Repository: corteva/rioxarray

Issue:
Make clip_box extend array
Today `clip_box` has an effect only when the array is shrunk. It would be nice if it could extend the array when the bounding box is bigger than the original one, maybe using xarray's `.pad()`?

Discussion:
davidbrochart: Actually there is a bug, the padding doesn't take into account the previous clipping. So maybe `.clip_box()` should be left as it is, and we should have a new `.pad_box()` method? Things like clipping on the right and padding on the left would be achieved by calling `.clip_box()` then `.pad_box()`.

Patch:
diff --git a/.all-contributorsrc b/.all-contributorsrc
index 99acdef6..1222b8ef 100644
--- a/.all-contributorsrc
+++ b/.all-contributorsrc
@@ -107,6 +107,16 @@
         "code",
         "bug"
       ]
+    },
+    {
+      "login": "jhamman",
+      "name": "Joe Hamman",
+      "avatar_url": "https://avatars3.githubusercontent.com/u/2443309?v=4",
+      "profile": "http://joehamman.com",
+      "contributions": [
+        "code",
+        "bug"
+      ]
     }
   ],
   "contributorsPerLine": 7
diff --git a/AUTHORS.rst b/AUTHORS.rst
index 6cd97a2b..1c257d83 100644
--- a/AUTHORS.rst
+++ b/AUTHORS.rst
@@ -23,6 +23,7 @@ Thanks goes to these wonderful people (`emoji key <https://allcontributors.org/d
     <tr>
       <td align="center"><a href="https://github.com/davidbrochart"><img src="https://avatars2.githubusercontent.com/u/4711805?v=4" width="100px;" alt="David Brochart"/><br /><sub><b>David Brochart</b></sub></a><br /><a href="https://github.com/corteva/rioxarray/commits?author=davidbrochart" title="Code">💻</a> <a href="https://github.com/corteva/rioxarray/commits?author=davidbrochart" title="Tests">⚠️</a> <a href="#ideas-davidbrochart" title="Ideas, Planning, & Feedback">🤔</a></td>
       <td align="center"><a href="https://github.com/cheginit"><img src="https://avatars2.githubusercontent.com/u/13016644?v=4" width="100px;" alt="Taher Chegini"/><br /><sub><b>Taher Chegini</b></sub></a><br /><a href="https://github.com/corteva/rioxarray/commits?author=cheginit" title="Code">💻</a> <a href="https://github.com/corteva/rioxarray/issues?q=author%3Acheginit" title="Bug reports">🐛</a></td>
+      <td align="center"><a href="http://joehamman.com"><img src="https://avatars3.githubusercontent.com/u/2443309?v=4" width="100px;" alt="Joe Hamman"/><br /><sub><b>Joe Hamman</b></sub></a><br /><a href="https://github.com/corteva/rioxarray/commits?author=jhamman" title="Code">💻</a> <a href="https://github.com/corteva/rioxarray/issues?q=author%3Ajhamman" title="Bug reports">🐛</a></td>
     </tr>
   </table>
 
diff --git a/README.rst b/README.rst
index 1400ab3e..14b2887e 100644
--- a/README.rst
+++ b/README.rst
@@ -9,7 +9,7 @@ rasterio xarray extension.
    :alt: Join the chat at https://gitter.im/rioxarray/community
    :target: https://gitter.im/rioxarray/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge
 
-.. image:: https://img.shields.io/badge/all_contributors-9-orange.svg?style=flat-square
+.. image:: https://img.shields.io/badge/all_contributors-10-orange.svg?style=flat-square
     :alt: All Contributors
     :target: https://github.com/corteva/rioxarray/blob/master/AUTHORS.rst
 
diff --git a/docs/examples/examples.rst b/docs/examples/examples.rst
index 75855186..74156c8f 100644
--- a/docs/examples/examples.rst
+++ b/docs/examples/examples.rst
@@ -13,6 +13,7 @@ This page contains links to a collection of examples of how to use rioxarray.
