Publications by Gopi Goteti

Towards the R package sheldus, Part 1: Natural Disaster Losses in the US in 2012

07.11.2013

The SHELDUS database, short for Spatial Hazard Events and Losses Database in the United States (http://webra.cas.sc.edu/hvri/products/sheldus.aspx), from the University of South Carolina, is a  database on human and property losses from natural disasters in the United States. Data from this database includes County-level information on property ...

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Towards the R package sheldus: Part 2: Losses from Natural Disasters in the US

09.11.2013

In my earlier post I summarized the work on my upcoming R package on the SHELDUS database. This is a database on human and property losses from natural disasters in the United States. Although the data is free, downloading the data is tedious and so is cleaning and analyzing it. My goal is to package the data efficiently so it could be accessed ...

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New R package sheldusr: Losses from Natural Disasters in the United States

17.11.2013

The SHELDUS database is database on human and property losses from natural disasters in the United States. Although the data is free, downloading the data is tedious and so is cleaning and analyzing it. The new R package sheldusr comes with the cleaned and pre-processed SHELDUS data and includes functionality to retrieve data for any desired t...

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Towards the R package emdat: Losses from Global Disasters, Part 1

18.11.2013

The International Disaster Database, EM-DAT from the Center for Research on the Epidemiology of Disasters (CRED, Belgium) is often used as a reference for losses on human life and property resulting from natural and man-made disasters. This database has over 20,000 country-level records from the early 1900s to the present. Data is av...

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New R package emdatr: Global Disaster Losses from the EM-DAT Database

22.11.2013

The International Disaster Database EM-DAT from the Center for Research on the Epidemiology of Disasters (CRED, Belgium) is often used as a reference for losses on human life and property resulting from natural and man-made disasters. This database has over 20,000 country-level records from the early 1900s to the present. Data is ava...

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New R package raincpc: Obtain and Analyze Global Rainfall data from the Climate Prediction Center (CPC)

26.11.2013

The Climate Prediction Center’s (CPC) daily rainfall data for the entire world, 1979 – present & 50-km resolution, is one of the few high quality and long term observation-based rainfall products. Data is available at CPC’s ftp site. However, it is a lot of data and there is no software to analyze and visualize the data.Some iss...

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New R package raincpc: Obtain and Analyze Rainfall data from the Climate Prediction Center (CPC)

26.11.2013

The Climate Prediction Center’s (CPC) daily rainfall data for the entire world, 1979 – present & 50-km resolution, is one of the few high quality and long term observation-based rainfall products. Data is available at CPC’s ftp site. However, it is a lot of data and there is no software to analyze and visualize the data.Some iss...

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The Tornado Project

09.12.2013

GoalBring consistency and transparency to the analyses of publicly available Tornado datasets using an R-based open source analysis.IssuesTornado data available from the NOAA Storm Prediction Center and other government agencies around the world has been the focus of many studies (e.g., see below references). However, there are a number of issue...

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The Tornado Project: Counting Tornadoes

29.12.2013

The goal of this open source R-based analysis, as mentioned in my earlier post, is to bring consistency and transparency to the analyses of publicly available Tornado datasets.The project home page is on my GitHub site – https://github.com/RationShop/tornado_r/wiki/The-Tornado-ProjectThe latest analysis is on the reproduction of s...

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The Rain Project: An R-based Open Source Analysis of Publicly Available Rainfall Data

06.01.2014

Rainfall data used by researchers in academia and industry does not always come in the same format. Data is often in atypical formats and in extremely large number of files and there is not always guidance on how to obtain, process and visualize the data. This project attempts to resolve this issue by serving as a hub for the processing of such p...

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