diff --git a/docs/tutorials/pretrained_weights.ipynb b/docs/tutorials/pretrained_weights.ipynb
index 28b354efee6..0c2c4a0fc48 100644
--- a/docs/tutorials/pretrained_weights.ipynb
+++ b/docs/tutorials/pretrained_weights.ipynb
@@ -215,7 +215,7 @@
     "id": "dWidC6vDrMON"
    },
    "source": [
-    "If you do not want to utilize the `ClassificationTask` functionality for your experiments, you can also just create a [timm](https://github.com/rwightman/pytorch-image-models) model with pretrained weights from TorchGeo as follows:"
+    "If you do not want to utilize the `ClassificationTask` functionality for your experiments, you can also just create a [timm](https://github.com/huggingface/pytorch-image-models) model with pretrained weights from TorchGeo as follows:"
    ]
   },
   {
diff --git a/docs/user/contributing.rst b/docs/user/contributing.rst
index 5e44212d884..91b8b4d3ab4 100644
--- a/docs/user/contributing.rst
+++ b/docs/user/contributing.rst
@@ -52,7 +52,7 @@ Tests
 
 TorchGeo uses `GitHub Actions <https://docs.github.com/en/actions>`_ for Continuous Integration. We run a suite of unit tests on every commit to ensure that pull requests don't break anything. If you submit a pull request that adds or modifies any Python code, we require unit tests for that code before the pull request can be merged.
 
-For example, if you add a new dataset in ``torchgeo/datasets/foo.py``, you'll need to create corresponding unit tests in ``tests/datasets/test_foo.py``. The easiest way to do this is to find unit tests for similar datasets and modify them for your dataset. These tests can then be run with `pytest <https://docs.pytest.org/>`_:
+For example, if you add a new dataset in ``torchgeo/datasets/foo.py``, you'll need to create corresponding unit tests in ``tests/datasets/test_foo.py``. The easiest way to do this is to find unit tests for similar datasets and modify them for your dataset. These tests can then be run with `pytest <https://docs.pytest.org/en/stable/>`_:
 
 .. code-block:: console
 
@@ -79,7 +79,7 @@ For example, if you add a new dataset in ``torchgeo/datasets/foo.py``, you'll ne
 
 From this output, you can see that all tests pass, but many lines of code in ``torchgeo/datasets/foo.py`` are not being tested, including 376--403, 429--496, etc. In order for this pull request to be merged, additional tests will need to be added until there is 100% test coverage.
 
-These tests require `pytest <https://docs.pytest.org/>`_ and `pytest-cov <https://pytest-cov.readthedocs.io/>`_ to be installed.
+These tests require `pytest <https://docs.pytest.org/en/stable/>`_ and `pytest-cov <https://pytest-cov.readthedocs.io/en/latest/>`_ to be installed.
 
 .. note:: If you add a new dataset, the tests will require some form of data to run. This data should be stored in ``tests/data/<dataset>``. Please don't include real data, as this may violate the license the data is distributed under, and can involve very large file sizes. Instead, create fake data examples using the instructions found `here <https://github.com/microsoft/torchgeo/blob/main/tests/data/README.md>`__.
 
@@ -91,7 +91,7 @@ Linters
 In order to remain `PEP-8 <https://peps.python.org/pep-0008/>`_ compliant and maintain a high-quality codebase, we use a couple of linting tools:
 
 * `ruff <https://docs.astral.sh/ruff/>`_ for code formatting
-* `mypy <https://mypy.readthedocs.io/>`_ for static type analysis
+* `mypy <https://mypy.readthedocs.io/en/stable/>`_ for static type analysis
 * `prettier <https://prettier.io/docs/en/>`_ for code formatting
 
 These tools should be used from the root of the project to ensure that our configuration files are found. Ruff is relatively easy to use, and will automatically fix most issues it encounters:
@@ -142,7 +142,7 @@ Now, every time you run ``git commit``, pre-commit will run and let you know if
 Documentation
 -------------
 
