diff --git a/docs/api.rst b/docs/api.rst
index e078150..dd17a2a 100644
--- a/docs/api.rst
+++ b/docs/api.rst
@@ -38,6 +38,11 @@ Parameters
 
    Dataset.dggs.grid_info
    Dataset.dggs.params
+
+.. autosummary::
+   :toctree: generated
+   :template: autosummary/accessor_method.rst
+
    Dataset.dggs.decode
 
 Indexing
@@ -72,7 +77,12 @@ Parameters
 
    DataArray.dggs.grid_info
    DataArray.dggs.params
-   DataArray.dggs.decode
+
+.. autosummary::
+   :toctree: generated
+   :template: autosummary/accessor_method.rst
+
+   Dataset.dggs.decode
 
 Indexing
 --------
diff --git a/docs/conf.py b/docs/conf.py
index 8cc092e..867ed5a 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -115,6 +115,7 @@
     "healpy": ("https://healpy.readthedocs.io/en/latest", None),
     "cdshealpix-python": ("https://cds-astro.github.io/cds-healpix-python", None),
     "shapely": ("https://shapely.readthedocs.io/en/stable", None),
+    "healpix-geo": ("https://healpix-geo.readthedocs.io/en/latest", None),
 }
 
 # -- myst-nb options ---------------------------------------------------------
diff --git a/pixi.lock b/pixi.lock
index 28ba3d7..fef7e96 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -36,6 +36,7 @@ environments:
         - conda: https://conda.anaconda.org/conda-forge/linux-64/azure-storage-common-cpp-12.10.0-hebae86a_2.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/azure-storage-files-datalake-cpp-12.12.0-h8b27e44_3.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/blosc-1.21.6-he440d0b_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/bokeh-3.8.0-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-1.1.0-hb9d3cd8_3.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-bin-1.1.0-hb9d3cd8_3.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-python-1.1.0-py311hfdbb021_3.conda
@@ -50,17 +51,23 @@ environments:
         - conda: https://conda.anaconda.org/conda-forge/linux-64/cftime-1.6.4-py311h9f3472d_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/charset-normalizer-3.4.3-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/click-8.2.1-pyh707e725_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/cloudpickle-3.1.1-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/colorama-0.4.6-pyhd8ed1ab_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/comm-0.2.3-pyhe01879c_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/contourpy-1.3.3-py311hdf67eae_1.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/coverage-7.10.5-py311h3778330_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/cycler-0.12.1-pyhd8ed1ab_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/linux-64/cytoolz-1.0.1-py311h9ecbd09_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/dask-2025.7.0-pyhe01879c_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/dask-core-2025.7.0-pyhe01879c_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/decorator-5.2.1-pyhd8ed1ab_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/distributed-2025.7.0-pyhe01879c_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/exceptiongroup-1.3.0-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/execnet-2.1.1-pyhd8ed1ab_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/executing-2.2.0-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/fonttools-4.59.2-py311h3778330_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/freetype-2.13.3-ha770c72_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/fsspec-2025.7.0-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/geoarrow-c-0.3.0-py311h1ddb823_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/geoarrow-pyarrow-0.2.0-pyhd8ed1ab_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/geoarrow-types-0.3.0-pyhd8ed1ab_0.conda
@@ -73,15 +80,18 @@ environments:
         - conda: https://conda.anaconda.org/conda-forge/linux-64/h5py-3.14.0-nompi_py311h7f87ba5_100.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/hdf4-4.2.15-h2a13503_7.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/hdf5-1.14.6-nompi_h6e4c0c1_103.conda
+        - conda: https://conda.anaconda.org/conda-forge/linux-64/healpix-geo-0.0.6-py311h902ca64_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/hpack-4.1.0-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/hyperframe-6.1.0-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/hypothesis-6.138.7-pyha770c72_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/idna-3.10-pyhd8ed1ab_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/importlib-metadata-8.7.0-pyhe01879c_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/iniconfig-2.0.0-pyhd8ed1ab_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/ipython-9.5.0-pyhfa0c392_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/ipython_pygments_lexers-1.1.1-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/ipywidgets-8.1.7-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/jedi-0.19.2-pyhd8ed1ab_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/jinja2-3.1.6-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/jupyterlab_widgets-3.0.15-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/keyutils-1.6.3-hb9d3cd8_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/kiwisolver-1.4.9-py311h724c32c_1.conda
@@ -149,11 +159,16 @@ environments:
         - conda: https://conda.anaconda.org/conda-forge/linux-64/libxml2-2.13.8-h2cb61b6_1.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/libzip-1.11.2-h6991a6a_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/locket-1.0.0-pyhd8ed1ab_0.tar.bz2
         - conda: https://conda.anaconda.org/conda-forge/noarch/lonboard-0.11.1-pyh80e38bb_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/linux-64/lz4-4.4.4-py311h8c6ae76_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/lz4-c-1.10.0-h5888daf_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/linux-64/markupsafe-3.0.2-py311h2dc5d0c_1.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/matplotlib-base-3.10.5-py311h0f3be63_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/matplotlib-inline-0.1.7-pyhd8ed1ab_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/linux-64/msgpack-python-1.1.1-py311hdf67eae_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/munkres-1.1.4-pyhd8ed1ab_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/narwhals-2.2.0-pyhcf101f3_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/netcdf4-1.7.2-nompi_py311h8b974bf_102.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/nlohmann_json-3.12.0-h3f2d84a_0.conda
@@ -164,6 +179,7 @@ environments:
         - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/pandas-2.3.2-py311hed34c8f_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/parso-0.8.5-pyhcf101f3_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/partd-1.4.2-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/pexpect-4.9.0-pyhd8ed1ab_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/pickleshare-0.7.5-pyhd8ed1ab_1004.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/pillow-11.3.0-py311h1322bbf_0.conda
@@ -173,6 +189,7 @@ environments:
         - conda: https://conda.anaconda.org/conda-forge/linux-64/proj-9.6.2-h18fbb6c_2.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/prometheus-cpp-1.3.0-ha5d0236_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/prompt-toolkit-3.0.52-pyha770c72_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/linux-64/psutil-7.0.0-py311h49ec1c0_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/psygnal-0.14.1-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/pthread-stubs-0.4-hb9d3cd8_1002.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/ptyprocess-0.7.0-pyhd8ed1ab_1.conda
@@ -206,9 +223,12 @@ environments:
         - conda: https://conda.anaconda.org/conda-forge/noarch/sortedcontainers-2.4.0-pyhd8ed1ab_1.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/sqlite-3.50.4-hbc0de68_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/stack_data-0.6.3-pyhd8ed1ab_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/tblib-3.1.0-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_hd72426e_102.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/toml-0.10.2-pyhd8ed1ab_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.2.1-pyhe01879c_2.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/toolz-1.0.0-pyhd8ed1ab_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/linux-64/tornado-6.5.2-py311h49ec1c0_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/traitlets-5.14.3-pyhd8ed1ab_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/typing-extensions-4.15.0-h396c80c_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.15.0-pyhcf101f3_0.conda
@@ -221,7 +241,10 @@ environments:
         - conda: https://conda.anaconda.org/conda-forge/noarch/xarray-2025.8.0-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxau-1.0.12-hb9d3cd8_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxdmcp-1.1.5-hb9d3cd8_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/xyzservices-2025.4.0-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/yaml-0.2.5-h280c20c_3.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/zict-3.0.0-pyhd8ed1ab_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.23.0-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/zlib-1.3.1-hb9d3cd8_2.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/zstandard-0.23.0-py311h49ec1c0_3.conda
         - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb8e6e7a_2.conda
@@ -232,7 +255,7 @@ environments:
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/arro3-core-0.6.1-py311hc638b3f_0.conda
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/arro3-io-0.6.1-py311hc638b3f_0.conda
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/astropy-base-7.1.0-py311h5e5ef3f_0.conda
-        - conda: https://conda.anaconda.org/conda-forge/noarch/astropy-iers-data-0.2025.8.25.0.36.58-pyhd8ed1ab_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/astropy-iers-data-0.2025.9.1.0.42.11-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/asttokens-3.0.0-pyhd8ed1ab_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/attrs-25.3.0-pyh71513ae_0.conda
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/aws-c-auth-0.9.0-h9eee66f_19.conda
@@ -254,9 +277,10 @@ environments:
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/azure-storage-common-cpp-12.10.0-h12fd690_2.conda
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/azure-storage-files-datalake-cpp-12.12.0-h30213e0_3.conda
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/blosc-1.21.6-h7dd00d9_1.conda
-        - conda: https://conda.anaconda.org/conda-forge/osx-arm64/brotli-1.1.0-h5505292_3.conda
-        - conda: https://conda.anaconda.org/conda-forge/osx-arm64/brotli-bin-1.1.0-h5505292_3.conda
-        - conda: https://conda.anaconda.org/conda-forge/osx-arm64/brotli-python-1.1.0-py311h155a34a_3.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/bokeh-3.8.0-pyhd8ed1ab_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/osx-arm64/brotli-1.1.0-h6caf38d_4.conda
+        - conda: https://conda.anaconda.org/conda-forge/osx-arm64/brotli-bin-1.1.0-h6caf38d_4.conda
+        - conda: https://conda.anaconda.org/conda-forge/osx-arm64/brotli-python-1.1.0-py311hf719da1_4.conda
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-h99b78c6_7.conda
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/c-ares-1.34.5-h5505292_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.8.3-hbd8a1cb_0.conda
@@ -265,20 +289,26 @@ environments:
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/cdshealpix-0.7.1-py311hc638b3f_2.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/certifi-2025.8.3-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/cffi-1.17.1-py311h3a79f62_0.conda
-        - conda: https://conda.anaconda.org/conda-forge/osx-arm64/cftime-1.6.4-py311h0f07fe1_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/osx-arm64/cftime-1.6.4-py311h8b6d4dd_2.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/charset-normalizer-3.4.3-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/click-8.2.1-pyh707e725_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/cloudpickle-3.1.1-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/colorama-0.4.6-pyhd8ed1ab_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/comm-0.2.3-pyhe01879c_0.conda
-        - conda: https://conda.anaconda.org/conda-forge/osx-arm64/contourpy-1.3.3-py311h57a9ea7_1.conda
-        - conda: https://conda.anaconda.org/conda-forge/osx-arm64/coverage-7.10.5-py311h2fe624c_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/osx-arm64/contourpy-1.3.3-py311h57a9ea7_2.conda
+        - conda: https://conda.anaconda.org/conda-forge/osx-arm64/coverage-7.10.6-py311h2fe624c_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/cycler-0.12.1-pyhd8ed1ab_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/osx-arm64/cytoolz-1.0.1-py311h917b07b_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/dask-2025.7.0-pyhe01879c_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/dask-core-2025.7.0-pyhe01879c_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/decorator-5.2.1-pyhd8ed1ab_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/distributed-2025.7.0-pyhe01879c_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/exceptiongroup-1.3.0-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/execnet-2.1.1-pyhd8ed1ab_1.conda
-        - conda: https://conda.anaconda.org/conda-forge/noarch/executing-2.2.0-pyhd8ed1ab_0.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/executing-2.2.1-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/fonttools-4.59.2-py311h2fe624c_0.conda
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/freetype-2.13.3-hce30654_1.conda
+        - conda: https://conda.anaconda.org/conda-forge/noarch/fsspec-2025.7.0-pyhd8ed1ab_0.conda
         - conda: https://conda.anaconda.org/conda-forge/osx-arm64/geoarrow-c-0.3.0-py311hf719da1_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/geoarrow-pyarrow-0.2.0-pyhd8ed1ab_1.conda
         - conda: https://conda.anaconda.org/conda-forge/noarch/geoarrow-types-0.3.0-pyhd8ed1ab_0.conda
@@ -291,16 +321,19 @@ environments:
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+    sha256: a83c83f5e622a2f34fb1d179c55c3ff912429cd0a54f9f3190ae44a0fdba2ad2
+    md5: a15c62b8a306b8978f094f76da2f903f
+    depends:
+      - python >=3.9
+    license: BSD-2-Clause
+    license_family: BSD
+    purls:
+      - pkg:pypi/tblib?source=hash-mapping
+    size: 17914
+    timestamp: 1743515657639
   - conda: https://conda.anaconda.org/conda-forge/noarch/terminado-0.18.1-pyh0d859eb_0.conda
     sha256: b300557c0382478cf661ddb520263508e4b3b5871b471410450ef2846e8c352c
     md5: efba281bbdae5f6b0a1d53c6d4a97c93
@@ -16887,6 +17916,31 @@ packages:
       - pkg:pypi/tomli?source=compressed-mapping
     size: 21238
     timestamp: 1753796677376
+  - conda: https://conda.anaconda.org/conda-forge/noarch/toolz-1.0.0-pyhd8ed1ab_1.conda
+    sha256: eda38f423c33c2eaeca49ed946a8d3bf466cc3364970e083a65eb2fd85258d87
+    md5: 40d0ed782a8aaa16ef248e68c06c168d
+    depends:
+      - python >=3.9
+    license: BSD-3-Clause
+    license_family: BSD
+    purls:
+      - pkg:pypi/toolz?source=hash-mapping
+    size: 52475
+    timestamp: 1733736126261
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/tornado-6.5.2-py311h49ec1c0_0.conda
+    sha256: 99b43e96b71271bf906d87d9dceeb1b5d7f79d56d2cd58374e528b56830c99af
+    md5: 8e82bf1a7614ac43096a5c8d726030a3
+    depends:
+      - __glibc >=2.17,<3.0.a0
+      - libgcc >=14
+      - python >=3.11,<3.12.0a0
+      - python_abi 3.11.* *_cp311
+    license: Apache-2.0
+    license_family: Apache
+    purls:
+      - pkg:pypi/tornado?source=hash-mapping
+    size: 869655
+    timestamp: 1754732128935
   - conda: https://conda.anaconda.org/conda-forge/linux-64/tornado-6.5.2-py312h4c3975b_0.conda
     sha256: 891965f8e495ad5cef399db03a13df48df7add06ae131f4b77a88749c74b2060
     md5: 82dacd4832dcde0c2b7888248a3b3d7c
@@ -16915,6 +17969,34 @@ packages:
       - pkg:pypi/tornado?source=hash-mapping
     size: 878421
     timestamp: 1754732125966
+  - conda: https://conda.anaconda.org/conda-forge/osx-arm64/tornado-6.5.2-py311h3696347_0.conda
+    sha256: e174acd73e641bc71673b9d4793a2c0321206baafd7a76e92b011fdc85a67908
+    md5: cb8f3a7aa93ebc21113e2f6266d66c9c
+    depends:
+      - __osx >=11.0
+      - python >=3.11,<3.12.0a0
+      - python >=3.11,<3.12.0a0 *_cpython
+      - python_abi 3.11.* *_cp311
+    license: Apache-2.0
+    license_family: Apache
+    purls:
+      - pkg:pypi/tornado?source=hash-mapping
+    size: 871796
+    timestamp: 1754732249406
+  - conda: https://conda.anaconda.org/conda-forge/osx-arm64/tornado-6.5.2-py312h163523d_0.conda
+    sha256: 82ceea2527ac484f5c8d7dee95033935b7fecb0b42afb2d9538f7397404aa6d8
+    md5: 181a5ca410bad66be792da0e11038016
+    depends:
+      - __osx >=11.0
+      - python >=3.12,<3.13.0a0
+      - python >=3.12,<3.13.0a0 *_cpython
+      - python_abi 3.12.* *_cp312
+    license: Apache-2.0
+    license_family: Apache
+    purls:
+      - pkg:pypi/tornado?source=hash-mapping
+    size: 853490
+    timestamp: 1754732280524
   - conda: https://conda.anaconda.org/conda-forge/osx-arm64/tornado-6.5.2-py313hcdf3177_0.conda
     sha256: e687a470c8cea7815da666493cb6161948a7a1ae118237624db7689612732a04
     md5: d086389c0d48b2751361720665321eeb