    manage_information_loss.ipynb
    clip_geom.ipynb
    clip_box.ipynb
+   pad_box.ipynb
    reproject.ipynb
    reproject_match.ipynb
    merge.ipynb
diff --git a/docs/examples/pad_box.ipynb b/docs/examples/pad_box.ipynb
new file mode 100644
index 00000000..fa0e5b00
--- /dev/null
+++ b/docs/examples/pad_box.ipynb
@@ -0,0 +1,1008 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Example - Pad Box"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import rioxarray # for the extension to load\n",
+    "import xarray\n",
+    "\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load in xarray dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "xds = xarray.open_dataarray(\"../../test/test_data/input/MODIS_ARRAY.nc\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
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+       "\n",
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+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
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+       "</style><div class='xr-wrap'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 200</li><li><span class='xr-has-index'>x</span>: 200</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-20be0e1e-edab-46f7-a598-659298c9e344' class='xr-array-in' type='checkbox' ><label for='section-20be0e1e-edab-46f7-a598-659298c9e344' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan 687.0 687.0 ... 491.0 504.0 504.0 515.0 469.0 485.0</span></div><pre class='xr-array-data'>array([[ nan,  nan,  nan, ..., 656., 656., 554.],\n",
+       "       [ nan,  nan,  nan, ..., 694., 694., 642.],\n",
+       "       [ nan,  nan,  nan, ..., 456., 575., 642.],\n",
+       "       ...,\n",
+       "       [993., 817., 817., ..., 471., 479., 498.],\n",
+       "       [893., 893., 816., ..., 479., 479., 469.],\n",
+       "       [816., 816., 832., ..., 515., 469., 485.]], dtype=float32)</pre></div></li><li class='xr-section-item'><input id='section-af132c8a-256f-43a9-be91-e491fcc3f087' class='xr-section-summary-in' type='checkbox'  checked><label for='section-af132c8a-256f-43a9-be91-e491fcc3f087' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.05e+06 5.05e+06 ... 5.004e+06</div><input id='attrs-6ac241f2-84a4-4ce7-a453-55b2f28be6d2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6ac241f2-84a4-4ce7-a453-55b2f28be6d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b4ab034-adea-428d-a09d-3cdcbf87918b' class='xr-var-data-in' type='checkbox'><label for='data-4b4ab034-adea-428d-a09d-3cdcbf87918b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([5049992.781974, 5049761.125615, 5049529.469257, 5049297.812899,\n",
+       "       5049066.156541, 5048834.500182, 5048602.843824, 5048371.187466,\n",
+       "       5048139.531108, 5047907.874749, 5047676.218391, 5047444.562033,\n",
+       "       5047212.905674, 5046981.249316, 5046749.592958, 5046517.9366  ,\n",
+       "       5046286.280241, 5046054.623883, 5045822.967525, 5045591.311167,\n",
+       "       5045359.654808, 5045127.99845 , 5044896.342092, 5044664.685734,\n",
+       "       5044433.029375, 5044201.373017, 5043969.716659, 5043738.0603  ,\n",
+       "       5043506.403942, 5043274.747584, 5043043.091226, 5042811.434867,\n",
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+       "       5041653.153076, 5041421.496718, 5041189.84036 , 5040958.184001,\n",
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+       "       5038873.276777, 5038641.620419, 5038409.96406 , 5038178.307702,\n",
+       "       5037946.651344, 5037714.994986, 5037483.338627, 5037251.682269,\n",
+       "       5037020.025911, 5036788.369553, 5036556.713194, 5036325.056836,\n",
+       "       5036093.400478, 5035861.74412 , 5035630.087761, 5035398.431403,\n",
+       "       5035166.775045, 5034935.118686, 5034703.462328, 5034471.80597 ,\n",