-All of our documentation is hosted on `Read the Docs <https://readthedocs.org/>`_. If you make non-trivial changes to the documentation, it helps to build the documentation yourself locally. To do this, make sure the dependencies are installed:
+All of our documentation is hosted on `Read the Docs <https://about.readthedocs.com/>`_. If you make non-trivial changes to the documentation, it helps to build the documentation yourself locally. To do this, make sure the dependencies are installed:
 
 .. code-block:: console
 
@@ -164,7 +164,7 @@ The resulting HTML files can be found in ``_build/html``. Open ``index.html`` in
 Tutorials
 ---------
 
-TorchGeo has a number of tutorials included in the documentation that can be run in `Google Colab <https://colab.research.google.com/>`_. These Jupyter notebooks are tested before each release to make sure that they still run properly. To test these locally, install `pytest <https://docs.pytest.org/>`_ and `nbmake <https://github.com/treebeardtech/nbmake>`_ and run:
+TorchGeo has a number of tutorials included in the documentation that can be run in `Google Colab <https://colab.research.google.com/>`_. These Jupyter notebooks are tested before each release to make sure that they still run properly. To test these locally, install `pytest <https://docs.pytest.org/en/stable/>`_ and `nbmake <https://github.com/treebeardtech/nbmake>`_ and run:
 
 .. code-block:: console
 
diff --git a/docs/user/installation.rst b/docs/user/installation.rst
index 3dd5545b774..9a96af95534 100644
--- a/docs/user/installation.rst
+++ b/docs/user/installation.rst
@@ -1,7 +1,7 @@
 Installation
 ============
 
-TorchGeo is simple and easy to install. We support installation using the `pip <https://pip.pypa.io/>`_, `conda <https://docs.conda.io/>`_, and `spack <https://spack.io/>`_ package managers.
+TorchGeo is simple and easy to install. We support installation using the `pip <https://pip.pypa.io/en/stable/>`_, `conda <https://docs.conda.io/en/latest/>`_, and `spack <https://spack.io/>`_ package managers.
 
 pip
 ---
@@ -34,7 +34,7 @@ By default, only required dependencies are installed. TorchGeo has a number of o
    $ pip install torchgeo[style,tests]
    $ pip install torchgeo[all]
 
-See the ``pyproject.toml`` for a complete list of options. See the `pip documentation <https://pip.pypa.io/>`_ for more details.
+See the ``pyproject.toml`` for a complete list of options. See the `pip documentation <https://pip.pypa.io/en/stable/>`_ for more details.
 
 conda
 -----
@@ -82,4 +82,4 @@ Optional dependencies can be installed by enabling build variants:
    $ spack install py-torchgeo+datasets
    $ spack install py-torchgeo+style+tests
 
-Run ``spack info py-torchgeo`` for a complete list of variants. See the `spack documentation <https://spack.readthedocs.io/>`_ for more details.
+Run ``spack info py-torchgeo`` for a complete list of variants. See the `spack documentation <https://spack.readthedocs.io/en/latest/>`_ for more details.
diff --git a/pyproject.toml b/pyproject.toml
index 66d10bab841..97d326961de 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -189,7 +189,7 @@ filterwarnings = [
     # https://github.com/pytorch/vision/pull/5898
     "ignore:.* is deprecated and will be removed in Pillow 10:DeprecationWarning:torchvision.transforms.functional_pil",
     "ignore:.* is deprecated and will be removed in Pillow 10:DeprecationWarning:torchvision.transforms._functional_pil",
-    # https://github.com/rwightman/pytorch-image-models/pull/1256
+    # https://github.com/huggingface/pytorch-image-models/pull/1256
     "ignore:.* is deprecated and will be removed in Pillow 10:DeprecationWarning:timm.data",
     # https://github.com/pytorch/pytorch/issues/72906
     # https://github.com/pytorch/pytorch/pull/69823
diff --git a/torchgeo/__init__.py b/torchgeo/__init__.py
index 21e4dc5ee3f..5574da2f7eb 100644
--- a/torchgeo/__init__.py
+++ b/torchgeo/__init__.py
@@ -3,8 +3,8 @@
 
 """TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data.
 
