diff --git a/xrspatial/tests/test_viewshed.py b/xrspatial/tests/test_viewshed.py
index 357a7dd1a..a914d4baa 100644
--- a/xrspatial/tests/test_viewshed.py
+++ b/xrspatial/tests/test_viewshed.py
@@ -580,6 +580,31 @@ def test_viewshed_custom_name(backend):
     assert result.name == "my_vs"
 
 
+@pytest.mark.parametrize("bad", [-1.0, -0.5, float("nan"),
+                                 float("inf"), float("-inf")])
+def test_viewshed_invalid_max_distance_raises(bad):
+    """Negative or non-finite max_distance raises a clear ValueError (#2855).
+
+    Validation lives at the public entry point, before backend dispatch,
+    so a single numpy raster covers every backend. Previously these
+    values fell through to confusing internal errors (e.g. "zero-size
+    array to reduction operation minimum" or "cannot convert float NaN
+    to integer").
+    """
+    raster = _make_raster("numpy")
+    with pytest.raises(ValueError, match="max_distance must be a finite"):
+        viewshed(raster, x=3, y=2, observer_elev=1, max_distance=bad)
+
+
+@pytest.mark.parametrize("backend", ["numpy", "dask+numpy"])
+@pytest.mark.parametrize("good", [0.0, 3.0])
+def test_viewshed_valid_max_distance_still_works(backend, good):
+    """Finite max_distance >= 0 passes validation and returns a result."""
+    raster = _make_raster(backend)
+    result = viewshed(raster, x=3, y=2, observer_elev=1, max_distance=good)
+    assert result.shape == raster.shape
+
+
 # -------------------------------------------------------------------
 # dask+cupy backend tests
 # -------------------------------------------------------------------
diff --git a/xrspatial/viewshed.py b/xrspatial/viewshed.py
index 1fbb4b294..e49939e07 100644
--- a/xrspatial/viewshed.py
+++ b/xrspatial/viewshed.py
@@ -1656,10 +1656,12 @@ def viewshed(raster: xarray.DataArray,
         when it is being analyzed for visibility.
     max_distance : float, optional
         Maximum analysis distance from the observer in surface units.
-        Cells beyond this distance are marked INVISIBLE without being
-        evaluated. When set and the raster is dask-backed, only the
-        chunks within the distance window are loaded — this is the most
-        efficient way to run viewshed on very large dask rasters.
+        Must be a finite number >= 0; a negative or non-finite value
+        raises ``ValueError``. Cells beyond this distance are marked
+        INVISIBLE without being evaluated. When set and the raster is
+        dask-backed, only the chunks within the distance window are
+        loaded — this is the most efficient way to run viewshed on very
+        large dask rasters.
     name : str, default='viewshed'
         Name of the output DataArray. Set on every backend so the
         result name does not depend on which backend ran.
@@ -1735,8 +1737,16 @@ def viewshed(raster: xarray.DataArray,
     """
     _validate_raster(raster, func_name='viewshed', name='raster')
 
-    # --- max_distance: extract spatial window for any backend ---
+    # --- max_distance: validate, then extract spatial window for any backend ---
     if max_distance is not None:
+        try:
+            is_bad = not np.isfinite(max_distance) or max_distance < 0
+        except (TypeError, ValueError):
+            is_bad = True
+        if is_bad:
+            raise ValueError(
+                "max_distance must be a finite number >= 0, "
+                f"got {max_distance!r}")
         return _viewshed_windowed(raster, x, y, observer_elev, target_elev,
                                   max_distance, name)