Repository: ACCESS-Cloud-Based-InSAR/dem-stitcher (language: python)

Issue:
Removal of `2021` from AWS Glo Registry
### The bug
The example on the github homepage does not work due to removal of `2021` prefix in glo-30 aws bucket.

### To Reproduce
```
bounds = [-119.085, 33.402, -118.984, 35.435]
X, p = stitch_dem(bounds,
                  dem_name='glo_30',
                  dst_ellipsoidal_height=False,
                  dst_area_or_point='Point')
```

```
---------------------------------------------------------------------------
CPLE_HttpResponseError                    Traceback (most recent call last)
File rasterio/_base.pyx:261, in rasterio._base.DatasetBase.__init__()

File rasterio/_shim.pyx:78, in rasterio._shim.open_dataset()

File rasterio/_err.pyx:216, in rasterio._err.exc_wrap_pointer()

CPLE_HttpResponseError: HTTP response code: 404

During handling of the above exception, another exception occurred:

RasterioIOError                           Traceback (most recent call last)
Input In [22], in <cell line: 2>()
      1 bounds = [-119.085, 33.402, -118.984, 35.435]
----> 2 X, p = stitch_dem(bounds,
      3                   dem_name='glo_30',
      4                   dst_ellipsoidal_height=False,
      5                   dst_area_or_point='Point')

File ~/opt/anaconda3/envs/dem-stitcher/lib/python3.9/site-packages/dem_stitcher/stitcher.py:304, in stitch_dem(bounds, dem_name, dst_ellipsoidal_height, dst_area_or_point, dst_resolution, n_threads_reproj, n_threads_downloading, driver, fill_in_glo_30)
    302     return RASTER_READERS[dem_name](url)
    303 with ThreadPoolExecutor(max_workers=n_threads_downloading) as executor:
--> 304     results = list(tqdm(executor.map(reader, urls),
    305                         total=len(urls),
    306                         desc=f'Reading {dem_name} Datasets'))
    308 # If datasets are non-existent, returns None
    309 datasets = list(filter(lambda x: x is not None, results))

File ~/opt/anaconda3/envs/dem-stitcher/lib/python3.9/site-packages/tqdm/std.py:1195, in tqdm.__iter__(self)
   1192 time = self._time
   1194 try:
-> 1195     for obj in iterable:
   1196         yield obj
   1197         # Update and possibly print the progressbar.
   1198         # Note: does not call self.update(1) for speed optimisation.

File ~/opt/anaconda3/envs/dem-stitcher/lib/python3.9/concurrent/futures/_base.py:609, in Executor.map.<locals>.result_iterator()
    606 while fs:
    607     # Careful not to keep a reference to the popped future
    608     if timeout is None:
--> 609         yield fs.pop().result()
    610     else:
    611         yield fs.pop().result(end_time - time.monotonic())

File ~/opt/anaconda3/envs/dem-stitcher/lib/python3.9/concurrent/futures/_base.py:446, in Future.result(self, timeout)
    444     raise CancelledError()
    445 elif self._state == FINISHED:
--> 446     return self.__get_result()
    447 else:
    448     raise TimeoutError()

File ~/opt/anaconda3/envs/dem-stitcher/lib/python3.9/concurrent/futures/_base.py:391, in Future.__get_result(self)
    389 if self._exception:
    390     try:
--> 391         raise self._exception
    392     finally:
    393         # Break a reference cycle with the exception in self._exception
    394         self = None

File ~/opt/anaconda3/envs/dem-stitcher/lib/python3.9/concurrent/futures/thread.py:58, in _WorkItem.run(self)
     55     return
     57 try:
---> 58     result = self.fn(*self.args, **self.kwargs)
     59 except BaseException as exc:
     60     self.future.set_exception(exc)

File ~/opt/anaconda3/envs/dem-stitcher/lib/python3.9/site-packages/dem_stitcher/stitcher.py:302, in stitch_dem.<locals>.reader(url)
    301 def reader(url):
--> 302     return RASTER_READERS[dem_name](url)

File ~/opt/anaconda3/envs/dem-stitcher/lib/python3.9/site-packages/dem_stitcher/dem_readers.py:12, in read_dem(dem_path)
     11 def read_dem(dem_path: str) -> rasterio.DatasetReader:
---> 12     ds = rasterio.open(dem_path)
     13     return ds

File ~/opt/anaconda3/envs/dem-stitcher/lib/python3.9/site-packages/rasterio/env.py:437, in ensure_env_with_credentials.<locals>.wrapper(*args, **kwds)
    434     session = DummySession()
    436 with env_ctor(session=session):
--> 437     return f(*args, **kwds)

File ~/opt/anaconda3/envs/dem-stitcher/lib/python3.9/site-packages/rasterio/__init__.py:220, in open(fp, mode, driver, width, height, count, crs, transform, dtype, nodata, sharing, **kwargs)
    216 # Create dataset instances and pass the given env, which will
    217 # be taken over by the dataset's context manager if it is not
    218 # None.
    219 if mode == 'r':
--> 220     s = DatasetReader(path, driver=driver, sharing=sharing, **kwargs)
    221 elif mode == "r+":
    222     s = get_writer_for_path(path, driver=driver)(
    223         path, mode, driver=driver, sharing=sharing, **kwargs
    224     )

File rasterio/_base.pyx:263, in rasterio._base.DatasetBase.__init__()

RasterioIOError: HTTP response code: 404
```



Discussion / hints:

Fix patch:
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 3322832..cf28283 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -6,6 +6,14 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [PEP 440](https://www.python.org/dev/peps/pep-0440/)
 and uses [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [2.3.1]
+
+### Fixed
+- Fixed tile urls for `glo*` and `srtm_v3`.
+- Include directions in readme for future dem tile updates.
+- Support python 3.11
+
+
 ## [2.3.0]
 
 ### Added
diff --git a/README.md b/README.md
index d378408..a180935 100644
--- a/README.md
+++ b/README.md
@@ -54,7 +54,7 @@ Currently, python 3.7+ is supported.
 
 ## With ISCE2 or gdal
 
-Although the thrust of using this package is for staging DEMs for InSAR, testing and maintaining suitable environments to use with InSAR processors (particularly ISCE2) is beyond the scope of what we are attempting to accomplish here. We provide an example notebook [here](./notebooks/Staging_a_DEM_for_ISCE2.ipynb) that demonstrates how to stage a DEM for ISCE2, which requires additional packages than required for the package on its own. For the notebook, we use the environment found in `environment.yml` of the Dockerized TopsApp [repository](https://github.com/ACCESS-Cloud-Based-InSAR/DockerizedTopsApp/blob/dev/environment.yml), used to generate interferograms (GUNWs) in the cloud.