-This library is part of the `PyTorch <http://pytorch.org/>`_ project. PyTorch is an open
-source machine learning framework.
+This library is part of the `PyTorch <https://pytorch.org/>`_ project. PyTorch is an
+open source machine learning framework.
 
 The :mod:`torchgeo` package consists of popular datasets, model architectures, and
 common image transformations for geospatial data.
diff --git a/torchgeo/datasets/advance.py b/torchgeo/datasets/advance.py
index b46695957be..c9fcea22a01 100644
--- a/torchgeo/datasets/advance.py
+++ b/torchgeo/datasets/advance.py
@@ -64,8 +64,8 @@ class ADVANCE(NonGeoDataset):
     """
 
     urls = (
-        'https://zenodo.org/record/3828124/files/ADVANCE_vision.zip?download=1',
-        'https://zenodo.org/record/3828124/files/ADVANCE_sound.zip?download=1',
+        'https://zenodo.org/records/3828124/files/ADVANCE_vision.zip?download=1',
+        'https://zenodo.org/records/3828124/files/ADVANCE_sound.zip?download=1',
     )
     filenames = ('ADVANCE_vision.zip', 'ADVANCE_sound.zip')
     md5s = ('a9e8748219ef5864d3b5a8979a67b471', 'a2d12f2d2a64f5c3d3a9d8c09aaf1c31')
diff --git a/torchgeo/datasets/cdl.py b/torchgeo/datasets/cdl.py
index 07bd8193b79..6cd2b483062 100644
--- a/torchgeo/datasets/cdl.py
+++ b/torchgeo/datasets/cdl.py
@@ -22,7 +22,7 @@ class CDL(RasterDataset):
     """Cropland Data Layer (CDL) dataset.
 
     The `Cropland Data Layer
-    <https://data.nal.usda.gov/dataset/cropscape-cropland-data-layer>`__, hosted on
+    <https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php>`__, hosted on
     `CropScape <https://nassgeodata.gmu.edu/CropScape/>`_, provides a raster,
     geo-referenced, crop-specific land cover map for the continental United States. The
     CDL also includes a crop mask layer and planting frequency layers, as well as
@@ -37,7 +37,7 @@ class CDL(RasterDataset):
 
     If you use this dataset in your research, please cite it using the following format:
 
-    * https://www.nass.usda.gov/Research_and_Science/Cropland/sarsfaqs2.php#Section1_14.0
+    * https://www.nass.usda.gov/Research_and_Science/Cropland/sarsfaqs2.php#what.1
     """
 
     filename_glob = '*_30m_cdls.tif'
diff --git a/torchgeo/datasets/chesapeake.py b/torchgeo/datasets/chesapeake.py
index 46dbaefc806..33a347576f9 100644
--- a/torchgeo/datasets/chesapeake.py
+++ b/torchgeo/datasets/chesapeake.py
@@ -330,7 +330,7 @@ class ChesapeakeCVPR(GeoDataset):
     additional layer of data to this dataset containing a prior over the Chesapeake Bay
     land cover classes generated from the NLCD land cover labels. For more information
     about this layer see `the dataset documentation
-    <https://zenodo.org/record/5866525>`_.
+    <https://zenodo.org/records/5866525>`_.
 
     If you use this dataset in your research, please cite the following paper:
 
@@ -340,7 +340,7 @@ class ChesapeakeCVPR(GeoDataset):
     subdatasets = ('base', 'prior_extension')
     urls: ClassVar[dict[str, str]] = {
         'base': 'https://lilablobssc.blob.core.windows.net/lcmcvpr2019/cvpr_chesapeake_landcover.zip',
-        'prior_extension': 'https://zenodo.org/record/5866525/files/cvpr_chesapeake_landcover_prior_extension.zip?download=1',
+        'prior_extension': 'https://zenodo.org/records/5866525/files/cvpr_chesapeake_landcover_prior_extension.zip?download=1',
     }
     filenames: ClassVar[dict[str, str]] = {
         'base': 'cvpr_chesapeake_landcover.zip',
diff --git a/torchgeo/datasets/deepglobelandcover.py b/torchgeo/datasets/deepglobelandcover.py
index 51b82f9ff92..47ef6f15ce3 100644
--- a/torchgeo/datasets/deepglobelandcover.py
+++ b/torchgeo/datasets/deepglobelandcover.py
@@ -61,7 +61,7 @@ class DeepGlobeLandCover(NonGeoDataset):
 
