scholarly journals Integrating multiple data sources in species distribution modeling: a framework for data fusion*

Ecology ◽  
2017 ◽  
Vol 98 (3) ◽  
pp. 840-850 ◽  
Author(s):  
Krishna Pacifici ◽  
Brian J. Reich ◽  
David A. W. Miller ◽  
Beth Gardner ◽  
Glenn Stauffer ◽  
...  
Keyword(s):  
Data Fusion ◽  
Species Distribution ◽  
Species Distribution Modeling ◽  
Data Sources ◽  
Multiple Data Sources ◽  
Distribution Modeling ◽  
Multiple Data

scholarly journals Assessment of Data Fusion Oriented on Data Mining Approaches to Enhance Precision Agriculture Practices aimed at Increase of Durum Wheat (Triticum turgidum L. var. durum) Yield.

2018 ◽  
Vol 1 (1) ◽  
pp. 47
Author(s):  
A. D’Accolti ◽  
S. Maggio ◽  
A. Massaro ◽  
A.M. Galiano ◽  
V. Birardi ◽  
...  
Keyword(s):  
Data Mining ◽  
Data Fusion ◽  
Durum Wheat ◽  
Precision Agriculture ◽  
Triticum Turgidum ◽  
Data Sources ◽  
Software Systems ◽  
World Population ◽  
Multiple Data Sources ◽  
Multiple Data

In 2050, world population will reach a total of 9 billion inhabitants and their food demand have to be satisfied. Durum wheat (Triticum turgidum L. var. durum) is one of the most important food crop and its consumption is increasing worldwide. Productivity growth in agriculture and profitable returns are strongly influenced by investment in research and development, where Precision Agriculture (PA) represents an innovative way to manage farms by introducing the Information and Communication Technology (ICT) into the production process. It is known that farms activities produce large amounts of data. Today ICT allows, with electronic and software systems, to collect and transfer automatically these data, thus increasing yields and profits. In this direction significant data are processed from agricultural production, and retrieved to extract useful information important to increase the knowledge base. Data from multiple data sources can be processed by a Data Fusion (DF) approach able to combine multiple data sources into an unique database system. Raw data are transformed into useful information, thus DF improves pattern recognition, analysis of growth factors, and relationship between crops and environments. Data Fusion is synonym of Data Integration, Sensor Fusion, and Image Fusion. By means of Data Mining (DM) it is possible to extract useful information from data of the production processes thus providing new outputs concerning product quality and product “health status”. The following literature take into account the DF and DM techniques applied to Precision Agriculture (PA) and to cultivation inputs (water, nitrogen, etc.) management.  We report also last advances of DF and DM in modern agriculture and in precision durum wheat production.

Using species distribution modeling to improve conservation of medicinal plants in Southwest China

Planta Medica ◽  
2016 ◽  
Vol 81 (S 01) ◽  
pp. S1-S381
Author(s):  
B Liu ◽  
F Li ◽  
Z Guo ◽  
L Hong ◽  
W Huang ◽  
...  
Keyword(s):  
Medicinal Plants ◽  
Species Distribution ◽  
Southwest China ◽  
Species Distribution Modeling ◽  
Distribution Modeling

scholarly journals Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting

2020 ◽  
Author(s):  
Lijing Wang ◽  
Aniruddha Adiga ◽  
Srinivasan Venkatramanan ◽  
Jiangzhuo Chen ◽  
Bryan Lewis ◽  
...  
Keyword(s):  
Deep Learning ◽  
Data Sources ◽  
Learning Models ◽  
Multiple Data Sources ◽  
Multiple Data
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