+Although the thrust of using this package is for staging DEMs for InSAR (particularly ISCE2), testing and maintaining suitable environments to use with InSAR processors is beyond the scope of what we are attempting to accomplish here. We provide an example notebook [here](./notebooks/Staging_a_DEM_for_ISCE2.ipynb) that demonstrates how to stage a DEM for ISCE2, which requires additional packages than required for the package on its own and additionally requires python version `<3.10`. For the notebook, we use the environment found in `environment.yml` of the Dockerized TopsApp [repository](https://github.com/ACCESS-Cloud-Based-InSAR/DockerizedTopsApp/blob/dev/environment.yml), used to generate interferograms (GUNWs) in the cloud.
 
 ## Credentials
 
@@ -67,10 +67,6 @@ machine urs.earthdata.nasa.gov
     password <password>
 ```
 
-## Using with ISCE2 or gdal
-
-Although the thrust of using this package is for staging DEMs for InSAR, testing and maintaining suitable environments to use with InSAR processors (particularly ISCE2) is beyond the scope of what we are attempting to accomplish here. We provide an example notebook [here](./notebooks/Staging_a_DEM_for_ISCE2.ipynb) that demonstrates how to stage a DEM for ISCE2, which requires additional packages than required for the package on its own. For the notebook, we use the environment found in `environment.yml` of the Dockerized TopsApp [repository](https://github.com/ACCESS-Cloud-Based-InSAR/DockerizedTopsApp/blob/dev/environment.yml), used to generate interferograms (GUNWs) in the cloud.
-
 # Notebooks
 
 We have notebooks to demonstrate common usage:
@@ -98,6 +94,8 @@ Out[1]: ['srtm_v3', 'nasadem', 'glo_90_missing', 'glo_30', '3dep', 'glo_90', 'ne
 4. `nasadem`: Nasadem [[link](https://lpdaac.usgs.gov/products/nasadem_hgtv001/)]
 5. `glo_90_missing`: these are tiles that are in `glo_90` but not in `glo_30`. They are over the countries Armenia and Azerbaijan. Used internally to help fill in gaps in coverage of `glo_30`.
 
+If there are issues with obtaining dem tiles from urls embedded within the geojson tiles (e.g. a `404` error as [here](https://github.com/ACCESS-Cloud-Based-InSAR/dem-stitcher/issues/48)), please see the [Development](#for-development) section below and/or open an issue ticket.
+
 # DEM Transformations
 
 Wherever possible, we do not resample the original DEMs unless specified by the user to do so. When extents are specified, we obtain the the minimum  pixel extent within the merged tile DEMs that contain that extent. Any required resampling (e.g. updating the CRS or updating the resolution because the tiles have non-square resolution at high latitudes) is done after these required translations. We importantly note that order in which these transformations are done is crucial, i.e. first translating the DEM (to either pixel- or area-center coordinates) and then resampling is different than first resampling and then translation (as affine transformations are not commutative). Here are some notes/discussions:
@@ -126,6 +124,15 @@ This is almost identical to normal installation:
 3. Create a new environment and install requirements using `conda env update --file environment.yml` (or use [`mamba`](https://github.com/mamba-org/mamba) to speed the install up)
 4. Install the package from cloned repo using `python -m pip install -e .`
 
+## DEM Urls
+
+If urls or readers need to be updated (they consistently do) or you want to add a new global or large DEM, then there are two points of contact:
+
+1. The notebooks that format the geojsons used for this library are [here](notebooks/organize_tile_data/)
+2. The readers are [here](dem_stitcher/dem_readers.py)
+
+The former is the more likely. When re-generating tiles, make sure to run all tests including integration tests (i.e. `pytest tests`). For example, if regenerating `glo` tiles, `glo-30` requires both resolution parameters (30 meters and 90 meters) and an additional notebook for filling in missing 30 meter tiles. These should be clearly spelled out in the notebook linked above.
+
 # Testing
 
 1. Install `pytest`
diff --git a/dem_stitcher/data/glo_30.geojson.zip b/dem_stitcher/data/glo_30.geojson.zip
index 554b6b7..8093c68 100644
Binary files a/dem_stitcher/data/glo_30.geojson.zip and b/dem_stitcher/data/glo_30.geojson.zip differ
diff --git a/dem_stitcher/data/glo_90.geojson.zip b/dem_stitcher/data/glo_90.geojson.zip
index e4af9c1..c909f45 100644
Binary files a/dem_stitcher/data/glo_90.geojson.zip and b/dem_stitcher/data/glo_90.geojson.zip differ
diff --git a/dem_stitcher/data/glo_90_missing.geojson.zip b/dem_stitcher/data/glo_90_missing.geojson.zip
index dbef017..d114e0a 100644
Binary files a/dem_stitcher/data/glo_90_missing.geojson.zip and b/dem_stitcher/data/glo_90_missing.geojson.zip differ
diff --git a/dem_stitcher/data/srtm_v3.geojson.zip b/dem_stitcher/data/srtm_v3.geojson.zip
index b00f3e3..8839d26 100644
Binary files a/dem_stitcher/data/srtm_v3.geojson.zip and b/dem_stitcher/data/srtm_v3.geojson.zip differ
diff --git a/dem_stitcher/geoid.py b/dem_stitcher/geoid.py
index 2a1ed2a..3ae449f 100644
--- a/dem_stitcher/geoid.py
+++ b/dem_stitcher/geoid.py
@@ -55,7 +55,7 @@ def remove_geoid(dem_arr: np.ndarray,
                  dem_area_or_point: str = 'Area',
                  res_buffer: int = 2) -> np.ndarray:
 
-    assert(dem_area_or_point in ['Point', 'Area'])
+    assert dem_area_or_point in ['Point', 'Area']
 
     extent = array_bounds(dem_profile['height'],
                           dem_profile['width'],
diff --git a/dem_stitcher/stitcher.py b/dem_stitcher/stitcher.py
index 676ce1d..2762674 100644
--- a/dem_stitcher/stitcher.py
+++ b/dem_stitcher/stitcher.py
@@ -153,8 +153,8 @@ def merge_tiles(datasets: List[rasterio.DatasetReader],
 def shift_profile_for_pixel_loc(src_profile: dict,
                                 src_area_or_point: str,
                                 dst_area_or_point: str) -> dict:
-    assert(dst_area_or_point in ['Area', 'Point'])
-    assert(src_area_or_point in ['Area', 'Point'])
+    assert dst_area_or_point in ['Area', 'Point']
+    assert src_area_or_point in ['Area', 'Point']
     if dst_area_or_point == 'Point' and src_area_or_point == 'Area':
         shift = -.5
         profile_shifted = translate_profile(src_profile, shift, shift)
@@ -210,7 +210,7 @@ def merge_and_transform_dem_tiles(datasets: list,
         dem_arr = dem_arr[0, ...]
