Update documentation

Author: spatialthoughts

README.html

@@ -186,24 +186,24 @@
 <li class="toctree-l1"><a class="reference internal" href="notebooks/geopandas_extract_from_excel.html">Extract a Shapefile Subset</a></li>
 <li class="toctree-l1"><a class="reference internal" href="notebooks/geopandas_fuzzy_table_join.html">Performing Fuzzy Table Joins</a></li>
 </ul>
-<p aria-level="2" class="caption" role="heading"><span class="caption-text">XArray for Raster Data Processing</span></p>
+<p aria-level="2" class="caption" role="heading"><span class="caption-text">Xarray for Raster Data Processing</span></p>
 <ul class="nav bd-sidenav">
-<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_raster_styling_analysis.html">Basic Raster Styling and Analysis</a></li>
-<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_mosaic_and_clip.html">Raster Mosaicing and Clipping</a></li>
-<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_raster_sampling.html">Sampling Raster Data with XArray</a></li>
-<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_extracting_time_series.html">Extracting Time Series (Single Point)</a></li>
-<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_extracting_time_series_multiple.html">Extracting Time-Series (Multiple Points)</a></li>
-<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_zonal_stats.html">Zonal Statistics with XArray</a></li>
-<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_zonal_stats_time_series.html">Zonal Statistics Time-Series with XArray</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_raster_styling_analysis.html">Basic Raster Styling and Analysis with Xarray</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_mosaic_and_clip.html">Raster Mosaicing and Clipping with Xarray</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_raster_sampling.html">Sampling Raster Data using Points with Xarray</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_zonal_stats.html">Sampling Raster Data using Polygons with Xarray</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_extracting_time_series.html">Extracting Time Series at a Single Point with Xarray</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_extracting_time_series_multiple.html">Extracting Time Series at Multiple Points with Xarray</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_zonal_stats_time_series.html">Extracting Time Series at Multiple Polygons with Xarray</a></li>
 <li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_processing_satellite_images.html">Processing Satellite Images with XArray</a></li>
 </ul>
-<p aria-level="2" class="caption" role="heading"><span class="caption-text">XArray for Climate Data Processing</span></p>
+<p aria-level="2" class="caption" role="heading"><span class="caption-text">Xarray for Climate Data Processing</span></p>
 <ul class="nav bd-sidenav">
 <li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_aggregating_time_series.html">Aggregating Precipitation Time Series</a></li>
 <li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_climate_anomaly.html">Calculating Climate Anomaly</a></li>
 <li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_climate_trends.html">Computing Pixel-Wise Long-Term Climate Trends</a></li>
 </ul>
-<p aria-level="2" class="caption" role="heading"><span class="caption-text">XArray Utilities</span></p>
+<p aria-level="2" class="caption" role="heading"><span class="caption-text">Xarray Utilities</span></p>
 <ul class="nav bd-sidenav">
 <li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_create_raster.html">Create a Raster from Array</a></li>
 <li class="toctree-l1"><a class="reference internal" href="notebooks/xarray_wrap_longitude.html">Transform Longitude Values</a></li>
@@ -213,7 +213,7 @@
 <li class="toctree-l1"><a class="reference internal" href="notebooks/dask_creating_spatial_data.html">Creating Spatial Data</a></li>
 <li class="toctree-l1"><a class="reference internal" href="notebooks/dask_median_composite.html">Creating a Median Composite with Dask</a></li>
 </ul>
-<p aria-level="2" class="caption" role="heading"><span class="caption-text">XEE (XArray + Google Earth Engine)</span></p>
+<p aria-level="2" class="caption" role="heading"><span class="caption-text">XEE (Xarray + Google Earth Engine)</span></p>
 <ul class="nav bd-sidenav">
 <li class="toctree-l1"><a class="reference internal" href="notebooks/xee_ic_to_netcdf.html">Exporting an ImageCollection to NetCDF</a></li>
 <li class="toctree-l1"><a class="reference internal" href="notebooks/xee_time_series_processing.html">Processing Time-Series with XEE and XArray</a></li>