@@ -16929,6 +18011,36 @@ packages:
       - pkg:pypi/tornado?source=hash-mapping
     size: 875854
     timestamp: 1754732465438
+  - conda: https://conda.anaconda.org/conda-forge/win-64/tornado-6.5.2-py311h3485c13_0.conda
+    sha256: 288fc2b231d4b9895fefb50066881531a8d148f5cb01aa99eb9d335bf00b6447
+    md5: 4f7ddc08f9282d519d5c1316e540d4ad
+    depends:
+      - python >=3.11,<3.12.0a0
+      - python_abi 3.11.* *_cp311
+      - ucrt >=10.0.20348.0
+      - vc >=14.3,<15
+      - vc14_runtime >=14.44.35208
+    license: Apache-2.0
+    license_family: Apache
+    purls:
+      - pkg:pypi/tornado?source=hash-mapping
+    size: 874287
+    timestamp: 1754732248470
+  - conda: https://conda.anaconda.org/conda-forge/win-64/tornado-6.5.2-py312he06e257_0.conda
+    sha256: bc5f5b20aa13e3ba343685c54d75a02c737ae6a5fe778908caf563d9f2273cb2
+    md5: ef13034aef592637ce6e2dc1ca126bca
+    depends:
+      - python >=3.12,<3.13.0a0
+      - python_abi 3.12.* *_cp312
+      - ucrt >=10.0.20348.0
+      - vc >=14.3,<15
+      - vc14_runtime >=14.44.35208
+    license: Apache-2.0
+    license_family: Apache
+    purls:
+      - pkg:pypi/tornado?source=hash-mapping
+    size: 855809
+    timestamp: 1754732413384
   - conda: https://conda.anaconda.org/conda-forge/win-64/tornado-6.5.2-py313h5ea7bf4_0.conda
     sha256: 6a461f7ffba2f0d90bca775fc95f58840c9b3ed3d6002659f4979a4a7b7ed344
     md5: 57756431d27f6043d8bc1e78eb8b3c7b
@@ -16998,11 +18110,6 @@ packages:
       - pkg:pypi/typing-utils?source=hash-mapping
     size: 15183
     timestamp: 1733331395943
-  - pypi: https://files.pythonhosted.org/packages/5c/23/c7abc0ca0a1526a0774eca151daeb8de62ec457e77262b66b359c3c7679e/tzdata-2025.2-py2.py3-none-any.whl
-    name: tzdata
-    version: "2025.2"
-    sha256: 1a403fada01ff9221ca8044d701868fa132215d84beb92242d9acd2147f667a8
-    requires_python: ">=2"
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025b-h78e105d_0.conda
     sha256: 5aaa366385d716557e365f0a4e9c3fca43ba196872abbbe3d56bb610d131e192
     md5: 4222072737ccff51314b5ece9c7d6f5a
@@ -17048,9 +18155,9 @@ packages:
       - pkg:pypi/unicodedata2?source=hash-mapping
     size: 404401
     timestamp: 1736692621599
-  - conda: https://conda.anaconda.org/conda-forge/osx-arm64/unicodedata2-16.0.0-py311h917b07b_0.conda
-    sha256: 4edd8c92ea579b8b5997e4b6159271dc47ce4826e880b8f8eec52be88619b03f
-    md5: d1e4a3605a1ca37cb73937772c5310af
+  - conda: https://conda.anaconda.org/conda-forge/osx-arm64/unicodedata2-16.0.0-py311h3696347_1.conda
+    sha256: 800e8ed94f2d771b006891b5af4c4b510c4cab49e8966ac08297b68d904f0e15
+    md5: 348a90d4b670542a7757e2415021bcf0
     depends:
       - __osx >=11.0
       - python >=3.11,<3.12.0a0
@@ -17060,11 +18167,11 @@ packages:
     license_family: Apache
     purls:
       - pkg:pypi/unicodedata2?source=hash-mapping
-    size: 411234
-    timestamp: 1736692763548
-  - conda: https://conda.anaconda.org/conda-forge/osx-arm64/unicodedata2-16.0.0-py312hea69d52_0.conda
-    sha256: c6ca9ea11eecc650df4bce4b3daa843821def6d753eeab6d81de35bb43f9d984
-    md5: 9a835052506b91ea8f0d8e352cd12246
+    size: 410696
+    timestamp: 1756494744297
+  - conda: https://conda.anaconda.org/conda-forge/osx-arm64/unicodedata2-16.0.0-py312h163523d_1.conda
+    sha256: 6620dfce63e763460d586f8b04c986e2318a58d6be06f30591a0d41902dd39cf
+    md5: e7e792c655daeca54a98cf44fe0bbb5a
     depends:
       - __osx >=11.0
       - python >=3.12,<3.13.0a0
@@ -17074,8 +18181,8 @@ packages:
     license_family: Apache
     purls:
       - pkg:pypi/unicodedata2?source=hash-mapping
-    size: 409745
-    timestamp: 1736692768349
+    size: 410699
+    timestamp: 1756494753956
   - conda: https://conda.anaconda.org/conda-forge/win-64/unicodedata2-16.0.0-py311he736701_0.conda
     sha256: 3f626553bfb49ac756cf40e0c10ecb3a915a86f64e036924ab956b37ad1fa9f4
     md5: 5ec4da89151e9d55f9ecad019f2d1e58
@@ -17325,6 +18432,7 @@ packages:
       - __osx >=11.0
       - python_abi 3.13.* *_cp313
     license: BSD-3-Clause
+    license_family: BSD
     purls:
       - pkg:pypi/websockets?source=hash-mapping
     size: 367500
@@ -17550,6 +18658,52 @@ packages:
       - types-pytz ; extra == 'types'
       - types-setuptools ; extra == 'types'
     requires_python: ">=3.11"
+  - pypi: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/xarray/2025.8.1.dev19+g9107078f3/xarray-2025.8.1.dev19+g9107078f3-py3-none-any.whl
+    name: xarray
+    version: 2025.8.1.dev19+g9107078f3
+    requires_dist:
+      - numpy>=1.26
+      - packaging>=24.1
+      - pandas>=2.2
+      - scipy>=1.13 ; extra == 'accel'
+      - bottleneck ; extra == 'accel'
+      - numbagg>=0.8 ; extra == 'accel'
+      - numba>=0.59 ; extra == 'accel'
+      - flox>=0.9 ; extra == 'accel'
+      - opt-einsum ; extra == 'accel'
+      - numpy<2.3 ; extra == 'accel'
+      - xarray[accel,etc,io,parallel,viz] ; extra == 'complete'
+      - netcdf4>=1.6.0 ; extra == 'io'
+      - h5netcdf ; extra == 'io'
+      - pydap ; extra == 'io'
+      - scipy>=1.13 ; extra == 'io'
+      - zarr>=2.18 ; extra == 'io'
+      - fsspec ; extra == 'io'
+      - cftime ; extra == 'io'
+      - pooch ; extra == 'io'
+      - sparse>=0.15 ; extra == 'etc'
+      - dask[complete] ; extra == 'parallel'
+      - cartopy>=0.23 ; extra == 'viz'
+      - matplotlib ; extra == 'viz'
+      - nc-time-axis ; extra == 'viz'
+      - seaborn ; extra == 'viz'
+      - pandas-stubs ; extra == 'types'
+      - scipy-stubs ; extra == 'types'
+      - types-pyyaml ; extra == 'types'
+      - types-pygments ; extra == 'types'
+      - types-colorama ; extra == 'types'
+      - types-decorator ; extra == 'types'
+      - types-defusedxml ; extra == 'types'
+      - types-docutils ; extra == 'types'
+      - types-networkx ; extra == 'types'
+      - types-pexpect ; extra == 'types'
+      - types-psutil ; extra == 'types'
+      - types-pycurl ; extra == 'types'
+      - types-openpyxl ; extra == 'types'
+      - types-python-dateutil ; extra == 'types'
+      - types-pytz ; extra == 'types'
+      - types-setuptools ; extra == 'types'
+    requires_python: ">=3.11"
   - conda: https://conda.anaconda.org/conda-forge/noarch/xarray-2025.8.0-pyhd8ed1ab_0.conda
     sha256: 91c476aab9f878a243b4edb31a3cf6c7bb4e873ff537315f475769b890bbbb29
     md5: a7b1b2ffdbf18922945874ccbe1420aa
@@ -17587,14 +18741,16 @@ packages:
     timestamp: 1755208520958
   - pypi: ./
     name: xdggs
-    version: 0.2.2.dev10+g09f90a854.d20250901
-    sha256: d806d023ac603e79080900639e991f910ab7ee673e1caebac49356d128f0d299
+    version: 0.2.2.dev85+gab8093648
+    sha256: a9978a9a2a31c571d9f1a5c95899f21ecb2caee96d6c344b2f467ff672e89a8f
     requires_dist:
       - arro3-core>=0.4.0
       - cdshealpix
       - h3ronpy
+      - healpix-geo>=0.0.6
       - lonboard>=0.9.3
       - matplotlib
+      - numpy>=2.0
       - pooch
       - pyproj>=3.3
       - xarray
@@ -17666,6 +18822,17 @@ packages:
     purls: []
     size: 69920
     timestamp: 1727795651979
+  - conda: https://conda.anaconda.org/conda-forge/noarch/xyzservices-2025.4.0-pyhd8ed1ab_0.conda
+    sha256: ac6d4d4133b1e0f69075158cdf00fccad20e29fc6cc45faa480cec37a84af6ae
+    md5: 5663fa346821cd06dc1ece2c2600be2c
+    depends:
+      - python >=3.8
+    license: BSD-3-Clause
+    license_family: BSD
+    purls:
+      - pkg:pypi/xyzservices?source=hash-mapping
+    size: 49477
+    timestamp: 1745598150265
   - conda: https://conda.anaconda.org/conda-forge/linux-64/yaml-0.2.5-h280c20c_3.conda
     sha256: 6d9ea2f731e284e9316d95fa61869fe7bbba33df7929f82693c121022810f4ad
     md5: a77f85f77be52ff59391544bfe73390a
@@ -17743,6 +18910,17 @@ packages:
     purls: []
     size: 2527503
     timestamp: 1731585151036
+  - conda: https://conda.anaconda.org/conda-forge/noarch/zict-3.0.0-pyhd8ed1ab_1.conda
+    sha256: 5488542dceeb9f2874e726646548ecc5608060934d6f9ceaa7c6a48c61f9cc8d
+    md5: e52c2ef711ccf31bb7f70ca87d144b9e
+    depends:
+      - python >=3.9
+    license: BSD-3-Clause
+    license_family: BSD
+    purls:
+      - pkg:pypi/zict?source=hash-mapping
+    size: 36341
+    timestamp: 1733261642963
   - conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.23.0-pyhd8ed1ab_0.conda
     sha256: 7560d21e1b021fd40b65bfb72f67945a3fcb83d78ad7ccf37b8b3165ec3b68ad
     md5: df5e78d904988eb55042c0c97446079f
diff --git a/pyproject.toml b/pyproject.toml
index 2c8e067..578fd2e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -24,7 +24,9 @@ classifiers = [
 requires-python = ">=3.11"
 dependencies = [
   "xarray",
+  "numpy>=2.0",
   "cdshealpix",
+  "healpix-geo>=0.0.6",
   "h3ronpy",
   "lonboard>=0.9.3",
   "pyproj>=3.3",
@@ -119,7 +121,7 @@ filterwarnings = [
 
