I have a data set having year-wise monthly average of minimum and maximum temperatures of 32 stations around the country since 1948. The latitude and longitude of the stations are given as well. I have been asked to dig deep into the data set and analyze the much I can. The main objective is to understand the trend and possibly predict the future values.

I have little experience to work with such data sets. I usually like to use R. I have three questions in particular.

1) I can see that the latitude and longitude of an station are given to be 25.72 and 89.26 respectively. The corresponding Y and X coordinates are calculated as 844822.3 and 426172.9. I don't understand how they have calculated this. Can anyone explain?

2) What model should I fit to the data to get a good prediction of future values? Since I have the data since 1948, I might use a time series model, but here I have the latitude and longitude information too. So is there any model that can use these information too? Is there any particular package in R that will be useful for me?

3) Can I use R to find interesting plots mapping my findings or different summary statistics in map of the country? Some 2D or 3D plots will be excellent for me.

Many thanks for your kind response in advance.

  • $\begingroup$ I am also quite concerned about the over-fitting problem that might occur by using the latitude and longitude as regressors. $\endgroup$
    – Blain Waan
    Commented Jul 4, 2014 at 9:29
  • $\begingroup$ For 1 the coordinates are likely in some type of projection. The answer to 3 is generically yes. 2 is difficult to answer in this format, IMO the best anyone could do is give general reference to the lit. $\endgroup$
    – Andy W
    Commented Jul 4, 2014 at 12:07
  • 4
    $\begingroup$ There is far too much here to address. To get a handle on these issues you will need to learn about representing geographic data (projections and coordinate systems); and then about spatio-temporal data analysis, which is a kind of marriage of time series analysis (which you need to know very well) and spatial data analysis (geostatistics); and have a deep understanding of climate models. Those things will take anybody years to learn and more years to learn well, but if you absolutely must do it yourself, take a look at Cressie & Wikle, Statistics for Spatio-Temporal Data (J. Wiley, 2011). $\endgroup$
    – whuber
    Commented Jul 4, 2014 at 15:48
  • $\begingroup$ Thank you so much for the reference. I'll try to learn it and yes I understand that it will take time. But thanks for you hints. $\endgroup$
    – Blain Waan
    Commented Jul 4, 2014 at 19:02
  • $\begingroup$ Also, look at the spacetime package in R! $\endgroup$ Commented Mar 26, 2016 at 13:36

1 Answer 1


That´s a big task for one person. I can suggest you only some books related to 1) and 3). If you want to analyse your data in R a good reference is Applied Spatial Data Analysis with R and thesp package. On the book´s webpage you can find sample data and the code used thorughout the book. Another books are:

Spatial Data Analysis in Ecology and Agriculture using R, a free book A Practical Guide to Geostatistical Mapping, or Displaying time series, spatial and space-time data with R. If you will work with rasters in R, than there is a raster package . Or you can do it in GIS software, for example ArcGIS or SAGA GIS, and check the GIS Stackexchange

My answer did not cover the time series analysis though...try the Quick R page.

  • $\begingroup$ This references will be a great help indeed. Thanks a lot! $\endgroup$
    – Blain Waan
    Commented Jul 5, 2014 at 4:52

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.