example_cor_spatial (1).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysis of correlation of spatial data: example with water temperature and chlorophyll concentration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Main objective: to check if there is correlation between the concetration of chlorophyll in water and the water temperature. Depending on the algae, there might be a direct or an inverse correlation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## First, we install and load the necessary packages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "install.packages(c(\"dplyr\",\"raster\",\"sdmpredictors\"), repos = \"http://cran.us.r-project.org\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "library(dplyr)\n",
    "library(raster)\n",
    "library(sdmpredictors)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Then, we load worldwide maps of mean temperature and chlorophyll concentration at sea surface."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in get_datadir(datadir):\n",
      "\"file.path(tempdir(), \"sdmpredictors\") will be used as datadir, set options(sdmpredictors_datadir=\"<directory>\") to avoid re-downloading the data in every session or set the datadir parameter in load_layers\"Warning message in get_datadir(datadir):\n",
      "\"file.path(tempdir(), \"sdmpredictors\") will be used as datadir, set options(sdmpredictors_datadir=\"<directory>\") to avoid re-downloading the data in every session or set the datadir parameter in load_layers\""
     ]
    }
   ],
   "source": [
    "temp_r <- sdmpredictors::load_layers(\"BO2_tempmean_ss\") \n",
    "chl_r <- sdmpredictors::load_layers(\"BO2_chlomean_ss\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## For each one of both worldwide maps, we select a small region of the map and we reduce resolution to ease analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "temp_crop_r <- raster::crop(temp_r,extent(-5,5,40,50))%>%  aggregate(2)\n",
    "chl_res_r <- raster::crop(chl_r,extent(-5,5,40,50))%>%  aggregate(2) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Now, we plot both resulting maps to compare their patterns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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PbsWSHE/Pz84OBg2t1BNywvLw8NDaXd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\nAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title \"Chlorophyll concentration (mean)\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "par(mfrow=c(1,2))\n",
    "plot(temp_crop_r[[1]], main='Sea surface temperature (mean)')\n",
    "# rect(0,40.2,2,41.7,border='red')\n",
    "rect(-3,46.5,-1.5,47.5,border='red')\n",
    "rect(-2,44,-0,46,border='red')\n",
    "rect(-4,48,-0.5,49.8,border='red')\n",
    "\n",
    "plot(chl_res_r[[1]],main='Chlorophyll concentration (mean)')\n",
    "# rect(0,40.2,2,41.7,border='red')\n",
    "rect(-3,46.5,-1.5,47.5,border='red')\n",
    "rect(-2,44,-0,46,border='red')\n",
    "rect(-4,48,-0.5,49.8,border='red')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Red rectangles mark interesting regions were patterns like correlated increase/decrease or inverse correlations seem to appear. This kind of effects can be related to different kinds of algae present at sea."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Now, we analyze the local correlation between both maps and perform correlation tests to see regions with significant positive or negative correlation between both maps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cor_result <- raster::corLocal(temp_crop_r, chl_res_r, test=TRUE )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Last, we visually analyze the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AgKOwAAgICgsAMAAAgICjsAAICAoLAD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",
      "text/plain": [
       "Plot with title \"Local correlation test - p-value\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "par(mfrow=c(1,2))\n",
    "plot(cor_result[[1]],main=\"Local correlation coefficient\")\n",
    "# rect(0,40.2,2,41.7,border='red')\n",
    "rect(-3,46.5,-1.5,47.5,border='red')\n",
    "rect(-2,44,-0,46,border='red')\n",
    "rect(-4,48,-0.5,49.8,border='red')\n",
    "plot(cor_result[[2]],main=\"Local correlation test - p-value\")\n",
    "# rect(0,40.2,2,41.7,border='red')\n",
    "rect(-3,46.5,-1.5,47.5,border='red')\n",
    "rect(-2,44,-0,46,border='red')\n",
    "rect(-4,48,-0.5,49.8,border='red')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}