scholarly journals Lateral sediment sources and knickzones as controls on spatio-temporal variations of sediment transport in an Alpine river

Sedimentology ◽  
2013 ◽  
Vol 60 (1) ◽  
pp. 342-357 ◽  
Author(s):  
Toufik Bekaddour ◽  
Fritz Schlunegger ◽  
Mikaël Attal ◽  
Kevin P. Norton
Keyword(s):  
Sediment Transport ◽  
Temporal Variations ◽  
Sediment Sources ◽  
Alpine River ◽  
Spatio Temporal

Monitoring bedload sediment transport in a pre-Alpine river: an experimental method

2017 ◽  
Vol 43 ◽  
pp. 57-63 ◽  
Author(s):  
Monica Papini ◽  
Vladislav Ivov Ivanov ◽  
Davide Brambilla ◽  
Diego Arosio ◽  
Laura Longoni
Keyword(s):  
Sediment Transport ◽  
Experimental Method ◽  
Alpine River ◽  
Bedload Sediment

Spatio-temporal variations of winter wheat water requirement and climatic causes in Huang-Huai-Hai Farming Region

2012 ◽  
Vol 20 (3) ◽  
pp. 356-362 ◽  
Author(s):  
Xiao-Lin YANG ◽  
Zhen-Wei SONG ◽  
Hong WANG ◽  
Quan-Hong SHI ◽  
Fu CHEN ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Temporal Variations ◽  
Water Requirement ◽  
Spatio Temporal

ASSESSMENT OF THE SPATIO-TEMPORAL VARIATIONS IN GROUND WATER STORAGE USING DOWN-SCALED GRACE DATA

2018 ◽  
Author(s):  
Hossein Sahour ◽  
◽  
Mohamed Sultan ◽  
Karem Abdelmohsen ◽  
Sita Karki ◽  
...  
Keyword(s):  
Ground Water ◽  
Water Storage ◽  
Temporal Variations ◽  
Grace Data ◽  
Spatio Temporal

scholarly journals A robust machine learning approach to SDG data segmentation

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Kassim S. Mwitondi ◽  
Isaac Munyakazi ◽  
Barnabas N. Gatsheni
Keyword(s):  
Temporal Variations ◽  
Data Repository ◽  
The Sustainable Development ◽  
Complex Interactions ◽  
Data Segmentation ◽  
Technological Advances ◽  
Machine Learning Approach ◽  
Development Goals ◽  
Data Source ◽  
Spatio Temporal

Abstract In the light of the recent technological advances in computing and data explosion, the complex interactions of the Sustainable Development Goals (SDG) present both a challenge and an opportunity to researchers and decision makers across fields and sectors. The deep and wide socio-economic, cultural and technological variations across the globe entail a unified understanding of the SDG project. The complexity of SDGs interactions and the dynamics through their indicators align naturally to technical and application specifics that require interdisciplinary solutions. We present a consilient approach to expounding triggers of SDG indicators. Illustrated through data segmentation, it is designed to unify our understanding of the complex overlap of the SDGs by utilising data from different sources. The paper treats each SDG as a Big Data source node, with the potential to contribute towards a unified understanding of applications across the SDG spectrum. Data for five SDGs was extracted from the United Nations SDG indicators data repository and used to model spatio-temporal variations in search of robust and consilient scientific solutions. Based on a number of pre-determined assumptions on socio-economic and geo-political variations, the data is subjected to sequential analyses, exploring distributional behaviour, component extraction and clustering. All three methods exhibit pronounced variations across samples, with initial distributional and data segmentation patterns isolating South Africa from the remaining five countries. Data randomness is dealt with via a specially developed algorithm for sampling, measuring and assessing, based on repeated samples of different sizes. Results exhibit consistent variations across samples, based on socio-economic, cultural and geo-political variations entailing a unified understanding, across disciplines and sectors. The findings highlight novel paths towards attaining informative patterns for a unified understanding of the triggers of SDG indicators and open new paths to interdisciplinary research.

Spatio-temporal variations of sea surface halocarbon concentrations and fluxes from southern Yellow Sea

2014 ◽  
Vol 121 (2) ◽  
pp. 369-388 ◽  
Author(s):  
Gui-Peng Yang ◽  
Bin Yang ◽  
Xiao-Lan Lu ◽  
Hai-Bing Ding ◽  
Zhen He
Keyword(s):  
Yellow Sea ◽  
Temporal Variations ◽  
Sea Surface ◽  
Southern Yellow Sea ◽  
Spatio Temporal
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