 
     # Ensure dem_arr has correct shape
-    assert(len(dem_arr.shape) == 2)
+    assert len(dem_arr.shape) == 2
 
     return dem_arr, dem_profile
 
diff --git a/notebooks/organize_tile_data/0_Format_and_Organize_Data.ipynb b/notebooks/organize_tile_data/0_Format_and_Organize_Data.ipynb
index 89fef6c..33f89b3 100644
--- a/notebooks/organize_tile_data/0_Format_and_Organize_Data.ipynb
+++ b/notebooks/organize_tile_data/0_Format_and_Organize_Data.ipynb
@@ -3,11 +3,11 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "external-chick",
+   "id": "d1972396",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-10T01:01:11.398263Z",
-     "start_time": "2022-06-10T01:01:08.226409Z"
+     "end_time": "2022-11-21T22:34:18.292579Z",
+     "start_time": "2022-11-21T22:34:17.044944Z"
     }
    },
    "outputs": [],
@@ -34,11 +34,11 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "western-carroll",
+   "id": "e0138588",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-10T01:01:11.403538Z",
-     "start_time": "2022-06-10T01:01:11.400848Z"
+     "end_time": "2022-11-21T22:34:18.297569Z",
+     "start_time": "2022-11-21T22:34:18.294972Z"
     }
    },
    "outputs": [],
@@ -49,7 +49,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "overall-harris",
+   "id": "0d352eda",
    "metadata": {},
    "source": [
     "# SRTM\n",
@@ -60,11 +60,11 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "patent-inflation",
+   "id": "71674531",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-02T00:08:05.537149Z",
-     "start_time": "2022-06-02T00:08:02.884778Z"
+     "end_time": "2022-11-21T22:34:20.786966Z",
+     "start_time": "2022-11-21T22:34:18.301674Z"
     }
    },
    "outputs": [
@@ -145,11 +145,11 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "compact-concept",
+   "id": "a5bf14db",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-02T00:08:05.557136Z",
-     "start_time": "2022-06-02T00:08:05.539186Z"
+     "end_time": "2022-11-21T22:34:20.813394Z",
+     "start_time": "2022-11-21T22:34:20.789929Z"
     }
    },
    "outputs": [
@@ -183,31 +183,31 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>N00E006</td>\n",
-       "      <td>http://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.00...</td>\n",
+       "      <td>https://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.0...</td>\n",
        "      <td>POLYGON ((6.00000 0.00000, 6.00000 1.00000, 7....</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>N00E009</td>\n",
-       "      <td>http://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.00...</td>\n",
+       "      <td>https://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.0...</td>\n",
        "      <td>POLYGON ((9.00000 0.00000, 9.00000 1.00000, 10...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>N00E010</td>\n",
-       "      <td>http://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.00...</td>\n",
+       "      <td>https://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.0...</td>\n",
        "      <td>POLYGON ((10.00000 0.00000, 10.00000 1.00000, ...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>N00E011</td>\n",
-       "      <td>http://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.00...</td>\n",
+       "      <td>https://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.0...</td>\n",
        "      <td>POLYGON ((11.00000 0.00000, 11.00000 1.00000, ...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>N00E012</td>\n",
-       "      <td>http://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.00...</td>\n",
+       "      <td>https://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.0...</td>\n",
        "      <td>POLYGON ((12.00000 0.00000, 12.00000 1.00000, ...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
@@ -216,11 +216,11 @@
       ],
       "text/plain": [
        "   tile_id                                                url  \\\n",
-       "0  N00E006  http://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.00...   \n",
-       "1  N00E009  http://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.00...   \n",
-       "2  N00E010  http://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.00...   \n",
-       "3  N00E011  http://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.00...   \n",
-       "4  N00E012  http://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.00...   \n",
+       "0  N00E006  https://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.0...   \n",
+       "1  N00E009  https://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.0...   \n",
+       "2  N00E010  https://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.0...   \n",
+       "3  N00E011  https://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.0...   \n",
+       "4  N00E012  https://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.0...   \n",
        "\n",
        "                                            geometry  \n",
        "0  POLYGON ((6.00000 0.00000, 6.00000 1.00000, 7....  \n",
@@ -240,17 +240,18 @@
     "df_srtm.rename(columns={'id': 'tile_id'}, inplace=True)\n",
     "df_srtm['url'] = df_srtm['tile_id'].map(lambda tile_id: f'http://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.003/2000.02.11/{tile_id}.SRTMGL1.hgt.zip')\n",
     "df_srtm = df_srtm[['tile_id', 'url', 'geometry']].copy()\n",
+    "df_srtm.url = df_srtm.url.map(lambda url: url.replace('http://', 'https://'))\n",
     "df_srtm.head()"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "straight-spending",
+   "id": "943ca4bf",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-02T00:08:06.677700Z",
-     "start_time": "2022-06-02T00:08:05.558917Z"
+     "end_time": "2022-11-21T22:34:21.838276Z",
+     "start_time": "2022-11-21T22:34:20.815102Z"
     }
    },
    "outputs": [
@@ -272,11 +273,11 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "extraordinary-scholar",
+   "id": "9d621645",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-02T00:08:11.162882Z",
-     "start_time": "2022-06-02T00:08:06.680454Z"
+     "end_time": "2022-11-21T22:34:25.686067Z",
+     "start_time": "2022-11-21T22:34:21.840098Z"
     }
    },
    "outputs": [],
@@ -289,18 +290,18 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "coastal-saver",
+   "id": "151599ea",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-02T00:08:11.751225Z",
-     "start_time": "2022-06-02T00:08:11.164982Z"
+     "end_time": "2022-11-21T22:34:26.272275Z",
+     "start_time": "2022-11-21T22:34:25.687784Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x1c7405c30>"