+       "       5034240.149612, 5034008.493253, 5033776.836895, 5033545.180537,\n",
+       "       5033313.524179, 5033081.86782 , 5032850.211462, 5032618.555104,\n",
+       "       5032386.898746, 5032155.242387, 5031923.586029, 5031691.929671,\n",
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+       "       5028680.397013, 5028448.740655, 5028217.084297, 5027985.427939,\n",
+       "       5027753.77158 , 5027522.115222, 5027290.458864, 5027058.802506,\n",
+       "       5026827.146147, 5026595.489789, 5026363.833431, 5026132.177072,\n",
+       "       5025900.520714, 5025668.864356, 5025437.207998, 5025205.551639,\n",
+       "       5024973.895281, 5024742.238923, 5024510.582565, 5024278.926206,\n",
+       "       5024047.269848, 5023815.61349 , 5023583.957132, 5023352.300773,\n",
+       "       5023120.644415, 5022888.988057, 5022657.331698, 5022425.67534 ,\n",
+       "       5022194.018982, 5021962.362624, 5021730.706265, 5021499.049907,\n",
+       "       5021267.393549, 5021035.737191, 5020804.080832, 5020572.424474,\n",
+       "       5020340.768116, 5020109.111758, 5019877.455399, 5019645.799041,\n",
+       "       5019414.142683, 5019182.486325, 5018950.829966, 5018719.173608,\n",
+       "       5018487.51725 , 5018255.860891, 5018024.204533, 5017792.548175,\n",
+       "       5017560.891817, 5017329.235458, 5017097.5791  , 5016865.922742,\n",
+       "       5016634.266384, 5016402.610025, 5016170.953667, 5015939.297309,\n",
+       "       5015707.640951, 5015475.984592, 5015244.328234, 5015012.671876,\n",
+       "       5014781.015518, 5014549.359159, 5014317.702801, 5014086.046443,\n",
+       "       5013854.390084, 5013622.733726, 5013391.077368, 5013159.42101 ,\n",
+       "       5012927.764651, 5012696.108293, 5012464.451935, 5012232.795577,\n",
+       "       5012001.139218, 5011769.48286 , 5011537.826502, 5011306.170144,\n",
+       "       5011074.513785, 5010842.857427, 5010611.201069, 5010379.544711,\n",
+       "       5010147.888352, 5009916.231994, 5009684.575636, 5009452.919277,\n",
+       "       5009221.262919, 5008989.606561, 5008757.950203, 5008526.293844,\n",
+       "       5008294.637486, 5008062.981128, 5007831.32477 , 5007599.668411,\n",
+       "       5007368.012053, 5007136.355695, 5006904.699337, 5006673.042978,\n",
+       "       5006441.38662 , 5006209.730262, 5005978.073904, 5005746.417545,\n",
+       "       5005514.761187, 5005283.104829, 5005051.44847 , 5004819.792112,\n",
+       "       5004588.135754, 5004356.479396, 5004124.823037, 5003893.166679])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-7.274e+06 ... -7.228e+06</div><input id='attrs-7f23ce3d-56b4-4cf5-bcb4-dcbe82cccd11' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7f23ce3d-56b4-4cf5-bcb4-dcbe82cccd11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd8575bf-ce09-41c6-a3bd-b2f6b7309b95' class='xr-var-data-in' type='checkbox'><label for='data-bd8575bf-ce09-41c6-a3bd-b2f6b7309b95' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([-7273893.821307, -7273662.164949, -7273430.508591, -7273198.852232,\n",
+       "       -7272967.195874, -7272735.539516, -7272503.883158, -7272272.226799,\n",
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+       "       -7270187.319575, -7269955.663217, -7269724.006858, -7269492.3505  ,\n",
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+       "       -7267407.443276, -7267175.786918, -7266944.130559, -7266712.474201,\n",
+       "       -7266480.817843, -7266249.161484, -7266017.505126, -7265785.848768,\n",
+       "       -7265554.19241 , -7265322.536051, -7265090.879693, -7264859.223335,\n",
+       "       -7264627.566977, -7264395.910618, -7264164.25426 , -7263932.597902,\n",
+       "       -7263700.941544, -7263469.285185, -7263237.628827, -7263005.972469,\n",