 [tool.pixi.workspace]
 channels = ["conda-forge"]
-platforms = ["linux-64", "osx-arm64", "win-64"]
+platforms = ["linux-64", "win-64", "osx-arm64"]
 
 [tool.pixi.system-requirements]
 libc = { family = "glibc", version = "2.34" }
@@ -138,6 +140,7 @@ pyproj = ">=3.3"
 matplotlib-base = ">=3.10.5"
 arro3-core = ">=0.4.0"
 pooch = ">=1.8.2"
+healpix-geo = ">=0.0.6"
 
 [tool.pixi.feature.tests.dependencies]
 pytest = "*"
@@ -148,6 +151,7 @@ netcdf4 = "*"
 hypothesis = "*"
 geoarrow-pyarrow = "*"
 shapely = ">=2.1.1,<3"
+dask = ">=2025.7.0"
 
 [tool.pixi.feature.tests.tasks]
 tests = "pytest -n auto --cov=xdggs"
@@ -164,6 +168,7 @@ pandas = "*"
 pyarrow = "*"
 h3ronpy = { git = "git+https://github.com/keewis/h3ronpy.git", subdirectory = "h3ronpy", rev = "version" }
 cdshealpix = { git = "git+https://github.com/cds-astro/cds-healpix-python.git" }
+healpix-geo = { git = "git+https://github.com/eopf-dggs/healpix-geo.git" }
 astropy = { git = "git+https://github.com/astropy/astropy.git" }
 
 [tool.pixi.feature.nightly.dependencies]
diff --git a/xdggs/accessor.py b/xdggs/accessor.py
index 1852c98..7f92f01 100644
--- a/xdggs/accessor.py
+++ b/xdggs/accessor.py
@@ -29,7 +29,9 @@ def __init__(self, obj: xr.Dataset | xr.DataArray):
         self._name = name
         self._index = index
 
-    def decode(self, grid_info=None, *, name="cell_ids") -> xr.Dataset | xr.DataArray:
+    def decode(
+        self, grid_info=None, *, name="cell_ids", index_options=None, **index_kwargs
+    ) -> xr.Dataset | xr.DataArray:
         """decode the DGGS cell ids
 
         Parameters
@@ -39,6 +41,8 @@ def decode(self, grid_info=None, *, name="cell_ids") -> xr.Dataset | xr.DataArra
             the dataset.
         name : str, default: "cell_ids"
             The name of the coordinate containing the cell ids.
+        index_options, **index_kwargs : dict, optional
+            Additional options to forward to the index.
 
         Returns
         -------
@@ -51,7 +55,12 @@ def decode(self, grid_info=None, *, name="cell_ids") -> xr.Dataset | xr.DataArra
         if isinstance(grid_info, dict):
             var.attrs = grid_info
 
-        return self._obj.drop_indexes(name, errors="ignore").set_xindex(name, DGGSIndex)
+        if index_options is None:
+            index_options = {}
+
+        return self._obj.drop_indexes(name, errors="ignore").set_xindex(
+            name, DGGSIndex, **(index_options | index_kwargs)
+        )
 
     @property
     def index(self) -> DGGSIndex:
diff --git a/xdggs/h3.py b/xdggs/h3.py
index 0868ed9..8cfcaa2 100644
--- a/xdggs/h3.py
+++ b/xdggs/h3.py
@@ -18,7 +18,6 @@
         cells_to_wkb_polygons,
         coordinates_to_cells,
     )
-from xarray.indexes import PandasIndex
 
 from xdggs.grid import DGGSInfo, translate_parameters
 from xdggs.index import DGGSIndex
@@ -203,7 +202,7 @@ class H3Index(DGGSIndex):
 
     def __init__(
         self,
-        cell_ids: Any | PandasIndex,
+        cell_ids: Any | xr.Index,
         dim: str,
         grid_info: DGGSInfo,
     ):
@@ -226,8 +225,8 @@ def from_variables(
     def grid_info(self) -> H3Info:
         return self._grid
 
-    def _replace(self, new_pd_index: PandasIndex):
-        return type(self)(new_pd_index, self._dim, self._grid)
+    def _replace(self, new_index: xr.Index):
+        return type(self)(new_index, self._dim, self._grid)
 
     def _repr_inline_(self, max_width: int):
         return f"H3Index(level={self._grid.level})"
diff --git a/xdggs/healpix.py b/xdggs/healpix.py
index 632b1e2..f9fa40c 100644
--- a/xdggs/healpix.py
+++ b/xdggs/healpix.py
@@ -1,5 +1,5 @@
 import json
-from collections.abc import Mapping
+from collections.abc import Hashable, Mapping
 from dataclasses import dataclass
 from typing import Any, ClassVar, Literal, Self, TypeVar
 
@@ -7,7 +7,8 @@
 import cdshealpix.ring
 import numpy as np
 import xarray as xr
-from xarray.indexes import PandasIndex
+from healpix_geo.nested import RangeMOCIndex
+from xarray.core.indexes import IndexSelResult, PandasIndex
 
 from xdggs.grid import DGGSInfo, translate_parameters
 from xdggs.index import DGGSIndex
@@ -16,6 +17,13 @@
 
 T = TypeVar("T")
 
+try:
+    import dask.array as da
+
+    dask_array_type = (da.Array,)
+except ImportError:
+    dask_array_type = ()
+
 
 def polygons_shapely(vertices):
     import shapely
@@ -107,12 +115,12 @@ class HealpixInfo(DGGSInfo):
     level: int
     """int : The hierarchical level of the grid"""
 
-    indexing_scheme: Literal["nested", "ring", "unique"] = "nested"
+    indexing_scheme: Literal["nested", "ring"] = "nested"
     """int : The indexing scheme of the grid"""
 
     valid_parameters: ClassVar[dict[str, Any]] = {
         "level": range(0, 29 + 1),
-        "indexing_scheme": ["nested", "ring", "unique"],
+        "indexing_scheme": ["nested", "ring"],
     }
 
     def __post_init__(self):
@@ -304,18 +312,353 @@ def cell_boundaries(self, cell_ids: Any, backend="shapely") -> np.ndarray:
         return backend_func(vertices)
 
