Difference between revisions of "Group13 Proposal"

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<font size = 6; color="#FFFFFF"><span style="font-family:Century Gothic;">ISSS608 Visual Analytics and Applications</span></font>
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<font size = 4; color="#FFFFFF"><span style="font-family:Century Gothic;">Group 13 : Proposal</span></font>
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<font size = 5; color="#FFFFFF"><span style="font-family:Century Gothic;">An Analysis of Changing Rainfall Patterns Across India Through Visualizations
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<font size = 5; color="#FFFFFF"><span style="font-family:Century Gothic;">Economic Growth And Climate Change
  
 
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[[Group04_Overview| <font color="#FFFFFF">Overview</font>]] 
 
 
 
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<font size = 5><span style="font-family:Century Gothic;">Introduction</span></font>  
 
<font size = 5><span style="font-family:Century Gothic;">Introduction</span></font>  
 
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The Organization for Economic Co-operation and Development is an intergovernmental economic organization with 37 member countries, founded in 1961 to stimulate economic progress and world trade. Most OECD members are high-income economies with a very high Human Development Index (HDI) and are regarded as developed countries. As of 2017, the OECD member states collectively comprised 62.2% of global nominal GDP (US$49.6 trillion) and 42.8% of global GDP ($54.2 trillion) at purchasing power parity.
  
With growing fluctuations in climate in recent years, one occupation that has been affected the most is <b><i>Agriculture</i></b>. This has turned into a global concern and particularly in India where these climate changes have contributed significantly in the growing rate of farmers taking their lives.
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[[Image:OECD.jpg|centre|350px]]
  
In this study, we intend to analyse India’s rainfall patters for past few years using Exploratory techniques. Over 80% of the annual rainfall is received in the four rainy months of June to September. There is great regional and temporal variation in the distribution of rainfall and although the monsoons affect most parts of India, the amount of rainfall varies from heavy to scanty on different parts.  
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But has this economic progress come at a cost? During this period, the reported green house gas (GHG) emissions has shown a rising trend. For instance, there was a large decrease in GHG emissions in 2009 due to economic recession, further enforcing our fears that human activities could have drastic impact on climate change. However, can the overall trend in GHG emissions be certainly attributed to changes in economic activity? Is there a clear convergence between economic activity and GHG emissions, resulting in a strong downward or upward trend in the GHG emissions intensity of economic activity, measured as GHG emissions per unit of GDP.
The primary motive of our analysis is to scrutinize the effect of irregularities in the rainfall pattern on crop yield in agriculture sector in India and in turn attempt to discover any relation between the growing rate of suicides amongst farmers. Through our visualizations, we would like to derive meaningful insights that foster our understanding about how climactic changes have an influence on various factors including socioeconomic factors that might lead to these suicidal attempts.
 
  
<!--INTRODUCTION-->
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This data-viz project report uncovers some facts for the world leaders to ponder over and take decisive measures before we cause an irreversible damage to a planet we call "home".
  
<!--INSPIRATION-->  
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<!--MOTIVATION-->  
 
<div style="text-align:center;vertical-align:bottom;padding-top:20px;">   
 
<div style="text-align:center;vertical-align:bottom;padding-top:20px;">   
<font size = 5><span style="font-family:Century Gothic;">Inspiration</span></font>  
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<font size = 5><span style="font-family:Century Gothic;">Motivation</span></font>  
 
</div>
 
</div>
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Climate hazards are natural events in weather cycles. We’ve always had hurricanes and droughts, flooding and high winds. However, we are currently witnessing a scale of destruction and devastation that is new and terrifying. 2017 alone has seen a series of devastating climate disasters in various parts of the world, extreme weather events such as Hurricane Irma, deadly heat waves in India, Europe and elsewhere, and flooding in south-east Asia. From Houston to Mumbai, millions of homes are underwater or blown over, and millions of people are homeless and impoverished. The evidence is overwhelming:
 +
<ul>
 +
  <li>Average of 400 “extreme weather events” every year</li>
 +
  <li>Since June 2017, roughly 41 million people have been affected by flooding</li>
 +
  <li>More than 150 million people live on land that will be below sea level or regular flood levels by the end of the century.</li>
 +
  <li>Growing storm surges and tsunamis threaten nearly a quarter of the world’s population.</li>
 +
</ul>
  
According to the '''''National Crime Records Bureau (NCRB)''''' of India as of 2015, at least 270,940 Indian farmers have committed suicide since 1995 resulting in an average 46 suicides a day. Going beyond the political issue that this has transformed into, farmer suicides is a sensitive matter that calls for attention and needs to be analysed in detail.
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In past few years, world leaders have come together to bring all nations together to undertake ambitious efforts to combat climate change. Through this project, we aim to provide more evidence on climate change and economic development. We hope to contribute to growing issue of climate change and possibly spread more awareness among people around the globe.
  