_sources/notebooks/xarray_extracting_time_series.ipynb

@@ -6,11 +6,11 @@
     "id": "VCi5DKHB7jag"
    },
    "source": [
-    "# Extracting Time Series (Single Point)\n",
+    "# Extracting Time Series at a Single Point with Xarray\n",
     "\n",
     "## Introduction\n",
     "\n",
-    "XArray makes it very easy to work with time-series data. The [DataArray](https://docs.xarray.dev/en/stable/user-guide/data-structures.html#dataarray) structure provides an efficient way to organize and represent earth observation time-series. We also get the benefit of many time-series processing functiions for temporal interpolation and smoothing. This tutorial shows how we can take individual GeoTIFF files and organize them as a XArray Dataset, extract time-series at any coordinate and do linear interpolation of masked observation.\n",
+    "Xarray makes it very easy to work with time-series data. The [DataArray](https://docs.xarray.dev/en/stable/user-guide/data-structures.html#dataarray) structure provides an efficient way to organize and represent earth observation time-series. We also get the benefit of many time-series processing functiions for temporal interpolation and smoothing. This tutorial shows how we can take individual GeoTIFF files and organize them as a Xarray Dataset, extract time-series at any coordinate and do linear interpolation of masked observation.\n",
     "\n",
     "## Overview of the Task\n",
     "\n",
@@ -170,7 +170,7 @@
     "\n",
     "For example the file `MOD13A1.006__500m_16_days_NDVI_doy2020161_aid0001.tif` contains **NDVI** values for the Day of the Year (DOY) **161** of the year **2020**.\n",
     "\n",
-    "We will now go through the directory and extract this information to create a XArray DataArray."
+    "We will now go through the directory and extract this information to create a Xarray DataArray."
    ]
   },
   {
@@ -251,7 +251,7 @@
     "id": "n-FAk2lMacPA"
    },
    "source": [
-    "We now have a list of individual XArray Datasets for each time step. We merge them to a single DataSet along the `time` dimension."
+    "We now have a list of individual Xarray Datasets for each time step. We merge them to a single DataSet along the `time` dimension."
    ]
   },
   {
@@ -851,7 +851,7 @@
     "* 2: Pixel covered with snow/ice\n",
     "* 3: Pixel is cloudy\n",
     "\n",
-    "We select all pixels with value 0 or 1 and mask the remaining ones. We can apply this as a vectorized operation across all scenes instead of iterating over each image. This is a very fast and efficient operation enabled by XArray.\n"
+    "We select all pixels with value 0 or 1 and mask the remaining ones. We can apply this as a vectorized operation across all scenes instead of iterating over each image. This is a very fast and efficient operation enabled by Xarray.\n"
    ]
   },
   {
@@ -1007,7 +1007,7 @@
     "id": "bZlwGdHn7T_S"
    },
    "source": [
-    "We have gaps in the time-series due to masked cloudy-pixels. Replace them with linearly interpolated values using XArray's [`interpolate_na()`](https://docs.xarray.dev/en/stable/generated/xarray.DataArray.interpolate_na.html) function."
+    "We have gaps in the time-series due to masked cloudy-pixels. Replace them with linearly interpolated values using Xarray's [`interpolate_na()`](https://docs.xarray.dev/en/stable/generated/xarray.DataArray.interpolate_na.html) function."
    ]
   },
   {

_sources/notebooks/xarray_extracting_time_series_multiple.ipynb

@@ -7,7 +7,7 @@
         "id": "a6973a51-8385-4a35-ac12-c60d1d2306f0"
       },
       "source": [
-        "# Extracting Time-Series (Multiple Points)\n",
+        "# Extracting Time Series at Multiple Points with Xarray\n",
         "\n",
         "## **Introduction**\n",
         "\n",