     If you use this dataset in your research, please cite the following paper:
 
-    * https://arxiv.org/pdf/1805.06561.pdf
+    * https://arxiv.org/pdf/1805.06561
 
     .. note::
 
diff --git a/torchgeo/datasets/dfc2022.py b/torchgeo/datasets/dfc2022.py
index edc79d8ae2b..6886ea6b1d3 100644
--- a/torchgeo/datasets/dfc2022.py
+++ b/torchgeo/datasets/dfc2022.py
@@ -43,7 +43,7 @@ class DFC2022(NonGeoDataset):
     * DEMs collected from the
       `IGN RGE ALTI database <https://geoservices.ign.fr/documentation/donnees/alti/rgealti/>`_
     * Labels collected from the
-      `UrbanAtlas 2012 database <https://land.copernicus.eu/local/urban-atlas/urban-atlas-2012/view/>`_
+      `UrbanAtlas 2012 database <https://land.copernicus.eu/en/products/urban-atlas/urban-atlas-2012>`_
     * Data collected from 19 regions in France
 
     Dataset format:
diff --git a/torchgeo/datasets/enviroatlas.py b/torchgeo/datasets/enviroatlas.py
index 5e6d4b80d99..b8af4aef70e 100644
--- a/torchgeo/datasets/enviroatlas.py
+++ b/torchgeo/datasets/enviroatlas.py
@@ -47,7 +47,7 @@ class EnviroAtlas(GeoDataset):
     .. versionadded:: 0.3
     """
 
-    url = 'https://zenodo.org/record/5778193/files/enviroatlas_lotp.zip?download=1'
+    url = 'https://zenodo.org/records/5778193/files/enviroatlas_lotp.zip?download=1'
     filename = 'enviroatlas_lotp.zip'
     md5 = 'bfe601be21c7c001315fc6154be8ef14'
 
diff --git a/torchgeo/datasets/eudem.py b/torchgeo/datasets/eudem.py
index 1d65a55f60c..765433bfc05 100644
--- a/torchgeo/datasets/eudem.py
+++ b/torchgeo/datasets/eudem.py
@@ -21,13 +21,8 @@
 class EUDEM(RasterDataset):
     """European Digital Elevation Model (EU-DEM) Dataset.
 
-    The `EU-DEM
-    <https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1?tab=mapview>`__
-    dataset is a Digital Elevation Model of reference for the entire European region.
-    The dataset can be downloaded from this `website
-    <https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1?tab=mapview>`_
-    after making an account. A dataset factsheet is available
-    `here <https://land.copernicus.eu/user-corner/publications/eu-dem-flyer/view>`__.
+    `EU-DEM <https://www.eea.europa.eu/en/datahub/datahubitem-view/d08852bc-7b5f-4835-a776-08362e2fbf4b>`__
+    is a Digital Elevation Model of reference for the entire European region.
 
     Dataset features:
 
@@ -41,10 +36,6 @@ class EUDEM(RasterDataset):
 
     * DEMs are single-channel tif files
 
-    If you use this dataset in your research, please give credit to:
-
-    * `Copernicus <https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1>`_
-
     .. versionadded:: 0.3
     """
 