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+       "       -7261847.690677, -7261616.034319, -7261384.377961, -7261152.721603,\n",
+       "       -7260921.065244, -7260689.408886, -7260457.752528, -7260226.09617 ,\n",
+       "       -7259994.439811, -7259762.783453, -7259531.127095, -7259299.470737,\n",
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+       "       -7247948.309182, -7247716.652823, -7247484.996465, -7247253.340107,\n",
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+       "       -7245168.432882, -7244936.776524, -7244705.120166, -7244473.463808,\n",
+       "       -7244241.807449, -7244010.151091, -7243778.494733, -7243546.838375,\n",
+       "       -7243315.182016, -7243083.525658, -7242851.8693  , -7242620.212942,\n",
+       "       -7242388.556583, -7242156.900225, -7241925.243867, -7241693.587508,\n",
+       "       -7241461.93115 , -7241230.274792, -7240998.618434, -7240766.962075,\n",
+       "       -7240535.305717, -7240303.649359, -7240071.993001, -7239840.336642,\n",
+       "       -7239608.680284, -7239377.023926, -7239145.367568, -7238913.711209,\n",
+       "       -7238682.054851, -7238450.398493, -7238218.742135, -7237987.085776,\n",
+       "       -7237755.429418, -7237523.77306 , -7237292.116701, -7237060.460343,\n",
+       "       -7236828.803985, -7236597.147627, -7236365.491268, -7236133.83491 ,\n",
+       "       -7235902.178552, -7235670.522194, -7235438.865835, -7235207.209477,\n",
+       "       -7234975.553119, -7234743.896761, -7234512.240402, -7234280.584044,\n",
+       "       -7234048.927686, -7233817.271327, -7233585.614969, -7233353.958611,\n",
+       "       -7233122.302253, -7232890.645894, -7232658.989536, -7232427.333178,\n",
+       "       -7232195.67682 , -7231964.020461, -7231732.364103, -7231500.707745,\n",
+       "       -7231269.051387, -7231037.395028, -7230805.73867 , -7230574.082312,\n",
+       "       -7230342.425954, -7230110.769595, -7229879.113237, -7229647.456879,\n",
+       "       -7229415.80052 , -7229184.144162, -7228952.487804, -7228720.831446,\n",
+       "       -7228489.175087, -7228257.518729, -7228025.862371, -7227794.206013])</pre></li></ul></div></li><li class='xr-section-item'><input id='section-9513f523-ec2a-48e1-8e55-e9c7f536c97c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9513f523-ec2a-48e1-8e55-e9c7f536c97c' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>crs :</span></dt><dd>+a=6371007.181 +b=6371007.181 +lon_0=0 +no_defs +proj=sinu +units=m +x_0=0 +y_0=0</dd><dt><span>res :</span></dt><dd>[231.65635826 231.65635826]</dd><dt><span>is_tiled :</span></dt><dd>0</dd><dt><span>nodata :</span></dt><dd>-28672.0</dd><dt><span>transform :</span></dt><dd>[ 2.31656358e+02  0.00000000e+00 -7.27400965e+06  0.00000000e+00\n",
+       " -2.31656358e+02  5.05010861e+06  0.00000000e+00  0.00000000e+00\n",
+       "  1.00000000e+00]</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray (y: 200, x: 200)>\n",
+       "array([[ nan,  nan,  nan, ..., 656., 656., 554.],\n",
+       "       [ nan,  nan,  nan, ..., 694., 694., 642.],\n",
+       "       [ nan,  nan,  nan, ..., 456., 575., 642.],\n",
+       "       ...,\n",
+       "       [993., 817., 817., ..., 471., 479., 498.],\n",
+       "       [893., 893., 816., ..., 479., 479., 469.],\n",
+       "       [816., 816., 832., ..., 515., 469., 485.]], dtype=float32)\n",
+       "Coordinates:\n",
+       "  * y        (y) float64 5.05e+06 5.05e+06 5.05e+06 ... 5.004e+06 5.004e+06\n",
+       "  * x        (x) float64 -7.274e+06 -7.274e+06 ... -7.228e+06 -7.228e+06\n",
+       "Attributes:\n",
+       "    crs:        +a=6371007.181 +b=6371007.181 +lon_0=0 +no_defs +proj=sinu +u...\n",
+       "    res:        [231.65635826 231.65635826]\n",
+       "    is_tiled:   0\n",
+       "    nodata:     -28672.0\n",
+       "    transform:  [ 2.31656358e+02  0.00000000e+00 -7.27400965e+06  0.00000000e..."