Although, agriculture contributes 14% in the Gross Domestic Product (GDP) in India, 64% of the population depends on agriculture for their livelihood. A new study suggests that India will see more erratic whether events in the coming years bringing more drought and more storms which makes it vitally important to study historical data to understand future better. This analysis is an honest endeavour in gaining deeper knowledge into the impact of increasingly changing whether trends so that we can be prepared to mitigate the risk of these uncontrollable factors and seek remedies that would help sustain such drastic natural phenomenon.
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<!--OBJECTIVES-->  
 
 
<!--INSPIRATION-->
 
 
 
<!--KEY OBJECTIVES-->
 
 
<div style="text-align:center;vertical-align:bottom;padding-top:5px;">  
 
<div style="text-align:center;vertical-align:bottom;padding-top:5px;">  
<font size = 5><span style="font-family:Century Gothic;">Key Objectives</span></font>
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<font size = 5><span style="font-family:Century Gothic;">Main Objectives</span></font>
 
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</div>
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The main objectives for this project are as listed:
  
The objective of this project is to analyze the rainfall pattern changes in India and to find out how it is affecting India’s overall Agricultural production. Also, we will try to find out if there is any correlation between changing rainfall patterns and farmer’s suicide cases happening in India.
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<p>
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<b>Driving Forces behind Climate Change</b>: Through interactive visualization, we aim to study trends in potential economic, science and technology, and climate change indicators over the last 2 decades. We will try to uncover relationship between climate change and economic factors. Since science and technology has advanced significantly during this period, we would like to find out its impact on climate and economic advancement.
 +
</p>
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<p>
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<b>Implement Forecast Model for Policymakers</b>: Using R Shiny and Tableau, we want to implement forecast model, driven by interactive visualization, to help policy makers take timely and corrective actions towards climate change.
 +
</p>
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[[Image:climate1.jpg|centre|350px|alt=Afghanistan savings of CO2]]
  
<!--KEY OBJECTIVES-->
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<!--TOOLS-->  
 
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<div style="text-align:center;vertical-align:bottom;padding-top:25px;">  
<!--RAINFALL IMAGE - TABLEAU-->
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<font size = 5><span style="font-family:Century Gothic;">Visualization Tools</span></font>  
<div style="text-align:center;vertical-align:bottom;padding-top:5px;">  
 
<font size = 5><span style="font-family:Century Gothic;">A Glance At The State-Wise Rainfall Patterns Across India for Years 2008 and 2015</span></font>
 
 
</div>
 
</div>
  
{| width="100%" cellspacing="0" cellpadding="0" valign="top" border="0"  | 
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For our analysis, we propose to carry out interactive visualisation using Tableau, Excel, JMP in addition to R involving following packages:
| style="text-align:center;" | 
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<ul>
;
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  <li>shiny</li>
[[File:RainfallPatternSideBySide.png|1000px]]
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  <li>shinydashboard</li>
;
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  <li>heatmaply</li>
|}
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  <li>RColorBrewer</li>
<!--RAINFALL IMAGE - TABLEAU-->
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  <li>tidyverse</li>
 
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  <li>tm</li>
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  <li>wordcloud</li>
 +
  <li>maps</li>
 +
  <li>circlize</li>
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  <li>migest</li>
 +
  <li>plotly</li>
 +
  <li>seriation</li>
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  <li>dendextend</li>
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  <li>GGally</li>
 +
  <li>sf</li>
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  <li>tmap</li>
 +
  </ul>
  
 
<!--DATASET-->  
 
<!--DATASET-->  
 
<div style="text-align:center;vertical-align:bottom;padding-top:25px;">  
 
<div style="text-align:center;vertical-align:bottom;padding-top:25px;">  
<font size = 5><span style="font-family:Century Gothic;">Description of Dataset</span></font>  
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<font size = 5><span style="font-family:Century Gothic;">Dataset Description</span></font>  
 
</div>
 
</div>
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With a deep dive into the corresponding pollutant type, activity and measure, the core of our analysis will be around following 3 Environment data-sets:
 +
<ul>
 +
  <li>http://stats.ukdataservice.ac.uk/ -> OECD -> Environment Statistics -> Air and Climate -> Air Emission Accounts</li>
 +
  <li>http://stats.ukdataservice.ac.uk/ -> OECD -> Environment Statistics -> Air and Climate -> Emissions of Air Pollutants</li>
 +
  <li>http://stats.ukdataservice.ac.uk/ -> OECD -> Environment Statistics -> Air and Climate -> Greenhouse Gas Emissions</li>
 +
</ul>
 +
We will also try to draw parallels of our analysis of environment statistics with a completely independent International Monetary Fund data-set to track growth measures in OECD countries:
 +
<ul>
 +
  <li>http://stats.ukdataservice.ac.uk/ -> International Monetary Fund-> World Economic Outlook</li>
 +
</ul>
 +
The following is a list of few indicators from our aggregated data-source.
 
