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COPERNICUS BIG DATA AND GOOGLE EARTH ENGINE FOR GLACIER SURFACE VELOCITY FIELD MONITORING: FEASIBILITY DEMONSTRATION ON SAN RAFAEL AND SAN QUINTIN GLACIERS

M. Di Tullio, F. Nocchi, A. Camplani, N. Emanuelli, A. Nascetti, M. Crespi
2018 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The leading idea of this work is to continuously retrieve glaciers surface velocity using free ESA Sentinel-1 SAR imagery and exploiting the potentialities of the Google Earth Engine (GEE) platform.  ...  GEE has been recently released by Google as a platform for petabyte-scale scientific analysis and visualization of geospatial datasets.  ...  This step is quite critical for the huge dataset size, depending upon the GEE API for geographical filtering used to manage the GEE database.  ... 
doi:10.5194/isprs-archives-xlii-3-289-2018 fatcat:jbt3vzygxff3nahdjh3a52xfvi

A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform

Pardhasaradhi Teluguntla, Prasad S Thenkabail, Adam Oliphant, Jun Xiong, Murali Krishna Gumma, Russell G. Congalton, Kamini Yadav, Alfredo Huete
2018 ISPRS journal of photogrammetry and remote sensing (Print)  
Reference training and validation data were gathered from: (a) field visits, (b) sub-meter to 5-m very high spatial resolution imagery (VHRI) data, and (c) ancillary sources such as from the National agriculture  ...  The cropland extent product further demonstrated the ability to estimate sub-national cropland areas accurately by providing an R 2 value of 0.85 when compared with province-wise cropland areas of China  ...  Acknowledgements Authors are grateful for the funding received through NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs), through NASA ROSES solicitation (June 1, 2013-May  ... 
doi:10.1016/j.isprsjprs.2018.07.017 fatcat:y35mxpopxngexhmap2vph3phfy

Seamless Synthetic Aperture Radar Archive for Interferometry Analysis

S. Baker, C. Baru, G. Bryson, B. Buechler, C. Crosby, E. Fielding, C. Meertens, J. Nicoll, C. Youn
2014 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The NASA Advancing Collaborative Connections for Earth System Science (ACCESS) seamless synthetic aperture radar (SAR) archive (SSARA) project is a collaboration between UNAVCO, the Alaska Satellite Facility  ...  SAR (InSAR) data products.  ...  InSAR Product, SSARA software, testing, and documentation contributions provided by Rudi Gens b , Tim Stern b , Kirk Hogenson b , and Greg Moore c .  ... 
doi:10.5194/isprsarchives-xl-1-65-2014 fatcat:shmyxkr5ujayjhshcuwn2qvshy

Knowledge Extracted from Copernicus Satellite Data

Dumitru Octavian, Schwarz Gottfried, Eltoft Torbjørn, Kræmer Thomas, Wagner Penelope, Hughes Nick, Arthus David, Fleming Andrew, Koubarakis Manolis, Datcu Mihai
2019 Zenodo  
During the development of deep learning algorithms, a key activity is to establish a large amount of referenced Earth Observation data.  ...  This approach is also a simple way to generate benchmarking datasets that can be used for testing and validating different algorithms, and for creating additional bigger datasets for large-scale demonstrations  ...  This research shows that cartographic science with the latest modern technologies and appropriate visualization will find its place in the large aspects of tasks of Digital Earth, early warning and disaster  ... 
doi:10.5281/zenodo.3941573 fatcat:zzifwgljifck5bpjnboetsftfu

On the Use of Standardized Multi-Temporal Indices for Monitoring Disturbance and Ecosystem Moisture Stress across Multiple Earth Observation Systems in the Google Earth Engine