+       "<matplotlib.image.AxesImage at 0x1c3747100>"
       ]
      },
      "execution_count": 7,
@@ -326,7 +327,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "thorough-sentence",
+   "id": "daa02c5e",
    "metadata": {},
    "source": [
     "# NASADEM"
@@ -334,12 +335,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "id": "large-surge",
+   "execution_count": 8,
+   "id": "3824ea86",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-02-02T21:27:39.732405Z",
-     "start_time": "2022-02-02T21:27:39.718329Z"
+     "end_time": "2022-11-21T22:34:26.289353Z",
+     "start_time": "2022-11-21T22:34:26.274039Z"
     }
    },
    "outputs": [
@@ -420,7 +421,7 @@
        "4  POLYGON ((12.00000 0.00000, 12.00000 1.00000, ...  "
       ]
      },
-     "execution_count": 9,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -434,12 +435,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "id": "iraqi-anderson",
+   "execution_count": 9,
+   "id": "1511de1c",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-02-02T21:28:26.060249Z",
-     "start_time": "2022-02-02T21:27:39.734133Z"
+     "end_time": "2022-11-21T22:34:30.168067Z",
+     "start_time": "2022-11-21T22:34:26.293603Z"
     }
    },
    "outputs": [],
@@ -451,28 +452,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "id": "disturbed-occasions",
+   "execution_count": 10,
+   "id": "2d4202d9",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-02-02T21:28:26.632017Z",
-     "start_time": "2022-02-02T21:28:26.061984Z"
+     "end_time": "2022-11-21T22:34:30.708053Z",
+     "start_time": "2022-11-21T22:34:30.169965Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x1ce0dc670>"
+       "<matplotlib.image.AxesImage at 0x1c3b5f610>"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -489,12 +490,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "id": "amended-model",
+   "execution_count": 11,
+   "id": "59cf62ab",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-02-02T21:28:27.732435Z",
-     "start_time": "2022-02-02T21:28:26.633688Z"
+     "end_time": "2022-11-21T22:34:31.838325Z",
+     "start_time": "2022-11-21T22:34:30.709803Z"
     }
    },
    "outputs": [
@@ -504,7 +505,7 @@
        "PosixPath('data/nasadem.geojson.zip')"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -515,7 +516,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "da2a1697",
+   "id": "b0a620b9",
    "metadata": {},
    "source": [
     "# GLO\n",
@@ -525,18 +526,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "id": "601da129",
+   "execution_count": 4,
+   "id": "08d2f103",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-10T01:24:05.123476Z",
-     "start_time": "2022-06-10T01:24:05.120683Z"
+     "end_time": "2022-11-21T18:48:48.435806Z",
+     "start_time": "2022-11-21T18:48:48.433196Z"
     }
    },
    "outputs": [],
    "source": [
-    "# Can update when new year is available\n",
-    "YEAR = '2021'\n",
+    "## Can update when new year is available\n",
+    "# YEAR = '2021'\n",
+    "## Currently Only 1 year is available\n",
     "\n",
     "# Change resolution to 30 or 90\n",
     "RES = 90\n",
@@ -546,46 +548,46 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "id": "central-retail",
+   "execution_count": 5,
+   "id": "09b7e303",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-10T01:24:10.968960Z",
-     "start_time": "2022-06-10T01:24:05.335661Z"
+     "end_time": "2022-11-21T18:48:51.475795Z",
+     "start_time": "2022-11-21T18:48:49.305809Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[{'Key': '2021/Copernicus_DSM_COG_30_N00_00_E006_00_DEM/AUXFILES/Copernicus_DSM_30_N00_00_E006_00_ACM.kml',\n",
-       "  'LastModified': datetime.datetime(2022, 4, 4, 19, 3, 58, tzinfo=tzutc()),\n",
+       "[{'Key': 'Copernicus_DSM_COG_30_N00_00_E006_00_DEM/AUXFILES/Copernicus_DSM_30_N00_00_E006_00_ACM.kml',\n",
+       "  'LastModified': datetime.datetime(2022, 5, 9, 12, 43, 24, tzinfo=tzutc()),\n",
        "  'ETag': '\"8fad074b0c6d0c80716f694674b90a1e\"',\n",
        "  'Size': 732,\n",
        "  'StorageClass': 'STANDARD'},\n",
-       " {'Key': '2021/Copernicus_DSM_COG_30_N00_00_E006_00_DEM/AUXFILES/Copernicus_DSM_COG_30_N00_00_E006_00_EDM.tif',\n",
-       "  'LastModified': datetime.datetime(2022, 4, 4, 19, 3, 57, tzinfo=tzutc()),\n",
+       " {'Key': 'Copernicus_DSM_COG_30_N00_00_E006_00_DEM/AUXFILES/Copernicus_DSM_COG_30_N00_00_E006_00_EDM.tif',\n",
+       "  'LastModified': datetime.datetime(2022, 5, 9, 12, 43, 24, tzinfo=tzutc()),\n",
        "  'ETag': '\"6b9d5ae5591a9ad5b5da334bbe9cf45e\"',\n",
        "  'Size': 50244,\n",
        "  'StorageClass': 'STANDARD'},\n",
-       " {'Key': '2021/Copernicus_DSM_COG_30_N00_00_E006_00_DEM/AUXFILES/Copernicus_DSM_COG_30_N00_00_E006_00_FLM.tif',\n",
-       "  'LastModified': datetime.datetime(2022, 4, 4, 19, 3, 54, tzinfo=tzutc()),\n",
+       " {'Key': 'Copernicus_DSM_COG_30_N00_00_E006_00_DEM/AUXFILES/Copernicus_DSM_COG_30_N00_00_E006_00_FLM.tif',\n",
+       "  'LastModified': datetime.datetime(2022, 5, 9, 12, 43, 24, tzinfo=tzutc()),\n",
        "  'ETag': '\"d34a617f3c36dde49e998546e2ad423d\"',\n",
        "  'Size': 53031,\n",
        "  'StorageClass': 'STANDARD'},\n",
-       " {'Key': '2021/Copernicus_DSM_COG_30_N00_00_E006_00_DEM/AUXFILES/Copernicus_DSM_COG_30_N00_00_E006_00_HEM.tif',\n",
-       "  'LastModified': datetime.datetime(2022, 4, 4, 19, 3, 56, tzinfo=tzutc()),\n",
+       " {'Key': 'Copernicus_DSM_COG_30_N00_00_E006_00_DEM/AUXFILES/Copernicus_DSM_COG_30_N00_00_E006_00_HEM.tif',\n",
+       "  'LastModified': datetime.datetime(2022, 5, 9, 12, 43, 24, tzinfo=tzutc()),\n",
        "  'ETag': '\"5413c19eec8f19605d579230b83a0f78\"',\n",
        "  'Size': 483015,\n",
        "  'StorageClass': 'STANDARD'},\n",
-       " {'Key': '2021/Copernicus_DSM_COG_30_N00_00_E006_00_DEM/AUXFILES/Copernicus_DSM_COG_30_N00_00_E006_00_WBM.tif',\n",
-       "  'LastModified': datetime.datetime(2022, 4, 4, 19, 3, 57, tzinfo=tzutc()),\n",
+       " {'Key': 'Copernicus_DSM_COG_30_N00_00_E006_00_DEM/AUXFILES/Copernicus_DSM_COG_30_N00_00_E006_00_WBM.tif',\n",
+       "  'LastModified': datetime.datetime(2022, 5, 9, 12, 43, 24, tzinfo=tzutc()),\n",
        "  'ETag': '\"17e0cde30aabb19fbfd9c38dd2924ea0\"',\n",
        "  'Size': 27621,\n",
        "  'StorageClass': 'STANDARD'}]"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -593,37 +595,34 @@
    "source": [
     "s3client = boto3.client('s3')\n",
     "BUCKET_NAME = f'copernicus-dem-{RES}m'\n",
-    "objects = s3client.list_objects(Bucket=BUCKET_NAME, \n",