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "xds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f44184da310>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "xds.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Pad using a bounding box\n",
+    "\n",
+    "See docs for `rio.pad_box`:\n",
+    "\n",
+    "  - [DataArray.pad_box](../rioxarray.rst#rioxarray.rioxarray.RasterArray.pad_box)\n",
+    "  - [Dataset.pad_box](../rioxarray.rst#rioxarray.rioxarray.RasterDataset.pad_box)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "xdsc = xds.rio.pad_box(\n",
+    "    minx=-7.3e+06,\n",
+    "    miny=4.99e+06,\n",
+    "    maxx=-7.2e+06,\n",
+    "    maxy=5.06e+06,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<title>Show/Hide data repr</title>\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<title>Show/Hide attributes</title>\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt, dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2 {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><div class='xr-wrap'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 303</li><li><span class='xr-has-index'>x</span>: 433</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6cad98e8-e0f5-4607-828d-632be19d619f' class='xr-array-in' type='checkbox' ><label for='section-6cad98e8-e0f5-4607-828d-632be19d619f' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan nan nan nan nan ... nan nan nan nan nan nan nan nan</span></div><pre class='xr-array-data'>array([[nan, nan, nan, ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan],\n",
+       "       ...,\n",
+       "       [nan, nan, nan, ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)</pre></div></li><li class='xr-section-item'><input id='section-88275f46-7916-4e61-b827-6f85f69df23a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-88275f46-7916-4e61-b827-6f85f69df23a' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.06e+06 5.06e+06 ... 4.99e+06</div><input id='attrs-9ea176e1-14ce-4c6d-a7b0-2b2fee6fe71c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ea176e1-14ce-4c6d-a7b0-2b2fee6fe71c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6ca0dd8-86a6-425f-841b-f261f4522e27' class='xr-var-data-in' type='checkbox'><label for='data-b6ca0dd8-86a6-425f-841b-f261f4522e27' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><pre class='xr-var-data'>array([5059954.005379, 5059722.349021, 5059490.692662, ..., 4990457.0979  ,\n",
+       "       4990225.441542, 4989993.785183])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-7.3e+06 -7.3e+06 ... -7.2e+06</div><input id='attrs-1c4adb39-92d5-4f61-bdad-d724a7fb4f2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c4adb39-92d5-4f61-bdad-d724a7fb4f2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f928a182-5da5-45f2-b4b2-e312dcbf9470' class='xr-var-data-in' type='checkbox'><label for='data-f928a182-5da5-45f2-b4b2-e312dcbf9470' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><pre class='xr-var-data'>array([-7300070.989791, -7299839.333433, -7299607.677075, ..., -7200458.755737,\n",
+       "       -7200227.099379, -7199995.443021])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-f29237fa-3861-4a5d-8500-0ff6789a754c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f29237fa-3861-4a5d-8500-0ff6789a754c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb5275a2-4656-49ed-a25e-704e672c9a5f' class='xr-var-data-in' type='checkbox'><label for='data-fb5275a2-4656-49ed-a25e-704e672c9a5f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;unknown&quot;,GEOGCS[&quot;unknown&quot;,DATUM[&quot;unknown&quot;,SPHEROID[&quot;unknown&quot;,6371007.181,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]]],PROJECTION[&quot;Sinusoidal&quot;],PARAMETER[&quot;longitude_of_center&quot;,0],PARAMETER[&quot;false_easting&quot;,0],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6371007.181</dd><dt><span>semi_minor_axis :</span></dt><dd>6371007.181</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>unknown</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>unknown</dd><dt><span>horizontal_datum_name :</span></dt><dd>unknown</dd><dt><span>projected_crs_name :</span></dt><dd>unknown</dd><dt><span>grid_mapping_name :</span></dt><dd>sinusoidal</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;unknown&quot;,GEOGCS[&quot;unknown&quot;,DATUM[&quot;unknown&quot;,SPHEROID[&quot;unknown&quot;,6371007.181,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]]],PROJECTION[&quot;Sinusoidal&quot;],PARAMETER[&quot;longitude_of_center&quot;,0],PARAMETER[&quot;false_easting&quot;,0],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd></dl></div><pre class='xr-var-data'>array(0)</pre></li></ul></div></li><li class='xr-section-item'><input id='section-7ce240c2-00a3-4a53-9036-3de4bb94ffaa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7ce240c2-00a3-4a53-9036-3de4bb94ffaa' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>transform :</span></dt><dd>(231.65635826438665, 0.0, -7300186.817970253, 0.0, -231.65635826345533, 5060069.833558019)</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray (y: 303, x: 433)>\n",
+       "array([[nan, nan, nan, ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan],\n",
+       "       ...,\n",
+       "       [nan, nan, nan, ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)\n",
+       "Coordinates:\n",
+       "  * y            (y) float64 5.06e+06 5.06e+06 5.059e+06 ... 4.99e+06 4.99e+06\n",
+       "  * x            (x) float64 -7.3e+06 -7.3e+06 -7.3e+06 ... -7.2e+06 -7.2e+06\n",
+       "    spatial_ref  int64 0\n",
+       "Attributes:\n",
+       "    transform:     (231.65635826438665, 0.0, -7300186.817970253, 0.0, -231.65...\n",
+       "    grid_mapping:  spatial_ref"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "xdsc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f4416bd7910>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "xdsc.plot()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/history.rst b/docs/history.rst
index 892bdfbf..79c83bb4 100644
--- a/docs/history.rst
+++ b/docs/history.rst
@@ -3,9 +3,11 @@ History
 
 Latest
 -------
+- BUG: Remove unnecessary memory copies in reproject method (pull #136)
 - BUG: Fix order of axis in `rio.isel_window` (pull #133)
 - BUG: Allow clipping with disjoint geometries (issue #132)
 - BUG: Remove automatically setting tiled=True for windowed writing (pull #134)
+- ENH: Add `rio.pad_box` (pull #138)
 
 0.0.28
 -------
diff --git a/rioxarray/rioxarray.py b/rioxarray/rioxarray.py
index acabdd0d..e28eb92c 100644
--- a/rioxarray/rioxarray.py
+++ b/rioxarray/rioxarray.py
@@ -948,7 +948,7 @@ class RasterArray(XRasterBase):
             self.nodata if self.nodata is not None else dst_nodata
         )
         rasterio.warp.reproject(
-            source=np.copy(self._obj.load().data),
+            source=self._obj.values,
             destination=dst_data,
             src_transform=src_affine,
             src_crs=self.crs,
@@ -1051,6 +1051,118 @@ class RasterArray(XRasterBase):
         subset.attrs["transform"] = tuple(self.transform(recalc=True))
         return subset
 
+    def pad_xy(self, minx, miny, maxx, maxy, constant_values):
+        """Pad the array to x,y bounds.
+
+        .. versionadded:: 0.0.29
+
+        Parameters
+        ----------
+        minx: float
+            Minimum bound for x coordinate.