Tyson L. Swetnam, Stephen R. Yool, Samapriya Roy, Donald A. Falk
2021 Remote Sensing  
In this work we explore three methods for quantifying ecosystem vegetation responses spatially and temporally using Google's Earth Engine, implementing an Ecosystem Moisture Stress Index (EMSI) to monitor  ...  Our results provide an expanded basis for detection and monitoring: (i) ecosystem phenology and health; (ii) wildfire potential or burn severity; (iii) herbivory; (iv) changes in ecosystem resilience;  ...  Acknowledgments: Foundational work was supported by the NASA Earth Sciences Application Center grant between The University of Arizona and University of California at Berkeley.  ... 
doi:10.3390/rs13081448 fatcat:epy7btojkbegne2w6pywcynua4

Performance evaluation of GEDI and ICESat-2 laser altimeter data for terrain and canopy height retrievals

Aobo Liu, Xiao Cheng, Zhuoqi Chen
2021 Remote Sensing of Environment  
Because the time interval between the spaceborne products and validation data may introduce additional errors, we validate the newly released GEDI L2A product (version 2) and the ICESat-2 ATL08 product  ...  (version 4) using high-resolution, locally calibrated airborne lidar products acquired in the same year (2019) as the reference datasets.  ...  The authors want to acknowledge the NASA for providing ICESat-2 and GEDI data, NEON for providing airborne lidar data, NOAA for providing VDatum software.  ... 
doi:10.1016/j.rse.2021.112571 fatcat:ucp3cdd6fbbordxeo7ixfuhw4m

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
2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
In this regard, Google has developed a cloud computing platform, called Google Earth Engine (GEE), to effectively address the challenges of big data analysis.  ...  Although this platform was launched in 2010 and has proved its high potential for different applications, it has not been fully investigated and utilized for RS applications until recent years.  ...  variety of disciplines in all branches of Earth science studies.  ... 
doi:10.1109/jstars.2020.3021052 fatcat:pudllv5h2ve4lfvqtx3p4qikju

Comparison of Thermal Infrared-Derived Maps of Irrigated and Non-Irrigated Vegetation in Urban and Non-Urban Areas of Southern California

Red Willow Coleman, Natasha Stavros, Glynn Hulley, Nicholas Parazoo
2020 Remote Sensing  
The July 2018 launch of the ECOsystem Spaceborne Thermal Radiometer on Space Station (ECOSTRESS) offers an opportunity to test this hypothesis using retrieved land surface temperature (LST) data in complex  ...  Mapping irrigated vegetation in Los Angeles is necessary for developing sustainable water use practices and accurately accounting for the megacity's carbon exchange and water balance changes.  ...  Support from the Earth Science Division OCO-2 program is acknowledged. Copyright 2020. All rights reserved. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs12244102 fatcat:ifwverm55fgaxb6shbtevghwsu

Guidelines on EO ICT support improvement to stakeholders v2

Gerhard Triebnig
2020 Zenodo  
This document integrates the lessons learned and provide implementation scenario guidelines for services in the agriculture domain on how to utilize the DIAS service infrastructure to achieve advancement  ...  With the introduction in 2010 of the Google Earth Engine 6 which for the first time offered a planetary-scale platform for Earth science data and analysis, also fast, online accessible storage for these  ...  The individual DIAS have all some sort of catalogue API for exploring their product offers, file access APIs, and dashboard functionality for storage and processing resource allocation and monitoring.  ... 
doi:10.5281/zenodo.4249914 fatcat:4ju6nl6apvdpla6bx7iy46et5q

The Land surface Data Toolkit (LDTv7.2) – a data fusion environment for land data assimilation systems

Kristi R. Arsenault, Sujay V. Kumar, James V. Geiger, Shugong Wang, Eric Kemp, David M. Mocko, Hiroko Kato Beaudoing, Augusto Getirana, Mahdi Navari, Bailing Li, Jossy Jacob, Jerry Wegiel (+1 others)
2018 Geoscientific Model Development Discussions  
The machine learning layer in LDT facilitates the use of modern data science algorithms for developing data-driven predictive models.  ...  Through the use of an object-oriented framework design, LDT provides extensible features for the continued development of support for different types of observational data sets and data analytics algorithms  ...  The data-rich Earth science arena is an ideal environment for deploying such data 30 science enhancements and the ML layers in LDT will be continually updated to exploit such capabilities. Geosci.  ... 
doi:10.5194/gmd-2018-63 fatcat:gyiu2pzl3fab5htyldfgokr5rq