{| class="wikitable"
 
{| class="wikitable"
 
|-
 
|-
! Data !! Format !! Source
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! Indicator Name!! Description
 +
|-
 +
| GDP || Gross Domestic Product Per Capita
 
|-
 
|-
| Rainfall Pattern district-wise  || xls || http://hydro.imd.gov.in/hydrometweb/(S(lf11dr45dr2w0czzyvrhep55))/DistrictRaifall.aspx
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| CO2|| Carbon Dioxide Emissions in Tonnes
 
|-
 
|-
| District-wise & Season-wise Crop Production  || xls || https://data.gov.in/catalog/district-wise-season-wise-crop-production-statistics
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| CO|| Carbon Monoxide Emissions in Tonnes
 +
|-
 +
| FDI_Inflow || FDI Inflow (USD) from Partner Countries
 +
|-
 +
| Forest|| % of Land Area covered by Forest
 
|-
 
|-
| Farmer Suicide Data 2015 || xls || https://data.gov.in/resources/farmers-suicide-data-period-2011-2014-ministry-agriculture-and-farmers-welfare
 
 
|}
 
|}
<!--DATASET-->
 
 
<!--KEY MILESTONES-->
 
<div style="text-align:center;vertical-align:bottom;padding-top:5px;">
 
<font size = 5><span style="font-family:Century Gothic;">Key Milestones</span></font>
 
 
Key milestones (tentative) are listed below:
 
 
</div>
 
 
{| width="100%" cellspacing="0" cellpadding="0" valign="top" border="0"  | 
 
| style="text-align:center;" | 
 
;
 
[[File:ProjectMilestonesGnattChart.png|700px]]
 
;
 
|}
 
 
<!--KEY MILESTONES-->
 
 
<!--EXPECTED CHALLENGES-->
 
<div style="text-align:center;vertical-align:bottom;padding-top:25px;">
 
<font size = 5><span style="font-family:Century Gothic;">Expected Challenges</span></font>
 
</div>
 
 
1. Data collection – we are still in the process of data collection. We are collecting data from various sources and will be integrating it together before analysis.
 
 
2. Steep learning curve – there is a steep learning curve involved in working with R-Shiny, SAS JMP Pro and Tableau.
 
 
3. Correlation between rainfall pattern and farmer’s suicide – Even though it is apparent that changes in the rainfall pattern over past few years affecting agriculture industry in India and increasing farmer’s worries, discovering direct correlation between rainfall pattern and farmer’s suicide is challenging.
 
 
<!--EXPECTED CHALLENGES-->
 
 
 
<!--REFERENCES-->
 
<!--REFERENCES-->
 
<div style="text-align:center;vertical-align:bottom;padding-top:25px;">  
 
<div style="text-align:center;vertical-align:bottom;padding-top:25px;">  
 
<font size = 5><span style="font-family:Century Gothic;">References</span></font>
 
<font size = 5><span style="font-family:Century Gothic;">References</span></font>
 
</div>
 
</div>
 
+
<ul>
<i><b>1.</b> https://www.theguardian.com/environment/2017/jul/31/suicides-of-nearly-60000-indian-farmers-linked-to-climate-change-study-claims</i>
+
  <li>[1] The Elements of Statistical Learning : Data Mining, Inference, and Prediction, Second Edition, By (author)  Trevor Hastie , By (author)  Jerome Friedman , By (author)  Robert Tibshirani</li>
 
+
  <li>[2] Naked Statistics : Stripping the Dread from the Data, By (author)  Charles Wheelan</li>
<i><b>2.</b> https://scroll.in/article/881265/india-has-not-published-data-on-farmer-suicides-for-the-last-two-years</i>
+
  <li>[3] Storytelling with Data : A Data Visualization Guide for Business Professionals, By (author)  Cole Nussbaumer Knaflic</li>
 
+
  <li>[4]    https://en.wikipedia.org/wiki/OECD</li>
<i><b>3.</b> http://www.pnas.org/content/early/2017/07/25/1701354114#sec-1</i>
+
  <li>[5] R for Data Science, By (author)  Hadley Wickham , By (author)  Garrett Grolemund</li>
 
+
  <li>[6]    http://www.datacamp.com</li>
<i><b>4.</b> http://www.newsweek.com/2014/04/18/death-farm-248127.html</i>
+
</ul>
 
 
<i><b>5.</b> http://www.chicagotribune.com/news/nationworld/science/ct-india-farmers-suicide-climate-change-20170731-story.html</i>
 
