scholarly journals General Server for Rapid Publishing of OGC-Compliant Earth Science Data Products

2021 ◽  
Author(s):  
Mattheus Ueckermann ◽  
Jerry Bieszczad
Keyword(s):  
Earth Science ◽  
Science Data ◽  
Data Products ◽  
Earth Science Data

scholarly journals Continuity of MODIS and VIIRS Snow Cover Extent Data Products for Development of an Earth Science Data Record

2020 ◽  
Vol 12 (22) ◽  
pp. 3781
Author(s):  
George Riggs ◽  
Dorothy Hall
Keyword(s):  
Snow Cover ◽  
Infrared Imaging ◽  
Earth Science ◽  
Satellite System ◽  
Science Data ◽  
Snow Cover Extent ◽  
Data Record ◽  
Data Products ◽  
Moderate Resolution ◽  
Earth Science Data

An Earth Observing System global snow cover extent data products record at moderate spatial resolution (375–500 m) began in February 2000 with the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra satellite. The record continued with the Aqua MODIS in July 2002, the Suomi-National Polar Platform (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) in January 2012 and continues with the Joint Polar Satellite System-1 (JPSS-1) VIIRS, launched in November of 2017. The objective of this work is to develop a snow cover extent Earth Science Data Record (ESDR) using different satellites, sensors and algorithms. There are many issues to understand when data from different algorithms and sensors are used over a decade-scale time period to create a continuous dataset. Issues may also arise with sensor degradation and even differences in sensor band locations. In this paper we describe development of an ESDR derived from existing MODIS and VIIRS data products and demonstrate continuity among the products. The MODIS and VIIRS snow cover detection algorithms produce very similar daily snow cover maps, with 90–97% agreement in snow cover extent (SCE) in different landscapes. Differences in SCE between products ranged from 2–15% and are attributable to convolved factors of viewing geometry, pixel spread across a scan and time of observation. Compared at a common grid size of 1 km, there is a mean of 95% agreement in SCE and a difference range of 1–10% between the MODIS and VIIRS SCE maps. Mapping sensor observations to a coarser resolution grid reduces the effect of the factors convolved in the 500 m tile to tile comparisons. We conclude that the MODIS and VIIRS SCE data products are reliable constituents of a moderate-resolution ESDR.

Distributed Generation of NASA Earth Science Data Products

2003 ◽  
Vol 1 (2) ◽  
pp. 101-116 ◽  
Author(s):  
Bruce R. Barkstrom ◽  
Thomas H. Hinke ◽  
Shradha Gavali ◽  
Warren Smith ◽  
William J. Seufzer ◽  
...  
Keyword(s):  
Distributed Generation ◽  
Earth Science ◽  
Science Data ◽  
Data Products ◽  
Earth Science Data

scholarly journals Earth Science Data Visualization Through Augmented Coloring Books

2018 ◽  
Author(s):  
Nihanth Cherukuru ◽  
Tim Scheitlin ◽  
Matt Rehme
Keyword(s):  
Data Visualization ◽  
Earth Science ◽  
Science Data ◽  
Earth Science Data

scholarly journals Toward a Collective Agenda on AI for Earth Science Data Analysis

2021 ◽  
Vol 9 (2) ◽  
pp. 88-104
Author(s):  
Devis Tuia ◽  
Ribana Roscher ◽  
Jan Dirk Wegner ◽  
Nathan Jacobs ◽  
Xiaoxiang Zhu ◽  
...  
Keyword(s):  
Data Analysis ◽  
Earth Science ◽  
Science Data ◽  
Earth Science Data

scholarly journals Giovanni: The Bridge Between Data and Science

Eos ◽  
2017 ◽  
Author(s):  
Zhong Liu ◽  
James Acker
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Earth Science ◽  
Remote Sensing Data ◽  
Data Sets ◽  
Science Data ◽  
Web Based ◽  
Sensing Data ◽  
Daunting Task ◽  
Earth Science Data

Using satellite remote sensing data sets can be a daunting task. Giovanni, a Web-based tool, facilitates access, visualization, and exploration for many of NASA’s Earth science data sets.

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