diff --git a/torchgeo/datasets/idtrees.py b/torchgeo/datasets/idtrees.py
index 6157579eb1b..28e890dc69f 100644
--- a/torchgeo/datasets/idtrees.py
+++ b/torchgeo/datasets/idtrees.py
@@ -137,12 +137,12 @@ class IDTReeS(NonGeoDataset):
     }
     metadata: ClassVar[dict[str, dict[str, str]]] = {
         'train': {
-            'url': 'https://zenodo.org/record/3934932/files/IDTREES_competition_train_v2.zip?download=1',
+            'url': 'https://zenodo.org/records/3934932/files/IDTREES_competition_train_v2.zip?download=1',
             'md5': '5ddfa76240b4bb6b4a7861d1d31c299c',
             'filename': 'IDTREES_competition_train_v2.zip',
         },
         'test': {
-            'url': 'https://zenodo.org/record/3934932/files/IDTREES_competition_test_v2.zip?download=1',
+            'url': 'https://zenodo.org/records/3934932/files/IDTREES_competition_test_v2.zip?download=1',
             'md5': 'b108931c84a70f2a38a8234290131c9b',
             'filename': 'IDTREES_competition_test_v2.zip',
         },
diff --git a/torchgeo/datasets/inaturalist.py b/torchgeo/datasets/inaturalist.py
index f33f2d14d57..bb5cfe3c8df 100644
--- a/torchgeo/datasets/inaturalist.py
+++ b/torchgeo/datasets/inaturalist.py
@@ -26,7 +26,7 @@ class INaturalist(GeoDataset):
 
     If you use an iNaturalist dataset in your research, please cite it according to:
 
-    * https://www.inaturalist.org/pages/help#cite
+    * https://help.inaturalist.org/en/support/solutions/articles/151000170344-how-should-i-cite-inaturalist-
 
     .. versionadded:: 0.3
     """
diff --git a/torchgeo/datasets/loveda.py b/torchgeo/datasets/loveda.py
index 0398410a674..93b6b18e455 100644
--- a/torchgeo/datasets/loveda.py
+++ b/torchgeo/datasets/loveda.py
@@ -63,17 +63,17 @@ class LoveDA(NonGeoDataset):
 
     info_dict: ClassVar[dict[str, dict[str, str]]] = {
         'train': {
-            'url': 'https://zenodo.org/record/5706578/files/Train.zip?download=1',
+            'url': 'https://zenodo.org/records/5706578/files/Train.zip?download=1',
             'filename': 'Train.zip',
             'md5': 'de2b196043ed9b4af1690b3f9a7d558f',
         },
         'val': {
-            'url': 'https://zenodo.org/record/5706578/files/Val.zip?download=1',
+            'url': 'https://zenodo.org/records/5706578/files/Val.zip?download=1',
             'filename': 'Val.zip',
             'md5': '84cae2577468ff0b5386758bb386d31d',
         },
         'test': {
-            'url': 'https://zenodo.org/record/5706578/files/Test.zip?download=1',
+            'url': 'https://zenodo.org/records/5706578/files/Test.zip?download=1',
             'filename': 'Test.zip',
             'md5': 'a489be0090465e01fb067795d24e6b47',
         },
diff --git a/torchgeo/datasets/openbuildings.py b/torchgeo/datasets/openbuildings.py
index f19f4c9a2ce..50b35ee39db 100644
--- a/torchgeo/datasets/openbuildings.py
+++ b/torchgeo/datasets/openbuildings.py
@@ -32,7 +32,7 @@ class OpenBuildings(VectorDataset):
     r"""Open Buildings dataset.
 
     The `Open Buildings
-    <https://sites.research.google/open-buildings/#download>`__ dataset
+    <https://sites.research.google/open-buildings/>`__ dataset
     consists of computer generated building detections across the African continent.
 
     Dataset features:
@@ -48,10 +48,10 @@ class OpenBuildings(VectorDataset):
     * meta data geojson file
 
     The data can be downloaded from `here
-    <https://sites.research.google/open-buildings/#download>`__. Additionally, the
-    `meta data geometry file
-    <https://sites.research.google/open-buildings/tiles.geojson>`_ also needs to be
-    placed in `root` as `tiles.geojson`.
+    <https://sites.research.google/open-buildings/#open-buildings-download>`__.
+    Additionally, the `meta data geometry file
+    <https://openbuildings-public-dot-gweb-research.uw.r.appspot.com/public/tiles.geojson>`_
+    also needs to be placed in `root` as `tiles.geojson`.
 
