Advances in Remote Sensing for Natural Resource Monitoring

2021 ◽  
Keyword(s):  
Remote Sensing ◽  
Natural Resource ◽  
Resource Monitoring ◽  
Natural Resource Monitoring

Climate Engine: Cloud Computing and Visualization of Climate and Remote Sensing Data for Advanced Natural Resource Monitoring and Process Understanding

2017 ◽  
Vol 98 (11) ◽  
pp. 2397-2410 ◽  
Author(s):  
Justin L. Huntington ◽  
Katherine C. Hegewisch ◽  
Britta Daudert ◽  
Charles G. Morton ◽  
John T. Abatzoglou ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Cloud Computing ◽  
Big Data ◽  
Natural Resource ◽  
Remote Sensing Data ◽  
Google Earth ◽  
Resource Monitoring ◽  
Sensing Data ◽  
Process Understanding ◽  
Natural Resource Monitoring

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 big data using cloud computing. Second, several examples are presented to highlight a range of climate research and applications related to drought, fire, ecology, and agriculture that can be rapidly generated using Climate Engine. 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.

scholarly journals The Event Book System: A Community-based Natural Resource Monitoring System from Namibia

2005 ◽  
Vol 14 (11) ◽  
pp. 2611-2631 ◽  
Author(s):  
Greg Stuart-Hill ◽  
Richard Diggle ◽  
Bevan Munali ◽  
Jo Tagg ◽  
David Ward
Keyword(s):  
Monitoring System ◽  
Natural Resource ◽  
Resource Monitoring ◽  
Community Based ◽  
System A ◽  
Natural Resource Monitoring

scholarly journals Unmanned Aircraft Systems (UASs) for Ecological Research and Natural-Resource Monitoring (Florida)

2008 ◽  
Vol 26 (1) ◽  
pp. 13-14 ◽  
Author(s):  
A. C. Watts ◽  
W. S. Bowman ◽  
A. H. Abd-Elrahman ◽  
A. Mohamed ◽  
B. E. Wilkinson ◽  
...  
Keyword(s):  
Natural Resource ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Ecological Research ◽  
Resource Monitoring ◽  
Aircraft Systems ◽  
Natural Resource Monitoring

Local Participation in Natural Resource Monitoring: a Characterization of Approaches

2009 ◽  
Vol 23 (1) ◽  
pp. 31-42 ◽  
Author(s):  
FINN DANIELSEN ◽  
NEIL D. BURGESS ◽  
ANDREW BALMFORD ◽  
PAUL F. DONALD ◽  
MIKKEL FUNDER ◽  
...  
Keyword(s):  
Natural Resource ◽  
Resource Monitoring ◽  
Local Participation ◽  
Natural Resource Monitoring

scholarly journals UTILISATION OF HYBRID POLARIMETRIC SAR DATA FOR NATURAL RESOURCE MONITORING – A NEW DIMENSION

2018 ◽  
Vol 37 (2) ◽  
pp. 355
Author(s):  
P. V. Jayasri ◽  
Manoj Joseph ◽  
H.S.V. Usha Sundari Ryali ◽  
E.V.S. Sita Kumari ◽  
A.V.V. Prasad
Keyword(s):  
Natural Resource ◽  
Resource Monitoring ◽  
Polarimetric Sar ◽  
Natural Resource Monitoring ◽  
Sar Data
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