Climate Engine: Cloud Computing and Visualization of Climate and Remote Sensing Data for Enhanced Natural Resource Monitoring and Process Understanding
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 for local-to-regional climate impacts. However,
these data remain largely inaccessible for a broader segment of potential users given
the computational demands of big data. Climate Engine is a web-based application
that overcomes many barriers that researchers and practitioners face when accessing
these large gridded datasets. Climate Engine uses Google's parallel cloud computing
platform, Google Earth Engine, to enable users to process, visualize, download, and
share various 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 big data using cloud computing.
Secondly, several examples of analyses enabled by Climate Engine are presented to
highlight a range of climate research and applications related to drought, fire, ecology,
and agriculture that can be rapidly generated through a web browser with an internet
connection. The ability to access climate and remote sensing data archives with on demand
parallel cloud computing has created vast opportunities for advanced natural
resource monitoring and process understanding. The Climate Engine application can
be found at ClimateEngine.org, along with URL links to make case study example
results highlighted in this article.
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 for local-to-regional climate impacts. However,
these data remain largely inaccessible for a broader segment of potential users given
the computational demands of big data. Climate Engine is a web-based application
that overcomes many barriers that researchers and practitioners face when accessing
these large gridded datasets. Climate Engine uses Google's parallel cloud computing
platform, Google Earth Engine, to enable users to process, visualize, download, and
share various 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 big data using cloud computing.
Secondly, several examples of analyses enabled by Climate Engine are presented to
highlight a range of climate research and applications related to drought, fire, ecology,
and agriculture that can be rapidly generated through a web browser with an internet
connection. The ability to access climate and remote sensing data archives with on demand
parallel cloud computing has created vast opportunities for advanced natural
resource monitoring and process understanding. The Climate Engine application can
be found at ClimateEngine.org, along with URL links to make case study example
results highlighted in this article.
Research Areas