-    "                                # Change this for previous years\n",
-    "                                Prefix=YEAR)\n",
+    "objects = s3client.list_objects(Bucket=BUCKET_NAME)\n",
     "objects['Contents'][:5]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
-   "id": "c450d2ae",
+   "execution_count": 7,
+   "id": "2be847ff",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-10T01:24:10.976109Z",
-     "start_time": "2022-06-10T01:24:10.971493Z"
+     "end_time": "2022-11-21T18:48:58.299909Z",
+     "start_time": "2022-11-21T18:48:58.297461Z"
     }
    },
    "outputs": [],
    "source": [
     "paginator = s3client.get_paginator('list_objects_v2')\n",
-    "pages = paginator.paginate(Bucket=BUCKET_NAME, \n",
-    "                           Prefix='2021')"
+    "pages = paginator.paginate(Bucket=BUCKET_NAME)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "id": "6a899284",
+   "execution_count": 8,
+   "id": "c1bfb903",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-10T01:27:44.428238Z",
-     "start_time": "2022-06-10T01:24:10.978116Z"
+     "end_time": "2022-11-21T18:51:49.915475Z",
+     "start_time": "2022-11-21T18:48:59.089467Z"
     }
    },
    "outputs": [
@@ -631,20 +630,20 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "424it [03:33,  1.99it/s]\n"
+      "424it [02:50,  2.48it/s]\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "{'Key': '2021/Copernicus_DSM_COG_30_N00_00_E006_00_DEM/AUXFILES/Copernicus_DSM_30_N00_00_E006_00_ACM.kml',\n",
-       " 'LastModified': datetime.datetime(2022, 4, 4, 19, 3, 58, tzinfo=tzutc()),\n",
+       "{'Key': 'Copernicus_DSM_COG_30_N00_00_E006_00_DEM/AUXFILES/Copernicus_DSM_30_N00_00_E006_00_ACM.kml',\n",
+       " 'LastModified': datetime.datetime(2022, 5, 9, 12, 43, 24, tzinfo=tzutc()),\n",
        " 'ETag': '\"8fad074b0c6d0c80716f694674b90a1e\"',\n",
        " 'Size': 732,\n",
        " 'StorageClass': 'STANDARD'}"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -659,36 +658,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
-   "id": "fcf64c32",
+   "execution_count": 9,
+   "id": "45895ac7",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-10T01:27:44.628225Z",
-     "start_time": "2022-06-10T01:27:44.431478Z"
+     "end_time": "2022-11-21T18:51:50.081428Z",
+     "start_time": "2022-11-21T18:51:49.917879Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[{'Key': '2021/Copernicus_DSM_COG_30_N00_00_E006_00_DEM/Copernicus_DSM_COG_30_N00_00_E006_00_DEM.tif',\n",
-       "  'LastModified': datetime.datetime(2022, 4, 4, 19, 3, 59, tzinfo=tzutc()),\n",
+       "[{'Key': 'Copernicus_DSM_COG_30_N00_00_E006_00_DEM/Copernicus_DSM_COG_30_N00_00_E006_00_DEM.tif',\n",
+       "  'LastModified': datetime.datetime(2022, 5, 9, 12, 43, 24, tzinfo=tzutc()),\n",
        "  'ETag': '\"0c3f5310131359cfa2dfb028bf3510fd\"',\n",
        "  'Size': 490119,\n",
        "  'StorageClass': 'STANDARD'},\n",
-       " {'Key': '2021/Copernicus_DSM_COG_30_N00_00_E009_00_DEM/Copernicus_DSM_COG_30_N00_00_E009_00_DEM.tif',\n",
-       "  'LastModified': datetime.datetime(2022, 4, 4, 21, 52, 36, tzinfo=tzutc()),\n",
+       " {'Key': 'Copernicus_DSM_COG_30_N00_00_E009_00_DEM/Copernicus_DSM_COG_30_N00_00_E009_00_DEM.tif',\n",
+       "  'LastModified': datetime.datetime(2022, 5, 9, 12, 43, 24, tzinfo=tzutc()),\n",
        "  'ETag': '\"4a63321e22c176df173951a67c79580a\"',\n",
        "  'Size': 3210718,\n",
        "  'StorageClass': 'STANDARD'},\n",
-       " {'Key': '2021/Copernicus_DSM_COG_30_N00_00_E010_00_DEM/Copernicus_DSM_COG_30_N00_00_E010_00_DEM.tif',\n",
-       "  'LastModified': datetime.datetime(2022, 4, 5, 1, 52, 6, tzinfo=tzutc()),\n",
+       " {'Key': 'Copernicus_DSM_COG_30_N00_00_E010_00_DEM/Copernicus_DSM_COG_30_N00_00_E010_00_DEM.tif',\n",
+       "  'LastModified': datetime.datetime(2022, 5, 9, 12, 43, 24, tzinfo=tzutc()),\n",
        "  'ETag': '\"c577e54674b6ae8abd4b246a25a52936\"',\n",
        "  'Size': 5763057,\n",
        "  'StorageClass': 'STANDARD'}]"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -701,12 +700,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "id": "b1c702c0",
+   "execution_count": 10,
+   "id": "58b19de1",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-10T01:27:44.634213Z",
-     "start_time": "2022-06-10T01:27:44.630586Z"
+     "end_time": "2022-11-21T18:51:50.086422Z",
+     "start_time": "2022-11-21T18:51:50.083020Z"
     }
    },
    "outputs": [
@@ -716,7 +715,7 @@
        "26475"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -727,12 +726,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
-   "id": "755f47d2",
+   "execution_count": 11,
+   "id": "d2da92b5",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-10T01:27:44.642662Z",
-     "start_time": "2022-06-10T01:27:44.636194Z"
+     "end_time": "2022-11-21T18:51:50.095383Z",
+     "start_time": "2022-11-21T18:51:50.089091Z"
     }
    },
    "outputs": [],
@@ -770,12 +769,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "id": "2fcb3e1d",
+   "execution_count": 12,
+   "id": "5726bcb0",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-10T01:27:45.127351Z",
-     "start_time": "2022-06-10T01:27:44.644397Z"
+     "end_time": "2022-11-21T18:51:50.427176Z",
+     "start_time": "2022-11-21T18:51:50.097200Z"
     }
    },
    "outputs": [
@@ -809,31 +808,31 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>Copernicus_DSM_COG_30_N00_00_E006_00_DEM</td>\n",
-       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/20...</td>\n",
+       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/Co...</td>\n",
        "      <td>POLYGON ((7.00000 0.00000, 7.00000 1.00000, 6....</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>Copernicus_DSM_COG_30_N00_00_E009_00_DEM</td>\n",
-       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/20...</td>\n",
+       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/Co...</td>\n",
        "      <td>POLYGON ((10.00000 0.00000, 10.00000 1.00000, ...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>Copernicus_DSM_COG_30_N00_00_E010_00_DEM</td>\n",
-       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/20...</td>\n",
+       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/Co...</td>\n",
        "      <td>POLYGON ((11.00000 0.00000, 11.00000 1.00000, ...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>Copernicus_DSM_COG_30_N00_00_E011_00_DEM</td>\n",
-       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/20...</td>\n",
+       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/Co...</td>\n",