     If you use this dataset in your research, please cite the following technical
     report:
diff --git a/torchgeo/datasets/pastis.py b/torchgeo/datasets/pastis.py
index 430a6330d89..06f716a9ffb 100644
--- a/torchgeo/datasets/pastis.py
+++ b/torchgeo/datasets/pastis.py
@@ -117,7 +117,7 @@ class PASTIS(NonGeoDataset):
     }
     directory = 'PASTIS-R'
     filename = 'PASTIS-R.zip'
-    url = 'https://zenodo.org/record/5735646/files/PASTIS-R.zip?download=1'
+    url = 'https://zenodo.org/records/5735646/files/PASTIS-R.zip?download=1'
     md5 = '4887513d6c2d2b07fa935d325bd53e09'
     prefix: ClassVar[dict[str, str]] = {
         's2': os.path.join('DATA_S2', 'S2_'),
diff --git a/torchgeo/datasets/reforestree.py b/torchgeo/datasets/reforestree.py
index 930799ed205..1c46c450191 100644
--- a/torchgeo/datasets/reforestree.py
+++ b/torchgeo/datasets/reforestree.py
@@ -57,7 +57,7 @@ class ReforesTree(NonGeoDataset):
     """
 
     classes = ('other', 'banana', 'cacao', 'citrus', 'fruit', 'timber')
-    url = 'https://zenodo.org/record/6813783/files/reforesTree.zip?download=1'
+    url = 'https://zenodo.org/records/6813783/files/reforesTree.zip?download=1'
 
     md5 = 'f6a4a1d8207aeaa5fbab7b21b683a302'
     zipfilename = 'reforesTree.zip'
diff --git a/torchgeo/datasets/seco.py b/torchgeo/datasets/seco.py
index 0d1df7f7bbe..c67fecb9c8e 100644
--- a/torchgeo/datasets/seco.py
+++ b/torchgeo/datasets/seco.py
@@ -35,7 +35,7 @@ class SeasonalContrastS2(NonGeoDataset):
 
     If you use this dataset in your research, please cite the following paper:
 
-    * https://arxiv.org/pdf/2103.16607.pdf
+    * https://arxiv.org/pdf/2103.16607
     """
 
     all_bands = (
@@ -56,13 +56,13 @@ class SeasonalContrastS2(NonGeoDataset):
 
     metadata: ClassVar[dict[str, dict[str, str]]] = {
         '100k': {
-            'url': 'https://zenodo.org/record/4728033/files/seco_100k.zip?download=1',
+            'url': 'https://zenodo.org/records/4728033/files/seco_100k.zip?download=1',
             'md5': 'ebf2d5e03adc6e657f9a69a20ad863e0',
             'filename': 'seco_100k.zip',
             'directory': 'seasonal_contrast_100k',
         },
         '1m': {
-            'url': 'https://zenodo.org/record/4728033/files/seco_1m.zip?download=1',
+            'url': 'https://zenodo.org/records/4728033/files/seco_1m.zip?download=1',
             'md5': '187963d852d4d3ce6637743ec3a4bd9e',
             'filename': 'seco_1m.zip',
             'directory': 'seasonal_contrast_1m',
diff --git a/torchgeo/datasets/sentinel.py b/torchgeo/datasets/sentinel.py
index 3dc5fc31771..79637931adb 100644
--- a/torchgeo/datasets/sentinel.py
+++ b/torchgeo/datasets/sentinel.py
@@ -25,7 +25,7 @@ class Sentinel(RasterDataset):
 
     If you use this dataset in your research, please cite it using the following format:
 
-    * https://asf.alaska.edu/data-sets/sar-data-sets/sentinel-1/sentinel-1-how-to-cite/
+    * https://asf.alaska.edu/datasets/daac/sentinel-1/
     """
 
 
@@ -33,7 +33,7 @@ class Sentinel1(Sentinel):
     r"""Sentinel-1 dataset.
 
