diff --git a/kwcoco/cli/coco_stats.py b/kwcoco/cli/coco_stats.py
index 8f9a56b..ba4f6ad 100644
--- a/kwcoco/cli/coco_stats.py
+++ b/kwcoco/cli/coco_stats.py
@@ -27,6 +27,7 @@ class CocoStatsCLI(scfg.DataConfig):
     annot_attrs = scfg.Value(False, isflag=True, help='show annotation attribute information')
     image_attrs = scfg.Value(False, isflag=True, help='show image attribute information')
     video_attrs = scfg.Value(False, isflag=True, help='show video attribute information')
+    channels = scfg.Value(False, isflag=True, help='show channel and sensor information')
     io_workers = scfg.Value(0, help=ub.paragraph(
             '''
             number of workers when reading multiple kwcoco files
@@ -195,6 +196,17 @@ def main(cls, cmdline=True, **kw):
                 if human_readable:
                     print('hist(annot_attrs) = {}'.format(ub.urepr(attrs, nl=1)))
 
+        if config['channels']:
+            if human_readable:
+                print('Channel and sensor stats')
+            stat_types['channels'] = {}
+            for dset in datasets:
+                channel_info = _coco_channel_stats(dset)
+                stat_types['channels'][dset.tag] = channel_info
+                if human_readable:
+                    rich_print('dset.tag = {!r}'.format(dset.tag))
+                    rich_print(ub.urepr(channel_info, nl=2, sort=0))
+
         if config['boxes']:
             if human_readable:
                 print('Box stats')
@@ -331,6 +343,84 @@ def main(cls, cmdline=True, **kw):
         #         print(ub.urepr(dset.boxsize_stats(), nl=-1, precision=2))
 
 
+def _coco_channel_stats(coco_dset):
+    """
+    Return information about which channels and sensors are available.
+
+    This is a streamlined version of the richer geowatch stats, focused on
+    generic kwcoco datasets.
+
+    Example:
+        >>> import kwcoco
+        >>> from kwcoco.cli.coco_stats import _coco_channel_stats
+        >>> dset = kwcoco.CocoDataset()
+        >>> dset.add_category('a')
+        >>> gid1 = dset.add_image(file_name='img1.tif', sensor_coarse='S1', width=1, height=1)
+        >>> gid2 = dset.add_image(file_name='img2.tif', sensor_coarse='S2', width=1, height=1)
+        >>> dset.add_asset(gid=gid1, file_name='a1.tif', channels='red,green', width=1, height=1)
+        >>> dset.add_asset(gid=gid1, file_name='a2.tif', channels='blue', width=1, height=1)
+        >>> dset.add_asset(gid=gid2, file_name='b1.tif', channels='red,green', width=1, height=1)
+        >>> dset.add_asset(gid=gid2, file_name='b2.tif', channels='nir', width=1, height=1)
+        >>> info = _coco_channel_stats(dset)
+        >>> assert info['sensor_hist'] == {'S1': 1, 'S2': 1}
+        >>> assert info['chan_hist']['blue,red,green,unknown-chan'] == 1
+        >>> assert info['chan_hist']['nir,red,green,unknown-chan'] == 1
+        >>> assert info['common_channels'] == '<FusedChannelSpec(red|green|unknown-chan)>'
+        >>> assert info['all_channels'] == '<FusedChannelSpec(blue|red|green|unknown-chan|nir)>'
+    """
+    import kwcoco
+    from kwcoco.coco_image import CocoImage
+
+    sensor_hist = ub.ddict(int)
+    chan_hist = ub.ddict(int)
+    single_chan_hist = ub.ddict(int)
+    sensorchan_hist = ub.ddict(lambda: ub.ddict(int))
+    sensorchan_hist2 = ub.ddict(int)
+    for _gid, img in coco_dset.index.imgs.items():
+        coco_img: CocoImage = coco_dset.coco_image(_gid)
+        channels = []
+        for obj in coco_img.iter_asset_objs():
+            channels.append(obj.get('channels', 'unknown-chan'))
+        channels = sorted(channels)
+        chan = ','.join(channels)
+        sensor = img.get('sensor_coarse', '*')
+        chan_hist[chan] += 1
+        sensor_hist[sensor] += 1
+        sensorchan_hist[sensor][chan] += 1
+        sensorchan = f'{sensor}:({chan})'
+        sensorchan_hist2[sensorchan] += 1
+
+        for single_chan in kwcoco.ChannelSpec(chan).unique():
+            single_chan_hist[single_chan] += 1
+
+    CS = kwcoco.ChannelSpec
+    FS = kwcoco.FusedChannelSpec
+    osets = [CS.coerce(c).fuse().to_oset() for c in chan_hist]
+    if len(osets) == 0:
+        common_channels = FS.coerce([])
+        all_channels = FS.coerce([])
+        all_sensorchan = kwcoco.SensorChanSpec.coerce('')
+    else:
+        common_channels = FS.coerce(list(ub.oset.intersection(*osets))).concise()
+        all_channels = FS.coerce(list(ub.oset.union(*osets))).concise()
+        all_sensorchan = kwcoco.SensorChanSpec.late_fuse(*[
+            kwcoco.SensorChanSpec.coerce(s)
+            for s in sensorchan_hist2.keys()]).concise()
+
+    info = {
+        'single_chan_hist': {k: int(v) for k, v in single_chan_hist.items()},
+        'chan_hist': {k: int(v) for k, v in chan_hist.items()},
+        'sensor_hist': {k: int(v) for k, v in sensor_hist.items()},
+        'sensorchan_hist': {k: {k2: int(v2) for k2, v2 in v.items()}
+                            for k, v in sensorchan_hist.items()},
+        'sensorchan_hist2': {k: int(v) for k, v in sensorchan_hist2.items()},
+        'common_channels': str(common_channels),
+        'all_channels': str(all_channels),
+        'all_sensorchan': str(all_sensorchan),
+    }
+    return info
+
+
 def _dataset_disk_usage(dset):
     """
     Compute disk usage of all image assets referenced by this dataset.