        "      <td>POLYGON ((12.00000 0.00000, 12.00000 1.00000, ...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>Copernicus_DSM_COG_30_N00_00_E012_00_DEM</td>\n",
-       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/20...</td>\n",
+       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/Co...</td>\n",
        "      <td>POLYGON ((13.00000 0.00000, 13.00000 1.00000, ...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
@@ -849,11 +848,11 @@
        "4  Copernicus_DSM_COG_30_N00_00_E012_00_DEM   \n",
        "\n",
        "                                                 url  \\\n",
-       "0  https://copernicus-dem-90m.s3.amazonaws.com/20...   \n",
-       "1  https://copernicus-dem-90m.s3.amazonaws.com/20...   \n",
-       "2  https://copernicus-dem-90m.s3.amazonaws.com/20...   \n",
-       "3  https://copernicus-dem-90m.s3.amazonaws.com/20...   \n",
-       "4  https://copernicus-dem-90m.s3.amazonaws.com/20...   \n",
+       "0  https://copernicus-dem-90m.s3.amazonaws.com/Co...   \n",
+       "1  https://copernicus-dem-90m.s3.amazonaws.com/Co...   \n",
+       "2  https://copernicus-dem-90m.s3.amazonaws.com/Co...   \n",
+       "3  https://copernicus-dem-90m.s3.amazonaws.com/Co...   \n",
+       "4  https://copernicus-dem-90m.s3.amazonaws.com/Co...   \n",
        "\n",
        "                                            geometry  \n",
        "0  POLYGON ((7.00000 0.00000, 7.00000 1.00000, 6....  \n",
@@ -863,7 +862,7 @@
        "4  POLYGON ((13.00000 0.00000, 13.00000 1.00000, ...  "
       ]
      },
-     "execution_count": 20,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -881,12 +880,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "id": "1b82f848",
+   "execution_count": 13,
+   "id": "938ed51f",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-10T01:27:47.387715Z",
-     "start_time": "2022-06-10T01:27:45.129261Z"
+     "end_time": "2022-11-21T18:51:52.523833Z",
+     "start_time": "2022-11-21T18:51:50.428979Z"
     }
    },
    "outputs": [
@@ -896,7 +895,7 @@
        "PosixPath('data/glo_90.geojson.zip')"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -907,12 +906,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
-   "id": "another-sponsorship",
+   "execution_count": 14,
+   "id": "ebbf0388",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-10T01:27:52.633026Z",
-     "start_time": "2022-06-10T01:27:47.389711Z"
+     "end_time": "2022-11-21T18:51:57.062492Z",
+     "start_time": "2022-11-21T18:51:52.525685Z"
     }
    },
    "outputs": [
@@ -923,13 +922,13 @@
        "       0.0, -0.0008333333333333334, 1.0004166666666667), 'blockxsize': 2048, 'blockysize': 2048, 'tiled': True, 'compress': 'deflate', 'interleave': 'band'}"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -953,7 +952,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "generous-selling",
+   "id": "57045da3",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2021-06-02T23:53:00.097929Z",
@@ -969,7 +968,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "entire-power",
+   "id": "5dcfc693",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:28:48.559716Z",
@@ -1023,7 +1022,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "id": "affecting-plate",
+   "id": "9952f68f",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:28:48.596019Z",
@@ -1040,7 +1039,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "id": "international-court",
+   "id": "a799de6f",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:29:03.551392Z",
@@ -1081,7 +1080,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "id": "capital-glass",
+   "id": "5ec0941a",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:29:03.569770Z",
@@ -1122,7 +1121,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "id": "competitive-significance",
+   "id": "ebf281ad",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:29:03.575664Z",
@@ -1156,7 +1155,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "id": "capable-proof",
+   "id": "8d05a408",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:29:03.854848Z",
@@ -1260,7 +1259,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "id": "attended-lunch",
+   "id": "4cbb68d6",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:29:03.859955Z",
@@ -1286,7 +1285,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "id": "qualified-moldova",
+   "id": "0fc33968",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:29:04.142852Z",
@@ -1312,7 +1311,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "behavioral-mount",
+   "id": "bee86860",
    "metadata": {},
    "source": [
     "# Ned1"
@@ -1321,7 +1320,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "id": "essential-daughter",
+   "id": "9ca88567",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:29:07.310341Z",
@@ -1375,7 +1374,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "id": "varying-grade",
+   "id": "fccb042e",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:29:07.314750Z",
@@ -1392,7 +1391,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "id": "square-prerequisite",
+   "id": "2cf85b8e",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:29:09.648598Z",
@@ -1433,7 +1432,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "id": "focused-berry",
+   "id": "ec55411c",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:29:09.659311Z",
@@ -1474,7 +1473,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "id": "republican-bristol",
+   "id": "47446aaf",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:29:09.665788Z",
@@ -1512,7 +1511,7 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "id": "affected-light",
+   "id": "e6397a66",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:29:09.736776Z",
@@ -1616,7 +1615,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "id": "north-wheat",
+   "id": "b5ac2ede",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-02T21:29:10.010145Z",
@@ -1657,7 +1656,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.0"
+   "version": "3.9.13"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/organize_tile_data/1_Missing_glo-30_tiles.ipynb b/notebooks/organize_tile_data/1_Missing_glo-30_tiles.ipynb
index 473f330..5c5bd8a 100644
--- a/notebooks/organize_tile_data/1_Missing_glo-30_tiles.ipynb
+++ b/notebooks/organize_tile_data/1_Missing_glo-30_tiles.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "c309f51c",
+   "id": "b63501f0",
    "metadata": {},
    "source": [
     "This notebook should be run after `glo_30.geojson.zip` and `glo_90.geojson.zip` have been generated in the previous notebook."