     The `Sentinel-1 mission
-    <https://sentinel.esa.int/web/sentinel/missions/sentinel-1>`_ comprises a
+    <https://sentiwiki.copernicus.eu/web/s1-mission>`_ comprises a
     constellation of two polar-orbiting satellites, operating day and night
     performing C-band synthetic aperture radar imaging, enabling them to
     acquire imagery regardless of the weather.
@@ -50,16 +50,16 @@ class Sentinel1(Sentinel):
     Product Types:
 
     * `Level-0
-      <https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-1-sar/product-types-processing-levels/level-0>`_:
+      <https://sentinels.copernicus.eu/en/web/sentinel/user-guides/sentinel-1-sar/product-types-processing-levels/level-0>`_:
       Raw (RAW)
     * `Level-1
-      <https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-1-sar/product-types-processing-levels/level-1>`_:
+      <https://sentinels.copernicus.eu/en/web/sentinel/user-guides/sentinel-1-sar/product-types-processing-levels/level-1>`_:
       Single Look Complex (SLC)
     * `Level-1
-      <https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-1-sar/product-types-processing-levels/level-1>`_:
+      <https://sentinels.copernicus.eu/en/web/sentinel/user-guides/sentinel-1-sar/product-types-processing-levels/level-1>`_:
       Ground Range Detected (GRD)
     * `Level-2
-      <https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-1-sar/product-types-processing-levels/level-2>`_:
+      <https://sentinels.copernicus.eu/en/web/sentinel/user-guides/sentinel-1-sar/product-types-processing-levels/level-2>`_:
       Ocean (OCN)
 
     Polarizations:
@@ -72,13 +72,13 @@ class Sentinel1(Sentinel):
     Acquisition Modes:
 
     * `Stripmap (SM)
-      <https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-1-sar/acquisition-modes/stripmap>`_
+      <https://sentinels.copernicus.eu/en/web/sentinel/user-guides/sentinel-1-sar/acquisition-modes/stripmap>`_
     * `Interferometric Wide (IW) swath
-      <https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-1-sar/acquisition-modes/interferometric-wide-swath>`_
+      <https://sentinels.copernicus.eu/en/web/sentinel/user-guides/sentinel-1-sar/acquisition-modes/interferometric-wide-swath>`_
     * `Extra Wide (EW) swatch
-      <https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-1-sar/acquisition-modes/extra-wide-swath>`_
+      <https://sentinels.copernicus.eu/en/web/sentinel/user-guides/sentinel-1-sar/acquisition-modes/extra-wide-swath>`_
     * `Wave (WV)
-      <https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-1-sar/acquisition-modes/wave>`_
+      <https://sentinels.copernicus.eu/en/web/sentinel/user-guides/sentinel-1-sar/acquisition-modes/wave>`_
 
     .. note::
        At the moment, this dataset only supports the GRD product type. Data must be
@@ -255,7 +255,7 @@ class Sentinel2(Sentinel):
     """Sentinel-2 dataset.
 
     The `Copernicus Sentinel-2 mission
-    <https://sentinel.esa.int/web/sentinel/missions/sentinel-2>`_ comprises a
+    <https://sentiwiki.copernicus.eu/web/s2-mission>`_ comprises a
     constellation of two polar-orbiting satellites placed in the same sun-synchronous
     orbit, phased at 180° to each other. It aims at monitoring variability in land
     surface conditions, and its wide swath width (290 km) and high revisit time (10 days
diff --git a/torchgeo/models/farseg.py b/torchgeo/models/farseg.py
index f57f59cde5f..dc25858abf6 100644
--- a/torchgeo/models/farseg.py
+++ b/torchgeo/models/farseg.py
@@ -36,7 +36,7 @@ class FarSeg(Module):
 
     If you use this model in your research, please cite the following paper:
 
-    * https://arxiv.org/pdf/2011.09766.pdf
+    * https://arxiv.org/pdf/2011.09766
     """
 
     def __init__(
diff --git a/torchgeo/models/resnet.py b/torchgeo/models/resnet.py
index 7429251c731..b61e816ea28 100644
--- a/torchgeo/models/resnet.py
+++ b/torchgeo/models/resnet.py
@@ -122,7 +122,7 @@
 class ResNet18_Weights(WeightsEnum):  # type: ignore[misc]
     """ResNet-18 weights.
 