 
+def construct_chunk_ranges(chunks, until):
+    start = 0
+
+    for chunksize in chunks:
+        stop = start + chunksize
+        if stop > until:
+            stop = until
+            if start == stop:
+                break
+
+        if until - start < chunksize:
+            chunksize = until - start
+
+        yield chunksize, slice(start, stop)
+        start = stop
+
+
+def subset_chunks(chunks, indexer):
+    def _subset_slice(offset, chunk, indexer):
+        if offset >= indexer.stop or offset + chunk < indexer.start:
+            # outside slice
+            return 0
+        elif offset >= indexer.start and offset + chunk < indexer.stop:
+            # full chunk
+            return chunk
+        else:
+            # partial chunk
+            left_trim = indexer.start - offset
+            right_trim = offset + chunk - indexer.stop
+
+            if left_trim < 0:
+                left_trim = 0
+
+            if right_trim < 0:
+                right_trim = 0
+
+            return chunk - left_trim - right_trim
+
+    def _subset_array(offset, chunk, indexer):
+        mask = (indexer >= offset) & (indexer < offset + chunk)
+
+        return np.sum(mask.astype(int))
+
+    def _subset(offset, chunk, indexer):
+        if isinstance(indexer, slice):
+            return _subset_slice(offset, chunk, indexer)
+        else:
+            return _subset_array(offset, chunk, indexer)
+
+    if chunks is None:
+        return None
+
+    chunk_offsets = np.cumulative_sum(chunks, include_initial=True)
+    total_length = chunk_offsets[-1]
+
+    if isinstance(indexer, slice):
+        indexer = slice(*indexer.indices(total_length))
+
+    trimmed_chunks = tuple(
+        _subset(offset, chunk, indexer)
+        for offset, chunk in zip(chunk_offsets[:-1], chunks)
+    )
+
+    return tuple(int(chunk) for chunk in trimmed_chunks if chunk > 0)
+
+
+def extract_chunk(index, slice_):
+    return index.isel(slice_).cell_ids()
+
+
+# optionally replaces the PandasIndex within HealpixIndex
+class HealpixMocIndex(xr.Index):
+    """More efficient index for healpix cell ids based on a MOC
+
+    This uses the rust `moc crate <https://crates.io/crates/moc>`_ to represent
+    cell ids as a set of disconnected ranges at level 29, vastly reducing the
+    memory footprint and computation time of set-like operations.
+
+    .. warning::
+
+       Only supported for the ``nested`` scheme.
+
+    See Also
+    --------
+    healpix_geo.nested.RangeMOCIndex
+        The low-level implementation of the index functionality.
+    """
+
+    def __init__(self, index, *, dim, name, grid_info, chunksizes):
+        self._index = index
+        self._dim = dim
+        self._grid_info = grid_info
+        self._name = name
+        self._chunksizes = chunksizes
+
+    @property
+    def size(self):
+        """The number of indexed cells."""
+        return self._index.size
+
+    @property
+    def nbytes(self):
+        """The number of bytes occupied by the index.
+
+        .. note::
+           This does not take any (constant) overhead into account.
+        """
+        return self._index.nbytes
+
+    @property
+    def chunksizes(self):
+        """The size of the chunks of the indexed coordinate."""
+        return self._chunksizes
+
+    @classmethod
+    def from_array(cls, array, *, dim, name, grid_info):
+        """Construct an index from a raw array.
+
+        Parameters
+        ----------
+        array : array-like
+            The array of cell ids as uint64. If the size is equal to the total
+            number of cells at the given refinement level, creates a full domain
+            index without looking at the cell ids. If a chunked array, it will
+            create indexes for each chunk and then merge the chunk indexes
+            in-memory.
+        dim : hashable
+            The dimension of the index.
+        name : hashable
+            The name of the indexed coordinate.
+        grid_info : xdggs.HealpixInfo
+            The grid parameters.
+
+        Returns
+        -------
+        index : HealpixMocIndex
+            The resulting index.
+        """
+        if grid_info.indexing_scheme != "nested":
+            raise ValueError(
+                "The MOC index currently only supports the 'nested' scheme"
+            )
+
+        if array.ndim != 1:
+            raise ValueError("only 1D cell ids are supported")
+
+        if array.size == 12 * 4**grid_info.level:
+            index = RangeMOCIndex.full_domain(grid_info.level)
+        elif isinstance(array, dask_array_type):
+            from functools import reduce
+
+            import dask
+
+            [indexes] = dask.compute(
+                dask.delayed(RangeMOCIndex.from_cell_ids)(grid_info.level, chunk)
+                for chunk in array.astype("uint64").to_delayed()
+            )
+            index = reduce(RangeMOCIndex.union, indexes)
+        else:
+            index = RangeMOCIndex.from_cell_ids(grid_info.level, array.astype("uint64"))
+
+        chunksizes = {dim: array.chunks[0] if hasattr(array, "chunks") else None}
+        return cls(
+            index, dim=dim, name=name, grid_info=grid_info, chunksizes=chunksizes
+        )
+
+    def _replace(self, index, chunksizes):
+        return type(self)(
+            index,
+            dim=self._dim,
+            name=self._name,
+            grid_info=self._grid_info,
+            chunksizes=chunksizes,
+        )
+
+    @classmethod
+    def from_variables(cls, variables, *, options):
+        """Create a new index object from the cell id coordinate variable
+
+        Parameters
+        ----------
+        variables : dict-like
+            Mapping of :py:class:`Variable` objects holding the coordinate labels
+            to index.
+        options : dict-like
+            Mapping of arbitrary options to pass to the HealpixInfo object.
+
+        Returns
+        -------
+        index : Index
+            A new Index object.
+        """
+        name, var, dim = _extract_cell_id_variable(variables)
+        grid_info = HealpixInfo.from_dict(var.attrs | options)
+
+        return cls.from_array(var.data, dim=dim, name=name, grid_info=grid_info)
+
+    def create_variables(self, variables):
+        """Create new coordinate variables from this index
+
+        Parameters
+        ----------
+        variables : dict-like, optional
+            Mapping of :py:class:`Variable` objects.
+
+        Returns
+        -------
+        index_variables : dict-like
+            Dictionary of :py:class:`Variable` objects.
+        """
+        name = self._name
+        if variables is not None and name in variables:
+            var = variables[name]
+            attrs = var.attrs
+            encoding = var.encoding
+        else:
+            attrs = None
+            encoding = None
+
+        chunks = self._chunksizes[self._dim]
+        if chunks is not None:
+            import dask
+            import dask.array as da
+
+            chunk_arrays = [
+                da.from_delayed(
+                    dask.delayed(extract_chunk)(self._index, slice_),
+                    shape=(chunksize,),
+                    dtype="uint64",
+                    name=f"chunk-{index}",
+                    meta=np.array((), dtype="uint64"),
+                )
+                for index, (chunksize, slice_) in enumerate(
+                    construct_chunk_ranges(chunks, self._index.size)
+                )
+            ]
+            data = da.concatenate(chunk_arrays, axis=0)
+            var = xr.Variable(self._dim, data, attrs=attrs, encoding=encoding)
+        else:
+            var = xr.Variable(
+                self._dim, self._index.cell_ids(), attrs=attrs, encoding=encoding
+            )
+
+        return {name: var}
+
+    def isel(self, indexers):
+        """Subset the index using positional indexers.
+
+        Parameters
+        ----------
+        indexers : dict-like
+            A dictionary of positional indexers as passed from
+            :py:meth:`Dataset.isel` and where the entries have been filtered for
+            the current index.
+
+        Returns
+        -------
+        maybe_index : Index
+            A new Index object or ``None``.
+        """
+        indexer = indexers[self._dim]
+        if isinstance(indexer, np.ndarray):
+            if np.isdtype(indexer.dtype, "signed integer"):
+                indexer = np.where(indexer >= 0, indexer, self.size + indexer).astype(
+                    "uint64"
+                )
+            elif np.isdtype(indexer.dtype, "unsigned integer"):
+                indexer = indexer.astype("uint64")
+            else:
+                raise ValueError("can only index with integer arrays or slices")
+
+        new_chunksizes = {
+            self._dim: subset_chunks(self._chunksizes[self._dim], indexer)
+        }
+
+        return self._replace(self._index.isel(indexer), chunksizes=new_chunksizes)
+
+    def sel(self, labels: dict[Hashable, Any]) -> IndexSelResult:
+        """Query the index using cell ids.
+
+        Parameters
+        ----------
+        labels : dict-like of hashable to slice or array-like
+            A dictionary of coordinate label indexers passed from
+            :py:meth:`Dataset.sel` and where the entries have been filtered
+            for the current index.
+
+        Returns
+        -------
+        sel_results : :py:class:`IndexSelResult`
+            An index query result object that contains dimension positional indexers.
+            It may also contain new indexes, coordinate variables, etc.
+        """
+        indexer = labels[self._name]
+        if isinstance(indexer, np.ndarray):
+            if np.isdtype(indexer.dtype, "signed integer"):
+                if np.any(indexer < 0):
+                    raise ValueError("Cell ids can't be negative")
+
+                indexer = np.astype(indexer, "uint64")
+            elif np.isdtype(indexer.dtype, "unsigned integer"):
+                indexer = np.astype(indexer, "uint64")
+            else:
+                raise ValueError("Can only index with cell id arrays or slices")
+
+        dim_indexer, new_index = self._index.sel(indexer)
+        new_chunksizes = {
+            self._dim: subset_chunks(self._chunksizes[self._dim], dim_indexer)
+        }
+
+        return IndexSelResult(
+            dim_indexers={self._dim: dim_indexer},
+            indexes={self._name: self._replace(new_index, chunksizes=new_chunksizes)},
+        )
+
+
 @register_dggs("healpix")
 class HealpixIndex(DGGSIndex):
     def __init__(
         self,
-        cell_ids: Any | PandasIndex,
+        cell_ids: Any | xr.Index,
         dim: str,
         grid_info: DGGSInfo,
+        index_kind: str = "pandas",
     ):
         if not isinstance(grid_info, HealpixInfo):
             raise ValueError(f"grid info object has an invalid type: {type(grid_info)}")
 