@@ -11,11 +11,11 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "5ddd210f",
+   "id": "55ba6cfd",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-14T23:20:04.834894Z",
-     "start_time": "2022-06-14T23:20:02.633183Z"
+     "end_time": "2022-11-21T18:58:55.185808Z",
+     "start_time": "2022-11-21T18:58:54.149387Z"
     }
    },
    "outputs": [],
@@ -30,11 +30,11 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "1c17ffa6",
+   "id": "378e6fe3",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-14T23:20:06.314449Z",
-     "start_time": "2022-06-14T23:20:04.837433Z"
+     "end_time": "2022-11-21T18:58:56.471438Z",
+     "start_time": "2022-11-21T18:58:55.189790Z"
     }
    },
    "outputs": [],
@@ -46,11 +46,11 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "e140b3fb",
+   "id": "e562872a",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-14T23:20:11.149804Z",
-     "start_time": "2022-06-14T23:20:06.321542Z"
+     "end_time": "2022-11-21T18:59:01.305396Z",
+     "start_time": "2022-11-21T18:58:56.473563Z"
     }
    },
    "outputs": [
@@ -66,7 +66,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -84,11 +84,11 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "da18ae07",
+   "id": "891c3c4a",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-14T23:20:15.816133Z",
-     "start_time": "2022-06-14T23:20:11.153889Z"
+     "end_time": "2022-11-21T18:59:05.044303Z",
+     "start_time": "2022-11-21T18:59:01.307688Z"
     }
    },
    "outputs": [
@@ -96,7 +96,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/var/folders/s6/fbsc26cd0ddffbp3_knts_9c0wcxj1/T/ipykernel_85443/1417027846.py:1: UserWarning: Geometry is in a geographic CRS. Results from 'buffer' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n",
+      "/var/folders/s6/fbsc26cd0ddffbp3_knts_9c0wcxj1/T/ipykernel_76421/1417027846.py:1: UserWarning: Geometry is in a geographic CRS. Results from 'buffer' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n",
       "\n",
       "  geometry_shrunk = df_glo30.geometry.buffer(-.01).unary_union\n"
      ]
@@ -109,11 +109,11 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "b7ffe3b0",
+   "id": "2cb536eb",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-14T23:20:21.442994Z",
-     "start_time": "2022-06-14T23:20:15.820260Z"
+     "end_time": "2022-11-21T18:59:10.501936Z",
+     "start_time": "2022-11-21T18:59:05.045547Z"
     }
    },
    "outputs": [
@@ -136,11 +136,11 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "4d59dbdf",
+   "id": "4afd8bc2",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-14T23:20:21.461636Z",
-     "start_time": "2022-06-14T23:20:21.446541Z"
+     "end_time": "2022-11-21T18:59:10.515791Z",
+     "start_time": "2022-11-21T18:59:10.504380Z"
     }
    },
    "outputs": [
@@ -175,31 +175,31 @@
        "      <th>0</th>\n",
        "      <td>POLYGON ((46.00000 38.00000, 46.00000 39.00000...</td>\n",
        "      <td>Copernicus_DSM_COG_30_N38_00_E045_00_DEM</td>\n",
-       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/20...</td>\n",
+       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/Co...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>POLYGON ((47.00000 38.00000, 47.00000 39.00000...</td>\n",
        "      <td>Copernicus_DSM_COG_30_N38_00_E046_00_DEM</td>\n",
-       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/20...</td>\n",
+       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/Co...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>POLYGON ((49.00000 38.00000, 49.00000 39.00000...</td>\n",
        "      <td>Copernicus_DSM_COG_30_N38_00_E048_00_DEM</td>\n",
-       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/20...</td>\n",
+       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/Co...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>POLYGON ((50.00000 38.00000, 50.00000 39.00000...</td>\n",
        "      <td>Copernicus_DSM_COG_30_N38_00_E049_00_DEM</td>\n",
-       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/20...</td>\n",
+       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/Co...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>POLYGON ((45.00000 39.00000, 45.00000 40.00000...</td>\n",
        "      <td>Copernicus_DSM_COG_30_N39_00_E044_00_DEM</td>\n",
-       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/20...</td>\n",
+       "      <td>https://copernicus-dem-90m.s3.amazonaws.com/Co...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -221,11 +221,11 @@
        "4  Copernicus_DSM_COG_30_N39_00_E044_00_DEM   \n",
        "\n",
        "                                                 url  \n",
-       "0  https://copernicus-dem-90m.s3.amazonaws.com/20...  \n",
-       "1  https://copernicus-dem-90m.s3.amazonaws.com/20...  \n",
-       "2  https://copernicus-dem-90m.s3.amazonaws.com/20...  \n",
-       "3  https://copernicus-dem-90m.s3.amazonaws.com/20...  \n",
-       "4  https://copernicus-dem-90m.s3.amazonaws.com/20...  "
+       "0  https://copernicus-dem-90m.s3.amazonaws.com/Co...  \n",
+       "1  https://copernicus-dem-90m.s3.amazonaws.com/Co...  \n",
+       "2  https://copernicus-dem-90m.s3.amazonaws.com/Co...  \n",
+       "3  https://copernicus-dem-90m.s3.amazonaws.com/Co...  \n",
+       "4  https://copernicus-dem-90m.s3.amazonaws.com/Co...  "
       ]
      },
      "execution_count": 6,
@@ -241,11 +241,11 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "0285a177",
+   "id": "e7e1bb1f",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-14T23:20:21.689722Z",
-     "start_time": "2022-06-14T23:20:21.463470Z"
+     "end_time": "2022-11-21T18:59:12.812423Z",
+     "start_time": "2022-11-21T18:59:12.460960Z"
     }
    },
    "outputs": [
@@ -261,7 +261,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -288,11 +288,11 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "b598b625",
+   "id": "b468e278",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-14T23:20:21.694016Z",
-     "start_time": "2022-06-14T23:20:21.691550Z"
+     "end_time": "2022-11-21T18:59:13.391344Z",
+     "start_time": "2022-11-21T18:59:13.388675Z"
     }
    },
    "outputs": [],
@@ -303,12 +303,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "id": "933794c5",
+   "execution_count": 10,
+   "id": "8bdf1ca6",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2022-06-14T23:20:21.703808Z",
-     "start_time": "2022-06-14T23:20:21.695771Z"
+     "end_time": "2022-11-21T19:52:24.734425Z",
+     "start_time": "2022-11-21T19:52:24.726689Z"
     }
    },
    "outputs": [
@@ -318,7 +318,7 @@
        "PosixPath('data/glo_90_missing.geojson.zip')"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/setup.py b/setup.py
index 2b8dcba..809a5ef 100755
--- a/setup.py
+++ b/setup.py
@@ -25,6 +25,7 @@
         'Programming Language :: Python :: 3.8',