+        miny: float
+            Minimum bound for y coordinate.
+        maxx: float
+            Maximum bound for x coordinate.
+        maxy: float
+            Maximum bound for y coordinate.
+        constant_values: scalar
+            The value used for padding. If None, nodata will be used if it is
+            set, and np.nan otherwise.
+
+
+        Returns
+        -------
+        DataArray: A padded :class:`xarray.DataArray` object.
+
+        """
+        left, bottom, right, top = self._internal_bounds()
+        resolution_x, resolution_y = self.resolution()
+        y_before = y_after = 0
+        x_before = x_after = 0
+        y_coord = self._obj[self.y_dim]
+        x_coord = self._obj[self.x_dim]
+
+        if top - resolution_y < maxy:
+            new_y_coord = np.arange(bottom, maxy, -resolution_y)[::-1]
+            y_before = len(new_y_coord) - len(y_coord)
+            y_coord = new_y_coord
+            top = y_coord[0]
+        if bottom + resolution_y > miny:
+            new_y_coord = np.arange(top, miny, resolution_y)
+            y_after = len(new_y_coord) - len(y_coord)
+            y_coord = new_y_coord
+            bottom = y_coord[-1]
+
+        if left - resolution_x > minx:
+            new_x_coord = np.arange(right, minx, -resolution_x)[::-1]
+            x_before = len(new_x_coord) - len(x_coord)
+            x_coord = new_x_coord
+            left = x_coord[0]
+        if right + resolution_x < maxx:
+            new_x_coord = np.arange(left, maxx, resolution_x)
+            x_after = len(new_x_coord) - len(x_coord)
+            x_coord = new_x_coord
+            right = x_coord[-1]
+
+        if constant_values is None:
+            constant_values = (
+                self.encoded_nodata if self.encoded_nodata is not None else self.nodata
+            )
+        if constant_values is None:
+            constant_values = np.nan
+
+        superset = self._obj.pad(
+            pad_width={
+                self.x_dim: (x_before, x_after),
+                self.y_dim: (y_before, y_after),
+            },
+            constant_values=constant_values,
+        ).rio.set_spatial_dims(x_dim=self.x_dim, y_dim=self.y_dim, inplace=True)
+        superset[self.x_dim] = x_coord
+        superset[self.y_dim] = y_coord
+        superset.attrs["transform"] = tuple(superset.rio.transform(recalc=True))
+        return superset
+
+    def pad_box(self, minx, miny, maxx, maxy, constant_values=None):
+        """Pad the :class:`xarray.DataArray` to a bounding box
+
+        .. versionadded:: 0.0.29
+
+        Parameters
+        ----------
+        minx: float
+            Minimum bound for x coordinate.
+        miny: float
+            Minimum bound for y coordinate.
+        maxx: float
+            Maximum bound for x coordinate.
+        maxy: float
+            Maximum bound for y coordinate.
+        constant_values: scalar
+            The value used for padding. If None, nodata will be used if it is
+            set, and np.nan otherwise.
+
+
+        Returns
+        -------
+        DataArray: A padded :class:`xarray.DataArray` object.
+
+        """
+        resolution_x, resolution_y = self.resolution()
+
+        pad_minx = minx - abs(resolution_x) / 2.0
+        pad_miny = miny - abs(resolution_y) / 2.0
+        pad_maxx = maxx + abs(resolution_x) / 2.0
+        pad_maxy = maxy + abs(resolution_y) / 2.0
+
+        pd_array = self.pad_xy(pad_minx, pad_miny, pad_maxx, pad_maxy, constant_values)
+
+        # make sure correct attributes preserved & projection added
+        _add_attrs_proj(pd_array, self._obj)
+
+        return pd_array
+
     def clip_box(self, minx, miny, maxx, maxy, auto_expand=False, auto_expand_limit=3):
         """Clip the :class:`xarray.DataArray` by a bounding box.