 
 
<i><b>6.</b> https://www.sciencedirect.com/science/article/pii/S2210600615300277</i>
 
 
 
<!--REFERENCES-->
 

Latest revision as of 00:07, 14 August 2018

ISSS608 Visual Analytics and Applications

Group 13 : Proposal

Climate.jpg

Economic Growth And Climate Change

Proposal

Analysis Report

Poster

Application

 

Introduction

The Organization for Economic Co-operation and Development is an intergovernmental economic organization with 37 member countries, founded in 1961 to stimulate economic progress and world trade. Most OECD members are high-income economies with a very high Human Development Index (HDI) and are regarded as developed countries. As of 2017, the OECD member states collectively comprised 62.2% of global nominal GDP (US$49.6 trillion) and 42.8% of global GDP ($54.2 trillion) at purchasing power parity.

OECD.jpg

But has this economic progress come at a cost? During this period, the reported green house gas (GHG) emissions has shown a rising trend. For instance, there was a large decrease in GHG emissions in 2009 due to economic recession, further enforcing our fears that human activities could have drastic impact on climate change. However, can the overall trend in GHG emissions be certainly attributed to changes in economic activity? Is there a clear convergence between economic activity and GHG emissions, resulting in a strong downward or upward trend in the GHG emissions intensity of economic activity, measured as GHG emissions per unit of GDP.

This data-viz project report uncovers some facts for the world leaders to ponder over and take decisive measures before we cause an irreversible damage to a planet we call "home".

Motivation

Climate hazards are natural events in weather cycles. We’ve always had hurricanes and droughts, flooding and high winds. However, we are currently witnessing a scale of destruction and devastation that is new and terrifying. 2017 alone has seen a series of devastating climate disasters in various parts of the world, extreme weather events such as Hurricane Irma, deadly heat waves in India, Europe and elsewhere, and flooding in south-east Asia. From Houston to Mumbai, millions of homes are underwater or blown over, and millions of people are homeless and impoverished. The evidence is overwhelming:

  • Average of 400 “extreme weather events” every year
  • Since June 2017, roughly 41 million people have been affected by flooding
  • More than 150 million people live on land that will be below sea level or regular flood levels by the end of the century.
  • Growing storm surges and tsunamis threaten nearly a quarter of the world’s population.

In past few years, world leaders have come together to bring all nations together to undertake ambitious efforts to combat climate change. Through this project, we aim to provide more evidence on climate change and economic development. We hope to contribute to growing issue of climate change and possibly spread more awareness among people around the globe.

Main Objectives

The main objectives for this project are as listed:

Driving Forces behind Climate Change: Through interactive visualization, we aim to study trends in potential economic, science and technology, and climate change indicators over the last 2 decades. We will try to uncover relationship between climate change and economic factors. Since science and technology has advanced significantly during this period, we would like to find out its impact on climate and economic advancement.

Implement Forecast Model for Policymakers: Using R Shiny and Tableau, we want to implement forecast model, driven by interactive visualization, to help policy makers take timely and corrective actions towards climate change.

Afghanistan savings of CO2

Visualization Tools

For our analysis, we propose to carry out interactive visualisation using Tableau, Excel, JMP in addition to R involving following packages:

  • shiny
  • shinydashboard
  • heatmaply
  • RColorBrewer
  • tidyverse
  • tm
  • wordcloud
  • maps
  • circlize
  • migest
  • plotly
  • seriation
  • dendextend
  • GGally
  • sf
  • tmap

Dataset Description

With a deep dive into the corresponding pollutant type, activity and measure, the core of our analysis will be around following 3 Environment data-sets:

We will also try to draw parallels of our analysis of environment statistics with a completely independent International Monetary Fund data-set to track growth measures in OECD countries:

The following is a list of few indicators from our aggregated data-source.

Indicator Name Description
GDP Gross Domestic Product Per Capita
CO2 Carbon Dioxide Emissions in Tonnes
CO Carbon Monoxide Emissions in Tonnes
FDI_Inflow FDI Inflow (USD) from Partner Countries
Forest % of Land Area covered by Forest

References

  • [1] The Elements of Statistical Learning : Data Mining, Inference, and Prediction, Second Edition, By (author) Trevor Hastie , By (author) Jerome Friedman , By (author) Robert Tibshirani
  • [2] Naked Statistics : Stripping the Dread from the Data, By (author) Charles Wheelan
  • [3] Storytelling with Data : A Data Visualization Guide for Business Professionals, By (author) Cole Nussbaumer Knaflic
  • [4] https://en.wikipedia.org/wiki/OECD
  • [5] R for Data Science, By (author) Hadley Wickham , By (author) Garrett Grolemund
  • [6] http://www.datacamp.com