         'Programming Language :: Python :: 3.9',
         'Programming Language :: Python :: 3.10',
+        'Programming Language :: Python :: 3.11',
     ],
 
     python_requires='>=3.7',


Test patch:
diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 5ed210e..0493fd2 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -15,7 +15,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.7", "3.8", "3.9", "3.10"]
+        python-version: ["3.7", "3.8", "3.9", "3.10", "3.11"]
 
     steps:
       - uses: actions/checkout@v2
diff --git a/tests/test_geoid.py b/tests/test_geoid.py
index 933996b..0a89501 100644
--- a/tests/test_geoid.py
+++ b/tests/test_geoid.py
@@ -25,7 +25,7 @@ def test_read_geoid():
     data_all = X_all[~mask]
 
     assert_array_equal(data_sub, data_all)
-    assert(p_r['transform'] == p_all['transform'])
+    assert p_r['transform'] == p_all['transform']
 
 
 @pytest.mark.parametrize("dem_res", [.001, .01, .1, 1])
@@ -52,7 +52,7 @@ def test_remove_geoid(get_los_angeles_dummy_profile, dem_res):
             _ = remove_geoid(Y, p_ref, 'geoid_18')
 
         res_buffer_updated = (int(np.ceil(dem_res / geoid_res)))
-        assert(res_buffer_default < res_buffer_updated)
+        assert res_buffer_default < res_buffer_updated
 
         X_sub_2 = remove_geoid(Y, p_ref, 'geoid_18', res_buffer=res_buffer_updated)
 
diff --git a/tests/test_missing.py b/tests/test_missing.py
index 2e93987..cc45779 100644
--- a/tests/test_missing.py
+++ b/tests/test_missing.py
@@ -27,7 +27,7 @@ def _open_one(path):
 
 @pytest.mark.parametrize('extent, containment', zip(extents, containment))
 def test_intersects_missing_tiles(extent, containment):
-    assert(intersects_missing_glo_30_tiles(extent) == containment)
+    assert intersects_missing_glo_30_tiles(extent) == containment
 
 
 def test_merge_glo30_and_glo_90(test_data_dir):
@@ -44,7 +44,7 @@ def test_merge_glo30_and_glo_90(test_data_dir):
                                                           X_glo_90, p_glo_90)
 
     assert_almost_equal(X_merged, X_merged_out, decimal=6)
-    assert(p_merged_out['transform'] == p_merged['transform'])
+    assert p_merged_out['transform'] == p_merged['transform']
 
 
 @pytest.mark.integration
@@ -69,4 +69,4 @@ def test_glo_90_filling(test_data_dir):
     X_merged, p_merged = _open_one(glo_merged_path)
 
     assert_almost_equal(X_merged, X_filled, decimal=6)
-    assert(p_filled['transform'] == p_merged['transform'])
+    assert p_filled['transform'] == p_merged['transform']
diff --git a/tests/test_rio_tools.py b/tests/test_rio_tools.py
index 4eeda9f..85c74aa 100644
--- a/tests/test_rio_tools.py
+++ b/tests/test_rio_tools.py
@@ -11,7 +11,7 @@ def test_update_resolution(test_data_dir):
     """
 
     data_dir = test_data_dir / 'rio_tools' / 'update_resolution'
-    assert(data_dir.exists())
+    assert data_dir.exists()
 
     with rasterio.open(data_dir / 'res_one_deg.tif') as ds:
         p_one_deg = ds.profile
@@ -25,9 +25,9 @@ def test_update_resolution(test_data_dir):
 
     t_one_deg = p_one_deg['transform']
     t_quarter_deg = p_quarter_deg['transform']
-    assert((t_one_deg * (0, 0)) == (t_quarter_deg * (0, 0)))
-    assert(res_one_deg == (1, 1))
-    assert(res_quarter_deg == (.25, .25))
+    assert (t_one_deg * (0, 0)) == (t_quarter_deg * (0, 0))
+    assert res_one_deg == (1, 1)
+    assert res_quarter_deg == (.25, .25)
 
     p_higher_res = update_profile_resolution(p_one_deg, .25)
     X_quarter_deg_reprj, _ = reproject_arr_to_match_profile(X_one_deg,
@@ -37,4 +37,4 @@ def test_update_resolution(test_data_dir):
     X_quarter_deg_reprj = X_quarter_deg_reprj[0, ...]
 
     assert_almost_equal(X_quarter_deg_reprj, X_quarter_deg, 5)
-    assert(t_quarter_deg == p_higher_res['transform'])
+    assert t_quarter_deg == p_higher_res['transform']
diff --git a/tests/test_stitcher.py b/tests/test_stitcher.py
index e612161..4c062e4 100644
--- a/tests/test_stitcher.py
+++ b/tests/test_stitcher.py
@@ -95,7 +95,7 @@ def test_merge_tiles(test_data_dir, extent, array, transform):
     list(map(lambda x: x.close, tile_datasets))
 
     assert_array_equal(X, array)
-    assert(p['transform'] == transform)
+    assert p['transform'] == transform
 
 
 """
@@ -140,7 +140,7 @@ def test_shift_pixel_loc(src_tag, dst_tag, transform_expected):
     t_new = p_new['transform']
 
     # Check the transform is what we expect
-    assert(transform_expected == t_new)
+    assert transform_expected == t_new
 
 
 @pytest.mark.parametrize("dem_name", ['glo_30', 'nasadem'])
@@ -193,4 +193,4 @@ def test_download_dem(dem_name):
                             dst_ellipsoidal_height=True,
                             dst_resolution=0.0002777777777777777775
                             )
-    assert(len(dem_arr.shape) == 2)
+    assert len(dem_arr.shape) == 2
diff --git a/tests/test_window.py b/tests/test_window.py
index fd44861..5ecb59d 100644
--- a/tests/test_window.py
+++ b/tests/test_window.py
@@ -78,7 +78,7 @@ def test_read_window_4326(test_data_dir, extent, array, transform):
                                             CRS.from_epsg(4326),
                                             res_buffer=0)
     assert_array_equal(array, window_arr)
-    assert(transform == p['transform'])
+    assert transform == p['transform']
 
 
 @pytest.mark.parametrize("geojson_index, array, transform", zip([0, 1, 2, 3], arrays, transforms))
@@ -97,7 +97,7 @@ def test_read_window_utm(test_data_dir, geojson_index, array, transform):
                                             crs,
                                             res_buffer=0)
     assert_array_equal(array, window_arr)
-    assert(transform == p['transform'])
+    assert transform == p['transform']
 
 
 """
@@ -123,7 +123,7 @@ def test_get_indices(extent, arr_index):
     """
     t = Affine(1, 0, 10, 0, -1, 0)
     ul, br = get_indices_from_extent(t, extent)
-    assert(arr_index == (ul, br))
+    assert arr_index == (ul, br)
 
 
 # Indices
@@ -141,7 +141,7 @@ def test_get_indices_buffered(extent, arr_index):
     """
     t = Affine(1, 0, 10, 0, -1, 0)
     ul, br = get_indices_from_extent(t, extent, res_buffer=1)
-    assert(arr_index == (ul, br))
+    assert arr_index == (ul, br)
 
 
 # Indices
@@ -159,7 +159,7 @@ def test_get_indices_shape(extent, arr_index):
     """
     t = Affine(1, 0, 10, 0, -1, 0)
     ul, br = get_indices_from_extent(t, extent, res_buffer=1, shape=(12, 10))
-    assert(arr_index == (ul, br))
+    assert arr_index == (ul, br)
 
 
 # Additional tests for unequal dimensions
@@ -202,4 +202,4 @@ def test_read_window_4326_unequal_dims(test_data_dir, extent, array, transform):
                                             CRS.from_epsg(4326),
                                             res_buffer=0)
     assert_array_equal(array, window_arr)
-    assert(transform == p['transform'])
+    assert transform == p['transform']