Merge pull request gee-community#342 from lopezvoliver/netcdf_to_ee

Netcdf to ee

README.rst

@@ -336,6 +336,12 @@ To import a 2D or 3D numpy array to an ee.Image using a given base coordinate re
 
   geemap.numpy_to_ee(np_array, crs, transform, transformWkt, band_names)
 
+To import one or more variables from a netCDF file with a regular grid in EPSG:4326 to an ee.Image:
+
+.. code:: python
+
+  geemap.netcdf_to_ee(nc_file, var_names, band_names, lon='lon', lat='lat')
+
 To calculate zonal statistics:
 
 .. code:: python

examples/notebooks/netcdf_to_ee.ipynb

@@ -0,0 +1,130 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Uncomment the following line to install [geemap](https://geemap.org) if needed.\n",
+    "\n",
+    "You will also need to install the following package:\n",
+    "- `xarray`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# !pip install geemap"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import geemap\n",
+    "import ee\n",
+    "ee.Initialize()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "if not os.path.exists('wind-global.nc'):\n",
+    "    url = 'https://github.com/giswqs/geemap/blob/master/examples/data/wind-global.nc'\n",
+    "    import requests\n",
+    "    r = requests.get(url)\n",
+    "    wind_data = r.content\n",
+    "    with open('wind-global.nc', 'wb') as f:\n",
+    "        f.write(wind_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f0ec3a01364a4eb391e4e25c6fe2725b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Map(center=[40, -100], controls=(WidgetControl(options=['position'], widget=HBox(children=(ToggleButton(value=…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Test with only one variable\n",
+    "img = geemap.netcdf_to_ee(nc_file=\"wind-global.nc\", var_names='u_wind')\n",
+    "import geemap.colormaps as cm\n",
+    "palette=cm.palettes.YlOrRd\n",
+    "Map = geemap.Map()\n",
+    "Map.addLayer(img, {'min':-20, 'max':25, 'palette':palette, 'opacity':0.6})\n",
+    "Map"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "cbe695f1593144d5a13bcfe52add9776",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Map(center=[40, -100], controls=(WidgetControl(options=['position'], widget=HBox(children=(ToggleButton(value=…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Test with two variables\n",
+    "img2 = geemap.netcdf_to_ee(nc_file=\"wind-global.nc\", var_names=['u_wind','v_wind'])\n",
+    "Map2 = geemap.Map()\n",
+    "Map2.addLayer(img2, {'bands':['u_wind'],'min':-20, 'max':25, 'palette':palette, 'opacity':0.6})\n",
+    "Map2"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "geemap",
+   "language": "python",
+   "name": "geemap"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

geemap/common.py

@@ -1773,6 +1773,97 @@ def get_image_collection_thumbnails(
         print(e)
 
 
+def netcdf_to_ee(nc_file, var_names, band_names=None, lon="lon", lat="lat"):
+    """
+    Creates an ee.Image from netCDF variables band_names that are read from nc_file. Currently only supports variables in a regular longitude/latitude grid (EPSG:4326).
+    
+    Args:
+        nc_file (str): the name of the netCDF file to read        
+        var_names (str or list): the name(s) of the variable(s) to read
+        band_names (list, optional): if given, the bands are renamed to band_names. Defaults to the original var_names
+        lon (str, optional): the name of the longitude variable in the netCDF file. Defaults to "lon"
+        lat (str, optional): the name of the latitude variable in the netCDF file. Defaults to "lat"
+        
+        Returns:
+            image: An ee.Image 
+        
+    """
+    try:
+        import xarray as xr
+
+    except Exception:
+        raise ImportError(
+            "You need to install xarray first. See https://github.com/pydata/xarray"
+        )
+
+    import numpy as np
+
+    try:
+
+        if not isinstance(nc_file, str):
+            print("The input file must be a string.")
+            return    
+        if band_names and not isinstance(band_names, (list,str)):
+            print("Band names must be a string or list.")
+            return
+        if not isinstance(lon, str) or not isinstance(lat, str):
+            print("The longitude and latitude variable names must be a string.")
+            return
+
+        ds = xr.open_dataset(nc_file)
+        data = ds[var_names]
+
+        lon_data = data[lon]
+        lat_data = data[lat]
+
+        dim_lon = np.unique(np.ediff1d(lon_data))
+        dim_lat = np.unique(np.ediff1d(lat_data))
+
+        if (len(dim_lon)!=1) or (len(dim_lat)!=1):
+            print("The netCDF file is not a regular longitude/latitude grid")
+            return
+
+        try:
+            data = data.to_array()
+            # ^ this is only needed (and works) if we have more than 1 variable
+            # axis_for_roll will be used in case we need to use np.roll
+            # and should be 1 for the case with more than 1 variable
+            axis_for_roll=1
+        except Exception:
+            axis_for_roll=0
+            # .to_array() does not work (and is not needed!) if there is only 1 variable
+            # in this case, the axis_for_roll needs to be 0      
+
+        data_np = np.array(data)
+
+        do_transpose = True # To do: figure out if we need to tranpose the data or not
+        if do_transpose:
+            try: 
+                data_np = np.transpose(data_np, (0,2,1))
+            except Exception:
+                data_np = np.transpose(data_np)
+
+        # Figure out if we need to roll the data or not 
+        # (see https://github.com/giswqs/geemap/issues/285#issuecomment-791385176)
+        if(np.max(lon_data)>180):
+            data_np = np.roll(data_np, 180, axis = axis_for_roll)
+            west_lon = lon_data[0]-180
+        else:
+            west_lon = lon_data[0]
+
+        transform = [dim_lon[0], 0, float(west_lon), 0, dim_lat[0], float(lat_data[0])]
+
+        if band_names is None:
+            band_names = var_names
+
+        image = numpy_to_ee(data_np, 'EPSG:4326', transform=transform, band_names=band_names)
+
+        return image
+
+    except Exception as e:
+        print(e)
+
+
 def numpy_to_ee(np_array, crs=None, transform=None, transformWkt=None, band_names=None):
     """
     Creates an ee.Image from a 3D numpy array where each 2D numpy slice is added to a band, and a geospatial transform that indicates where to put the data. If the np_array is already 2D only, then it is only a one-band image.