-        super().__init__(cell_ids, dim, grid_info)
+        self._dim = dim
+
+        if isinstance(cell_ids, xr.Index):
+            self._index = cell_ids
+        elif index_kind == "pandas":
+            self._index = PandasIndex(cell_ids, dim)
+        elif index_kind == "moc":
+            self._index = HealpixMocIndex.from_array(
+                cell_ids, dim=dim, grid_info=grid_info, name="cell_ids"
+            )
+        self._kind = index_kind
+
+        self._grid = grid_info
+
+    def values(self):
+        if self._kind == "moc":
+            return self._index._index.cell_ids()
+        else:
+            return self._index.index.values
 
     @classmethod
     def from_variables(
@@ -326,16 +669,21 @@ def from_variables(
     ) -> "HealpixIndex":
         _, var, dim = _extract_cell_id_variable(variables)
 
+        index_kind = options.pop("index_kind", "pandas")
+
         grid_info = HealpixInfo.from_dict(var.attrs | options)
 
-        return cls(var.data, dim, grid_info)
+        return cls(var.data, dim, grid_info, index_kind=index_kind)
+
+    def create_variables(self, variables):
+        return self._index.create_variables(variables)
 
-    def _replace(self, new_pd_index: PandasIndex):
-        return type(self)(new_pd_index, self._dim, self._grid)
+    def _replace(self, new_index: xr.Index):
+        return type(self)(new_index, self._dim, self._grid, index_kind=self._kind)
 
     @property
     def grid_info(self) -> HealpixInfo:
         return self._grid
 
     def _repr_inline_(self, max_width: int):
-        return f"HealpixIndex(level={self._grid.level}, indexing_scheme={self._grid.indexing_scheme})"
+        return f"HealpixIndex(level={self._grid.level}, indexing_scheme={self._grid.indexing_scheme}, kind={self._kind})"
diff --git a/xdggs/index.py b/xdggs/index.py
index 9b1fcef..bfcd9de 100644
--- a/xdggs/index.py
+++ b/xdggs/index.py
@@ -9,7 +9,7 @@
 from xdggs.utils import GRID_REGISTRY, _extract_cell_id_variable
 
 
-def decode(ds, grid_info=None, *, name="cell_ids"):
+def decode(ds, grid_info=None, *, name="cell_ids", index_options=None, **index_kwargs):
     """
     decode grid parameters and create a DGGS index
 
@@ -23,6 +23,8 @@ def decode(ds, grid_info=None, *, name="cell_ids"):
         the dataset.
     name : str, default: "cell_ids"
         The name of the coordinate containing the cell ids.
+    index_options, **index_kwargs : dict, optional
+        Additional options to forward to the index.
 
     Returns
     -------
@@ -34,20 +36,25 @@ def decode(ds, grid_info=None, *, name="cell_ids"):
     xarray.Dataset.dggs.decode
     xarray.DataArray.dggs.decode
     """
-    return ds.dggs.decode(name=name, grid_info=grid_info)
+    if index_options is None:
+        index_options = {}
+
+    return ds.dggs.decode(
+        name=name, grid_info=grid_info, index_options=index_options | index_kwargs
+    )
 
 
 class DGGSIndex(Index):
     _dim: str
-    _pd_index: PandasIndex
+    _index: xr.Index
 
-    def __init__(self, cell_ids: Any | PandasIndex, dim: str, grid_info: DGGSInfo):
+    def __init__(self, cell_ids: Any | xr.Index, dim: str, grid_info: DGGSInfo):
         self._dim = dim
 
-        if isinstance(cell_ids, PandasIndex):
-            self._pd_index = cell_ids
+        if isinstance(cell_ids, xr.Index):
+            self._index = cell_ids
         else:
-            self._pd_index = PandasIndex(cell_ids, dim)
+            self._index = PandasIndex(cell_ids, dim)
 
         self._grid = grid_info
 
@@ -66,37 +73,41 @@ def from_variables(
             raise ValueError(f"unknown DGGS grid name: {grid_name}")
 
         index = cls.from_variables(variables, options=options)
-        index._pd_index.index.name = name
+        if isinstance(index._index, PandasIndex):
+            index._index.index.name = name
 
         return index
 
+    def values(self):
+        return self._index.index.values
+
     def create_variables(
         self, variables: Mapping[Any, xr.Variable] | None = None
     ) -> dict[Hashable, xr.Variable]:
-        return self._pd_index.create_variables(variables)
+        return self._index.create_variables(variables)
 
     def isel(
         self: "DGGSIndex", indexers: Mapping[Any, int | np.ndarray | xr.Variable]
     ) -> Union["DGGSIndex", None]:
-        new_pd_index = self._pd_index.isel(indexers)
-        if new_pd_index is not None:
-            return self._replace(new_pd_index)
+        new_index = self._index.isel(indexers)
+        if new_index is not None:
+            return self._replace(new_index)
         else:
             return None
 
     def sel(self, labels, method=None, tolerance=None):
         if method == "nearest":
             raise ValueError("finding nearest grid cell has no meaning")
-        return self._pd_index.sel(labels, method=method, tolerance=tolerance)
+        return self._index.sel(labels, method=method, tolerance=tolerance)
 
-    def _replace(self, new_pd_index: PandasIndex):
+    def _replace(self, new_index: PandasIndex):
         raise NotImplementedError()
 
     def cell_centers(self) -> tuple[np.ndarray, np.ndarray]:
-        return self._grid.cell_ids2geographic(self._pd_index.index.values)
+        return self._grid.cell_ids2geographic(self.values())
 
     def cell_boundaries(self) -> np.ndarray:
-        return self.grid_info.cell_boundaries(self._pd_index.index.values)
+        return self.grid_info.cell_boundaries(self.values())
 
     @property
     def grid_info(self) -> DGGSInfo:
diff --git a/xdggs/tests/__init__.py b/xdggs/tests/__init__.py
index 1a19348..1d767c0 100644
--- a/xdggs/tests/__init__.py
+++ b/xdggs/tests/__init__.py
@@ -1,4 +1,7 @@
+from contextlib import nullcontext
+
 import geoarrow.pyarrow as ga
+import pytest
 import shapely
 
 from xdggs.tests.matchers import (  # noqa: F401
@@ -7,6 +10,52 @@
     assert_exceptions_equal,
 )
 
