diff --git a/ocf_datapipes/select/select_spatial_slice.py b/ocf_datapipes/select/select_spatial_slice.py
index 5cf883d03..b29bc45e4 100644
--- a/ocf_datapipes/select/select_spatial_slice.py
+++ b/ocf_datapipes/select/select_spatial_slice.py
@@ -103,24 +103,33 @@ def _get_idx_of_pixel_closest_to_poi(
 
 def _get_idx_of_pixel_closest_to_poi_geostationary(
     xr_data: xr.DataArray,
-    center_osgb: Location,
+    center_coordinate: Location,
 ) -> Location:
     """
     Return x and y index location of pixel at center of region of interest.
 
     Args:
         xr_data: Xarray dataset
-        center_osgb: Center in OSGB coordinates
+        center_coordinate: Central coordinate
 
     Returns:
         Location for the center pixel in geostationary coordinates
     """
-
     xr_coords, xr_x_dim, xr_y_dim = spatial_coord_type(xr_data)
+    if center_coordinate.coordinate_system == "osgb":
+        x, y = osgb_to_geostationary_area_coords(x=center_coordinate.x, 
+                                                 y=center_coordinate.y,
+                                                 xr_data=xr_data)
+    elif center_coordinate.coordinate_system == "lon_lat":
+        x, y = lon_lat_to_geostationary_area_coords(x=center_coordinate.x,
+                                                    y=center_coordinate.y,
+                                                    xr_data=xr_data)
+    else:
+        raise NotImplementedError(f"Only 'osgb' and 'lon_lat' location coordinates are \
+                                  supported in conversion to geostationary \
+                                   - not '{center_coordinate.coordinate_system}'")
 
-    x, y = osgb_to_geostationary_area_coords(x=center_osgb.x, y=center_osgb.y, xr_data=xr_data)
     center_geostationary = Location(x=x, y=y, coordinate_system="geostationary")
-
     # Check that the requested point lies within the data
     assert xr_data[xr_x_dim].min() < x < xr_data[xr_x_dim].max()
     assert xr_data[xr_y_dim].min() < y < xr_data[xr_y_dim].max()
@@ -390,7 +399,7 @@ def select_spatial_slice_pixels(
         if xr_coords == "geostationary":
             center_idx: Location = _get_idx_of_pixel_closest_to_poi_geostationary(
                 xr_data=xr_data,
-                center_osgb=location,
+                center_coordinate=location,
             )
         else:
             center_idx: Location = _get_idx_of_pixel_closest_to_poi(
diff --git a/tests/select/test_select_spatial_slice.py b/tests/select/test_select_spatial_slice.py
index cdb3a89f2..0d408fe1f 100644
--- a/tests/select/test_select_spatial_slice.py
+++ b/tests/select/test_select_spatial_slice.py
@@ -1,14 +1,16 @@
 import numpy as np
 import xarray as xr
-from ocf_datapipes.utils import Location
 
 from ocf_datapipes.select import (
     PickLocations,
     SelectSpatialSliceMeters,
     SelectSpatialSlicePixels,
 )
-
-from ocf_datapipes.select.select_spatial_slice import slice_spatial_pixel_window_from_xarray
+from ocf_datapipes.select.select_spatial_slice import (
+    _get_idx_of_pixel_closest_to_poi_geostationary,
+    slice_spatial_pixel_window_from_xarray,
+)
+from ocf_datapipes.utils import Location
 
 
 def test_slice_spatial_pixel_window_from_xarray_function():
@@ -158,3 +160,27 @@ def test_select_spatial_slice_meters_icon_global(passiv_datapipe, icon_global_da
     # ICON global has roughly 13km spacing, so this should be around 7x7 grid
     assert len(data.longitude) == 49
     assert len(data.latitude) == 49
+
+def test_get_idx_of_pixel_closest_to_poi_geostationary_lon_lat_location():
+    # Create dummy data
+    x = np.arange(5000000, -5000000, -5000)
+    y = np.arange(5000000, -5000000, -5000)[::-1]
+
+    xr_data = xr.Dataset(
+        data_vars=dict(
+            data=(["x_geostationary", "y_geostationary"], np.random.normal(size=(len(x), len(y)))),
+        ),
+        coords=dict(
+            x_geostationary=(["x_geostationary"], x),
+            y_geostationary=(["y_geostationary"], y),
+        ),
+    )
+    xr_data.attrs["area"] = 'msg_seviri_iodc_3km:\n  description: MSG SEVIRI Indian Ocean Data Coverage service area definition with\n    3 km resolution\n  projection:\n    proj: geos\n    lon_0: 41.5\n    h: 35785831\n    x_0: 0\n    y_0: 0\n    a: 6378169\n    rf: 295.488065897014\n    no_defs: null\n    type: crs\n  shape:\n    height: 3712\n    width: 3712\n  area_extent:\n    lower_left_xy: [5000000, 5000000]\n    upper_right_xy: [-5000000, -5000000]\n    units: m\n'
+
+
+    center = Location(x=77.1, y=28.6, coordinate_system="lon_lat")
+
+    location_center_idx = _get_idx_of_pixel_closest_to_poi_geostationary(xr_data=xr_data, center_coordinate=center)
+
+    assert location_center_idx.coordinate_system == 'idx'
+    assert location_center_idx.x == 2000