanqiu Wang,Craig S. Long,Muthuvel Chelliah,Yan Xue,Boyin Huang,Jae-Kyung E. Schemm,Wesley Ebisuzaki,Roger Lin,Pingping Xie,Mingyue Chen,Shuntai Zhou,Wayne Higgins,Cheng-Zhi Zou,Quanhua Liu,Yong Chen,Yong Han,Lidia Cucurull,Richard W. Reynolds,Glenn Rutledge,Mitch Goldberg +51 more
TL;DR: The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010 as mentioned in this paper, which was designed and executed as a global, high-resolution coupled atmosphere-ocean-land surface-sea ice system to provide the best estimate of the state of these coupled domains over this period.
Journal ArticleDOI
Cloud computing: state-of-the-art and research challenges
Qi Zhang,Lu Cheng,Raouf Boutaba +2 more
TL;DR: A survey of cloud computing is presented, highlighting its key concepts, architectural principles, state-of-the-art implementation as well as research challenges to provide a better understanding of the design challenges of cloud Computing and identify important research directions in this increasingly important area.
Journal ArticleDOI
The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes.
Chris Funk,Pete Peterson,Martin Landsfeld,Diego Pedreros,James P. Verdin,Shraddhanand Shukla,Gregory Husak,James Rowland,Laura Harrison,Andrew Hoell,Joel Michaelsen +10 more
TL;DR: The Variable Infiltration Capacity model, a novel blending procedure incorporating the spatial correlation structure of CCD-estimates to assign interpolation weights, is presented and it is shown that CHIRPS can support effective hydrologic forecasts and trend analyses in southeastern Ethiopia.