 
@@ -1226,7 +1338,7 @@ class RasterArray(XRasterBase):
         :class:`numpy.ndarray`: An interpolated :class:`numpy.ndarray`.
 
         """
-        src_data_flat = np.copy(src_data).flatten()
+        src_data_flat = src_data.flatten()
         try:
             data_isnan = np.isnan(self.nodata)
         except TypeError:
@@ -1507,6 +1619,39 @@ class RasterDataset(XRasterBase):
             x_dim=self.x_dim, y_dim=self.y_dim, inplace=True
         )
 
+    def pad_box(self, minx, miny, maxx, maxy):
+        """Pad the :class:`xarray.Dataset` to a bounding box.
+
+        .. warning:: Only works if all variables in the dataset have the
+                     same coordinates.
+
+        Parameters
+        ----------
+        minx: float
+            Minimum bound for x coordinate.
+        miny: float
+            Minimum bound for y coordinate.
+        maxx: float
+            Maximum bound for x coordinate.
+        maxy: float
+            Maximum bound for y coordinate.
+
+        Returns
+        -------
+        DataArray: A padded :class:`xarray.Dataset` object.
+
+        """
+        padded_dataset = xarray.Dataset(attrs=self._obj.attrs)
+        for var in self.vars:
+            padded_dataset[var] = (
+                self._obj[var]
+                .rio.set_spatial_dims(x_dim=self.x_dim, y_dim=self.y_dim, inplace=True)
+                .rio.pad_box(minx, miny, maxx, maxy,)
+            )
+        return padded_dataset.rio.set_spatial_dims(
+            x_dim=self.x_dim, y_dim=self.y_dim, inplace=True
+        )
+
     def clip_box(self, minx, miny, maxx, maxy, auto_expand=False, auto_expand_limit=3):
         """Clip the :class:`xarray.Dataset` by a bounding box.
 


Test patch:
diff --git a/test/integration/test_integration_rioxarray.py b/test/integration/test_integration_rioxarray.py
index 76c35847..bb2ce5c9 100644
--- a/test/integration/test_integration_rioxarray.py
+++ b/test/integration/test_integration_rioxarray.py
@@ -157,6 +157,44 @@ def modis_clip(request, tmpdir):
     )
 
 
+def test_pad_box(modis_clip):
+    with modis_clip["open"](modis_clip["input"]) as xdi:
+        # first, clip
+        clipped_ds = xdi.rio.clip_box(
+            minx=xdi.x[4].values,
+            miny=xdi.y[6].values,
+            maxx=xdi.x[6].values,
+            maxy=xdi.y[4].values,
+        )
+        # then, extend back to original
+        padded_ds = clipped_ds.rio.pad_box(
+            minx=xdi.x[0].values,
+            miny=xdi.y[-1].values,
+            maxx=xdi.x[-1].values,
+            maxy=xdi.y[0].values,
+        )
+        # finally, clip again
+        clipped_ds2 = padded_ds.rio.clip_box(
+            minx=xdi.x[4].values,
+            miny=xdi.y[6].values,
+            maxx=xdi.x[6].values,
+            maxy=xdi.y[4].values,
+        )
+        _assert_xarrays_equal(clipped_ds, clipped_ds2)
+        # padded data should have the same size as original data
+        if hasattr(xdi, "variables"):
+            for var in xdi.rio.vars:
+                for padded_size, original_size in zip(
+                    padded_ds[var].shape, xdi[var].shape
+                ):
+                    assert padded_size == original_size
+        else:
+            for padded_size, original_size in zip(padded_ds.shape, xdi.shape):
+                assert padded_size == original_size
+        # make sure it safely writes to netcdf
+        padded_ds.to_netcdf(modis_clip["output"])
+
+
 def test_clip_box(modis_clip):
     with modis_clip["open"](modis_clip["input"]) as xdi, modis_clip["open"](
         modis_clip["compare"]