+try:
+    import dask
+    import dask.array as da
+
+    has_dask = True
+except ImportError:
+    dask = None
+
+    class da:
+        @staticmethod
+        def arange(*args, **kwargs):
+            pass
+
+    has_dask = False
+
+
+# vendored from xarray
+class CountingScheduler:
+    """Simple dask scheduler counting the number of computes.
+
+    Reference: https://stackoverflow.com/questions/53289286/"""
+
+    def __init__(self, max_computes=0):
+        self.total_computes = 0
+        self.max_computes = max_computes
+
+    def __call__(self, dsk, keys, **kwargs):
+        self.total_computes += 1
+        if self.total_computes > self.max_computes:
+            raise RuntimeError(
+                f"Too many computes. Total: {self.total_computes} > max: {self.max_computes}."
+            )
+        return dask.get(dsk, keys, **kwargs)
+
+
+requires_dask = pytest.mark.skipif(not has_dask, reason="requires dask")
+
 
 def geoarrow_to_shapely(arr):
     return shapely.from_wkb(ga.as_wkb(arr))
+
+
+# vendored from xarray
+def raise_if_dask_computes(max_computes=0):
+    # return a dummy context manager so that this can be used for non-dask objects
+    if not has_dask:
+        return nullcontext()
+    scheduler = CountingScheduler(max_computes)
+    return dask.config.set(scheduler=scheduler)
diff --git a/xdggs/tests/test_h3.py b/xdggs/tests/test_h3.py
index e1c2629..c58c020 100644
--- a/xdggs/tests/test_h3.py
+++ b/xdggs/tests/test_h3.py
@@ -221,8 +221,8 @@ def test_init(cell_ids, dim, level):
     assert index._dim == dim
 
     # TODO: how do we check the index, if at all?
-    assert index._pd_index.dim == dim
-    assert np.all(index._pd_index.index.values == cell_ids)
+    assert index._index.dim == dim
+    assert np.all(index._index.index.values == cell_ids)
 
 
 @pytest.mark.parametrize("level", levels)
@@ -247,8 +247,8 @@ def test_from_variables(variable_name, variable, options):
     assert (index._dim,) == variable.dims
 
     # TODO: how do we check the index, if at all?
-    assert (index._pd_index.dim,) == variable.dims
-    assert np.all(index._pd_index.index.values == variable.data)
+    assert (index._index.dim,) == variable.dims
+    assert np.all(index._index.index.values == variable.data)
 
 
 @pytest.mark.parametrize(["old_variable", "new_variable"], variable_combinations)
@@ -267,7 +267,7 @@ def test_replace(old_variable, new_variable):
 
     assert new_index._grid == index._grid
     assert new_index._dim == index._dim
-    assert new_index._pd_index == new_pandas_index
+    assert new_index._index == new_pandas_index
 
 
 @pytest.mark.parametrize("max_width", [20, 50, 80, 120])
diff --git a/xdggs/tests/test_healpix.py b/xdggs/tests/test_healpix.py
index 23d190c..51e9842 100644
--- a/xdggs/tests/test_healpix.py
+++ b/xdggs/tests/test_healpix.py
@@ -12,7 +12,13 @@
 from xarray.core.indexes import PandasIndex
 
 from xdggs import healpix
-from xdggs.tests import assert_exceptions_equal, geoarrow_to_shapely
+from xdggs.tests import (
+    assert_exceptions_equal,
+    da,
+    geoarrow_to_shapely,
+    raise_if_dask_computes,
+    requires_dask,
+)
 
 
 # namespace class
@@ -460,9 +466,9 @@ def test_init(self, cell_ids, dim, grid) -> None:
 
         assert index._grid == grid
         assert index._dim == dim
-        assert index._pd_index.dim == dim
+        assert index._index.dim == dim
 
-        np.testing.assert_equal(index._pd_index.index.values, cell_ids)
+        np.testing.assert_equal(index._index.index.values, cell_ids)
 
     @given(strategies.grids())
     def test_grid(self, grid):
@@ -486,7 +492,20 @@ def test_from_variables(variable_name, variable, options) -> None:
     assert index._grid.indexing_scheme == expected_scheme
 
     assert (index._dim,) == variable.dims
-    np.testing.assert_equal(index._pd_index.index.values, variable.data)
+    np.testing.assert_equal(index._index.index.values, variable.data)
+
+
+def test_from_variables_moc() -> None:
+    level = 2
+    grid_info = {"grid_name": "healpix", "level": level, "indexing_scheme": "nested"}
+    variables = {"cell_ids": xr.Variable("cells", np.arange(12 * 4**level), grid_info)}
+
+    index = healpix.HealpixIndex.from_variables(
+        variables, options={"index_kind": "moc"}
+    )
+
+    assert isinstance(index._index, healpix.HealpixMocIndex)
+    assert index.grid_info.to_dict() == grid_info
 
 
 @pytest.mark.parametrize(["old_variable", "new_variable"], variable_combinations)
@@ -506,7 +525,7 @@ def test_replace(old_variable, new_variable) -> None:
     new_index = index._replace(new_pandas_index)
 
     assert new_index._dim == index._dim
-    assert new_index._pd_index == new_pandas_index
+    assert new_index._index == new_pandas_index
     assert index._grid == grid
 
