Investigative Data Journalism Conference

Investigative Data Journalism Conference

Learn more »

Knowledge Management

Knowledge Management

  • Decision Science
  • Workflow Management
  • Data Mining

Data Analysis

Data Analysis

  • Analytical Tools
  • Machine Learning
  • Visualization

Data Storage

Data Storage

  • Database Systems
  • Distributed Storage
  • Data Warehousing

Financial Management

Financial managmenet strategies

  • Decision Science
  • Workflow Management
  • Data Mining
Home

Economical Analysis

Political, social, and economical topics

  • Anlytical Tools
  • Machine Learning
  • Visualization
Home

Videos

Instructional Videos

  • Database Systems
  • Distributed Storage
  • Data Warehousing
Home

TJG Web Services Reports

TJG Web Services Reports

Big data analysis to support climate change

Dr. Tamaro Green

Big data analysis to support climate change

2020-11-24

Big data analysis may provide tools to support the analysis of meteorological climate data (Matouq et al., 2013).  Matouq et al. (2013) describe artificial neural networks as efficient for analyzing relationships between meteorological parameters and weather data.  Huyer and Partey (2019) suggest that climate smart agriculture can provide benefits for women in diminishing a gender division in labor.

Climate change may require specific research for the areas that are affected such as urban, rural, coastal, and inland.  Cui and Shi (2012) describe urbanization as a precursor to further climate change as urban areas have higher air temperature, longer summers, lower humidity, and lower wind speed than rural areas.  Dirksen, Ronda, Theeuwes, and Pagani (2019) measure the fraction of the visible sky as an indicator for climate change in urban environments.  Makido, Dhakal, and Yamagata (2012) identified correlations between satellite images of urban areas with per capita CO2 emissions.  Ren (2015) describe modifications that urbanization can have on climates such as changes to heat and radioactive properties from building materials, increased air pollution from human activities, and changes to aerodynamic systems from building structures.

 

 

 

Cui, L., & Shi, J. (2012). Urbanization and its environmental effects in Shanghai, China. Urban Climate, 2, 1-15. doi:https://doi.org/10.1016/j.uclim.2012.10.008

Dirksen, M., Ronda, R. J., Theeuwes, N. E., & Pagani, G. A. (2019). Sky view factor calculations and its application in urban heat island studies. Urban Climate, 30, 100498. doi:https://doi.org/10.1016/j.uclim.2019.100498

Huyer, S., & Partey, S. (2019). Weathering the storm or storming the norms? Moving gender equality forward in climate-resilient agriculture. Climatic Change. doi:10.1007/s10584-019-02612-5

Makido, Y., Dhakal, S., & Yamagata, Y. (2012). Relationship between urban form and CO2 emissions: Evidence from fifty Japanese cities. Urban Climate, 2, 55-67. doi:https://doi.org/10.1016/j.uclim.2012.10.006

Matouq, M., El-Hasan, T., Al-Bilbisi, H., Abdelhadi, M., Hindiyeh, M., Eslamian, S., & Duheisat, S. (2013). The climate change implication on Jordan: A case study using GIS and Artificial Neural Networks for weather forecasting. Journal of Taibah University for Science, 7(2), 44-55. doi:https://doi.org/10.1016/j.jtusci.2013.04.001

Ren, G.-Y. (2015). Urbanization as a major driver of urban climate change. Advances in Climate Change Research, 6(1), 1-6. doi:https://doi.org/10.1016/j.accre.2015.08.003



Back to stories

Big Data Platforms

Textual Analysis, Image Analysis, Financial Analysis

Programming Languages

Cross platform and Internet of Things development

Training

Knowledge management systems

Cryptocurrency Capitalization
DJIA

IDJC 2020

International Data Journalism Conference

IDJC 2020

International Data Journalism Conference

IDJC 2020

International Data Journalism Conference