-    For `timm <https://github.com/rwightman/pytorch-image-models>`_
+    For `timm <https://github.com/huggingface/pytorch-image-models>`_
     *resnet18* implementation.
 
     .. versionadded:: 0.4
@@ -301,7 +301,7 @@ class ResNet18_Weights(WeightsEnum):  # type: ignore[misc]
 class ResNet50_Weights(WeightsEnum):  # type: ignore[misc]
     """ResNet-50 weights.
 
-    For `timm <https://github.com/rwightman/pytorch-image-models>`_
+    For `timm <https://github.com/huggingface/pytorch-image-models>`_
     *resnet50* implementation.
 
     .. versionadded:: 0.4
@@ -597,7 +597,7 @@ class ResNet50_Weights(WeightsEnum):  # type: ignore[misc]
 class ResNet152_Weights(WeightsEnum):  # type: ignore[misc]
     """ResNet-152 weights.
 
-    For `timm <https://github.com/rwightman/pytorch-image-models>`_
+    For `timm <https://github.com/huggingface/pytorch-image-models>`_
     *resnet152* implementation.
 
     .. versionadded:: 0.6
@@ -663,7 +663,7 @@ def resnet18(
 
     If you use this model in your research, please cite the following paper:
 
-    * https://arxiv.org/pdf/1512.03385.pdf
+    * https://arxiv.org/pdf/1512.03385
 
     .. versionadded:: 0.4
 
@@ -697,7 +697,7 @@ def resnet50(
 
     If you use this model in your research, please cite the following paper:
 
-    * https://arxiv.org/pdf/1512.03385.pdf
+    * https://arxiv.org/pdf/1512.03385
 
     .. versionchanged:: 0.4
        Switched to multi-weight support API.
@@ -732,7 +732,7 @@ def resnet152(
 
     If you use this model in your research, please cite the following paper:
 
-    * https://arxiv.org/pdf/1512.03385.pdf
+    * https://arxiv.org/pdf/1512.03385
 
     .. versionadded:: 0.6
 
diff --git a/torchgeo/models/vit.py b/torchgeo/models/vit.py
index 1878883f484..13785af416e 100644
--- a/torchgeo/models/vit.py
+++ b/torchgeo/models/vit.py
@@ -37,7 +37,7 @@
 class ViTSmall16_Weights(WeightsEnum):  # type: ignore[misc]
     """Vision Transformer Small Patch Size 16 weights.
 
-    For `timm <https://github.com/rwightman/pytorch-image-models>`_
+    For `timm <https://github.com/huggingface/pytorch-image-models>`_
     *vit_small_patch16_224* implementation.
 
     .. versionadded:: 0.4
diff --git a/torchgeo/trainers/byol.py b/torchgeo/trainers/byol.py
index 35243eaa545..38aac522b9d 100644
--- a/torchgeo/trainers/byol.py
+++ b/torchgeo/trainers/byol.py
@@ -286,7 +286,7 @@ class BYOLTask(BaseTask):
 
     Reference implementation:
 
-    * https://github.com/deepmind/deepmind-research/tree/master/byol
+    * https://github.com/google-deepmind/deepmind-research/tree/master/byol
 
     If you use this trainer in your research, please cite the following paper:
 
diff --git a/torchgeo/transforms/indices.py b/torchgeo/transforms/indices.py
index d04385d6ad1..ac3fee56fff 100644
--- a/torchgeo/transforms/indices.py
+++ b/torchgeo/transforms/indices.py
@@ -74,7 +74,7 @@ class AppendNBR(AppendNormalizedDifferenceIndex):
 
     If you use this index in your research, please cite the following paper:
 
-    * https://www.sciencebase.gov/catalog/item/4f4e4b20e4b07f02db6abb36
+    * https://www.yumpu.com/en/document/view/24226870/the-normalized-burn-ratio-and-relationships-to-burn-severity-/7
 
     .. versionadded:: 0.2
     """