 
@@ -521,3 +540,305 @@ def test_repr_inline(level, max_width) -> None:
     assert f"level={level}" in actual
     # ignore max_width for now
     # assert len(actual) <= max_width
+
+
+class TestHealpixMocIndex:
+    @pytest.mark.parametrize(
+        ["level", "cell_ids", "max_computes"],
+        (
+            pytest.param(
+                2, np.arange(12 * 4**2, dtype="uint64"), 1, id="numpy-2-full_domain"
+            ),
+            pytest.param(
+                2,
+                np.arange(3 * 4**2, 5 * 4**2, dtype="uint64"),
+                1,
+                id="numpy-2-region",
+            ),
+            pytest.param(
+                10,
+                da.arange(12 * 4**10, chunks=(4**6,), dtype="uint64"),
+                0,
+                marks=requires_dask,
+                id="dask-10-full_domain",
+            ),
+            pytest.param(
+                15,
+                da.arange(12 * 4**15, chunks=(4**10,), dtype="uint64"),
+                0,
+                marks=requires_dask,
+                id="dask-15-full_domain",
+            ),
+            pytest.param(
+                10,
+                da.arange(3 * 4**10, 5 * 4**10, chunks=(4**6,), dtype="uint64"),
+                1,
+                marks=requires_dask,
+                id="dask-10-region",
+            ),
+        ),
+    )
+    def test_from_array(self, level, cell_ids, max_computes):
+        grid_info = healpix.HealpixInfo(level=level, indexing_scheme="nested")
+
+        with raise_if_dask_computes(max_computes=max_computes):
+            index = healpix.HealpixMocIndex.from_array(
+                cell_ids, dim="cells", name="cell_ids", grid_info=grid_info
+            )
+
+        assert isinstance(index, healpix.HealpixMocIndex)
+        chunks = index.chunksizes["cells"]
+        assert chunks is None or isinstance(chunks[0], int)
+        assert index.size == cell_ids.size
+        assert index.nbytes == 16
+
+    def test_from_array_unsupported_indexing_scheme(self):
+        level = 1
+        cell_ids = np.arange(12 * 4**level, dtype="uint64")
+        grid_info = healpix.HealpixInfo(level=level, indexing_scheme="ring")
+
+        with pytest.raises(ValueError, match=".*only supports the 'nested' scheme"):
+            healpix.HealpixMocIndex.from_array(
+                cell_ids, dim="cells", name="cell_ids", grid_info=grid_info
+            )
+
+    @pytest.mark.parametrize("dask", [False, pytest.param(True, marks=requires_dask)])
+    @pytest.mark.parametrize(
+        ["level", "cell_ids"],
+        (
+            (
+                1,
+                np.array(
+                    [0, 1, 2, 3, 4, 5, 6, 7, 8, 22, 23, 24, 25, 43, 45, 46, 47],
+                    dtype="uint64",
+                ),
+            ),
+            (4, np.arange(12 * 4**4, dtype="uint64")),
+        ),
+    )
+    def test_from_variables(self, level, cell_ids, dask):
+        grid_info_mapping = {
+            "grid_name": "healpix",
+            "level": level,
+            "indexing_scheme": "nested",
+        }
+        variables = {"cell_ids": xr.Variable("cells", cell_ids, grid_info_mapping)}
+        if dask:
+            variables["cell_ids"] = variables["cell_ids"].chunk(4**level)
+
+        actual = healpix.HealpixMocIndex.from_variables(variables, options={})
+
+        assert isinstance(actual, healpix.HealpixMocIndex)
+        assert actual.size == cell_ids.size
+        np.testing.assert_equal(actual._index.cell_ids(), cell_ids)
+
+    @pytest.mark.parametrize(
+        "indexer",
+        (
+            slice(None),
+            slice(None, 4**1),
+            slice(2 * 4**1, 7 * 4**1),
+            slice(7, 25),
+            np.array([-4, -3, -2], dtype="int64"),
+            np.array([12, 13, 14, 15, 16], dtype="uint64"),
+            np.array([1, 2, 3, 4, 5], dtype="uint32"),
+        ),
+    )
+    @pytest.mark.parametrize(
+        "chunks",
+        [
+            pytest.param(None, id="none"),
+            pytest.param((12, 12, 12, 12), marks=requires_dask, id="equally_sized"),
+        ],
+    )
+    def test_isel(self, indexer, chunks):
+        from healpix_geo.nested import RangeMOCIndex
+
+        grid_info = healpix.HealpixInfo(level=1, indexing_scheme="nested")
+        cell_ids = np.arange(12 * 4**grid_info.level, dtype="uint64")
+        if chunks is None:
+            input_chunks = None
+            expected_chunks = None
+        else:
+            import dask.array as da
+
+            cell_ids_ = da.arange(
+                12 * 4**grid_info.level, dtype="uint64", chunks=chunks
+            )
+            input_chunks = cell_ids_.chunks[0]
+            expected_chunks = cell_ids_[indexer].chunks[0]
+
+        index = healpix.HealpixMocIndex(
+            RangeMOCIndex.from_cell_ids(grid_info.level, cell_ids),
+            dim="cells",
+            name="cell_ids",
+            grid_info=grid_info,
+            chunksizes={"cells": input_chunks},
+        )
+
+        actual = index.isel({"cells": indexer})
+        expected = healpix.HealpixMocIndex(
+            RangeMOCIndex.from_cell_ids(grid_info.level, cell_ids[indexer]),
+            dim="cells",
+            name="cell_ids",
+            grid_info=grid_info,
+            chunksizes={"cells": expected_chunks},
+        )
+
+        assert isinstance(actual, healpix.HealpixMocIndex)
+        assert actual.nbytes == expected.nbytes
+        assert actual.chunksizes == expected.chunksizes
+        np.testing.assert_equal(actual._index.cell_ids(), expected._index.cell_ids())
+
+    @pytest.mark.parametrize(
+        "chunks",
+        [
+            pytest.param((12, 12, 12, 12), marks=requires_dask),
+            pytest.param((18, 10, 10, 10), marks=requires_dask),
+            pytest.param((8, 12, 14, 14), marks=requires_dask),
+            None,
+        ],
+    )
+    def test_create_variables(self, chunks):
+        from healpix_geo.nested import RangeMOCIndex
+
+        grid_info = healpix.HealpixInfo(level=1, indexing_scheme="nested")
+        cell_ids = np.arange(12 * 4**grid_info.level, dtype="uint64")
+        indexer = slice(3 * 4**grid_info.level, 7 * 4**grid_info.level)
+        index = healpix.HealpixMocIndex(
+            RangeMOCIndex.from_cell_ids(grid_info.level, cell_ids[indexer]),
+            dim="cells",
+            name="cell_ids",
+            grid_info=grid_info,
+            chunksizes={"cells": chunks},
+        )
+
+        if chunks is not None:
+            variables = {
+                "cell_ids": xr.Variable("cells", cell_ids, grid_info.to_dict()).chunk(
+                    {"cells": chunks}
+                )
+            }
+        else:
+            variables = {
+                "cell_ids": xr.Variable("cells", cell_ids, grid_info.to_dict())
+            }
+
+        actual = index.create_variables(variables)
+        expected = {"cell_ids": variables["cell_ids"].isel(cells=indexer)}
+
+        assert actual.keys() == expected.keys()
+        xr.testing.assert_equal(actual["cell_ids"], expected["cell_ids"])
+
+    def test_create_variables_new(self):
+        from healpix_geo.nested import RangeMOCIndex
+
+        grid_info = healpix.HealpixInfo(level=1, indexing_scheme="nested")
+        cell_ids = np.arange(12 * 4**grid_info.level, dtype="uint64")
+        indexer = slice(3 * 4**grid_info.level, 7 * 4**grid_info.level)
+        index = healpix.HealpixMocIndex(
+            RangeMOCIndex.from_cell_ids(grid_info.level, cell_ids[indexer]),
+            dim="cells",
+            name="cell_ids",
+            grid_info=grid_info,
+            chunksizes={"cells": None},
+        )
+        actual = index.create_variables({})
+        expected = {"cell_ids": xr.Variable("cells", cell_ids[indexer])}
+
+        assert actual.keys() == expected.keys()
+        xr.testing.assert_equal(actual["cell_ids"], expected["cell_ids"])
+
+    @pytest.mark.parametrize(
+        "indexer",
+        (
+            slice(None),
+            slice(None, 4**1),
+            slice(2 * 4**1, 7 * 4**1),
+            slice(7, 25),
+            np.array([12, 13, 14, 15, 16], dtype="uint64"),
+            np.array([1, 2, 3, 4, 5], dtype="uint32"),
+        ),
+    )
+    @pytest.mark.parametrize(
+        "chunks",
+        [
+            pytest.param(None, id="none"),
+            pytest.param((12, 12, 12, 12), marks=requires_dask, id="equally_sized"),
+        ],
+    )
+    def test_sel(self, indexer, chunks):
+        from healpix_geo.nested import RangeMOCIndex
+
+        grid_info = healpix.HealpixInfo(level=1, indexing_scheme="nested")
+        cell_ids = np.arange(12 * 4**grid_info.level, dtype="uint64")
+
+        if isinstance(indexer, slice):
+            start, stop, step = indexer.indices(cell_ids.size)
+            if stop < cell_ids.size:
+                stop += 1
+
+            expected_indexer = slice(start, stop, step)
+        else:
+            expected_indexer = indexer
+
+        if chunks is None:
+            input_chunks = None
+            expected_chunks = None
+        else:
+            import dask.array as da
+
+            cell_ids_ = da.arange(
+                12 * 4**grid_info.level, dtype="uint64", chunks=chunks
+            )
+            input_chunks = cell_ids_.chunks[0]
+            expected_chunks = cell_ids_[expected_indexer].chunks[0]
+
+        index = healpix.HealpixMocIndex(
+            RangeMOCIndex.from_cell_ids(grid_info.level, cell_ids),
+            dim="cells",
+            name="cell_ids",
+            grid_info=grid_info,
+            chunksizes={"cells": input_chunks},
+        )
+
+        result = index.sel({"cell_ids": indexer})
+        actual = result.indexes["cell_ids"]
+        actual_indexer = result.dim_indexers["cells"]
+
+        expected = healpix.HealpixMocIndex(
+            RangeMOCIndex.from_cell_ids(grid_info.level, cell_ids[expected_indexer]),
+            dim="cells",
+            name="cell_ids",
+            grid_info=grid_info,
+            chunksizes={"cells": expected_chunks},
+        )
+
+        if isinstance(actual_indexer, slice):
+            assert actual_indexer == expected_indexer
+        else:
+            np.testing.assert_equal(actual_indexer, expected_indexer)
+
+        assert isinstance(actual, healpix.HealpixMocIndex)
+        assert actual.nbytes == expected.nbytes
+        assert actual.chunksizes == expected.chunksizes
+        np.testing.assert_equal(actual._index.cell_ids(), expected._index.cell_ids())
+
+    def test_sel_error(self):
+        from healpix_geo.nested import RangeMOCIndex
+
+        grid_info = healpix.HealpixInfo(level=1, indexing_scheme="nested")
+        cell_ids = np.arange(12 * 4**grid_info.level, dtype="uint64")
+
+        index = healpix.HealpixMocIndex(
+            RangeMOCIndex.from_cell_ids(grid_info.level, cell_ids),
+            dim="cells",
+            name="cell_ids",
+            grid_info=grid_info,
+            chunksizes={"cells": None},
+        )
+
+        indexer = np.array([-4, 2, 1], dtype="int64")
+
+        with pytest.raises(ValueError, match="Cell ids can't be negative"):
+            index.sel({"cell_ids": indexer})