Demonstration of a Space Capable Miniature Dual Frequency GNSS Receiver

E. Glenn Lightsey, Todd E. Humphreys, Jahshan A. Bhatti, Andrew J. Joplin, Brady W. O'Hanlon, Steven P. Powell
2014 Navigation  
In preparation for upcoming space flights, FOTON was also designed for operation in low Earth orbit.  ...  The receiver, known as the Fast, Orbital, TEC, Observables, and Navigation (FOTON) receiver, is intended for use in space applications.  ...  ACKNOWLEDGMENTS The authors wish to thank Ummon Karpe for useful discussions and preliminary analysis of the FOTON data.  ... 
doi:10.1002/navi.52 fatcat:nyedmbfoyvegbpgiuetasxqaei

Optical Remote Sensing [chapter]

Man Sing Wong, Xiaolin Zhu, Sawaid Abbas, Coco Yin Tung Kwok, Meilian Wang
2021 The Urban Book Series  
AbstractApplications of Earth-observational remote sensing are rapidly increasing over urban areas.  ...  This chapter briefly describes the history of optical remote sensing, the basic operation of satellite image processing, advanced methods of object extraction for modern urban designs, various applications  ...  The information in a satellite image can be extracted and classified at various processing units of the image; for example, pixel level, a unit defined by the image spatial resolution; sub-pixel level,  ... 
doi:10.1007/978-981-15-8983-6_20 fatcat:zpfeem553vhulm6dx5ncddl64y

The potential for remote sensing and hydrologic modelling to assess the spatio-temporal dynamics of ponds in the Ferlo Region (Senegal)

V. Soti, C. Puech, D. Lo Seen, A. Bertran, C. Vignolles, B. Mondet, N. Dessay, A. Tran
2010 Hydrology and Earth System Sciences  
optical satellite images to access pond location and surface area at given dates, 2) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model (DEM) data to estimate  ...  Calibration was performed from daily field data (rainfall, water level) collected during the 2001 and 2002 rainy seasons and from three different sources of remote sensing data: 1) very high spatial resolution  ...  Earth, 34, 309-315, 2009.  ... 
doi:10.5194/hess-14-1449-2010 fatcat:ttg4y46kdngbvljjchs5lruda4

The Future of Earth Observation in Hydrology

Matthew F. McCabe, Matthew Rodell, Douglas E. Alsdorf, Diego G. Miralles, Remko Uijlenhoet, Wolfgang Wagner, Arko Lucieer, Rasmus Houborg, Niko E. C. Verhoest, Trenton E. Franz, Jiancheng Shi, Huilin Gao (+1 others)
2017 Hydrology and Earth System Sciences Discussions  
Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-meter resolution, pushing back on spatiotemporal constraints  ...  sensing of the Earth on a daily basis.  ...  , astrophysics, and Earth science).  ... 
doi:10.5194/hess-2017-54 fatcat:c7wtq6ytjnfzhppbcetvzz7dk4

Guidelines on EO ICT support improvement to stakeholders v1

Gerhard Triebnig
2019 Zenodo  
This document integrates the lessons learned and provide implementation scenario guidelines for services in the agriculture domain on how to utilize the DIAS service infrastructure to achieve advancement  ...  With the introduction in 2010 of the Google Earth Engine 6 which for the first time offered a planetary-scale platform for Earth science data and analysis, also fast, online accessible storage for these  ...  for product discovery via OpenSearch API-© Mundi ___________________ 39 Figure 19 Product items for download (list is truncated) ____________________________________________ 39 Figure 20 Original product  ... 
doi:10.5281/zenodo.4248940 fatcat:bxbei6rq6vbwbj6fa6og4kweci
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