diff --git a/ecoscope/analysis/seasons.py b/ecoscope/analysis/seasons.py
index 2ef062ee..449eb319 100644
--- a/ecoscope/analysis/seasons.py
+++ b/ecoscope/analysis/seasons.py
@@ -20,20 +20,34 @@ def _min_max_scaler(x):
     return x_std
 
 
-def std_ndvi_vals(aoi=None, start=None, end=None):
-    coll = ee.ImageCollection("MODIS/MCD43A4_006_NDVI").select("NDVI").filterDate(start, end)
+def std_ndvi_vals(
+    aoi=None,
+    img_coll=None,
+    band=None,
+    img_scale=1,
+    start=None,
+    end=None
+):
+  
+    coll = ee.ImageCollection(img_coll).select(band).filterDate(start, end).map(lambda x: x.multiply(
+        ee.Image(img_scale)).set("system:time_start", x.get("system:time_start")))
 
+    if aoi:
+      geo = ee.Feature(shapely.geometry.mapping(aoi)).geometry()
+    else:
+      geo = None
+    
     ndvi_vals = (
         coll.toBands()
-        .reduceRegion("mean", ee.Feature(shapely.geometry.mapping(aoi)).geometry(), bestEffort=True)
+        .reduceRegion("mean", geo, bestEffort=True)
         .values()
         .getInfo()
     )
-    ndvi_vals_std = _min_max_scaler(ndvi_vals)
+    
     return pd.DataFrame(
         {
             "img_date": pd.to_datetime(coll.aggregate_array("system:time_start").getInfo(), unit="ms", utc=True),
-            "NDVI": ndvi_vals_std,
+            "NDVI": ndvi_vals,
         }
     ).dropna(axis=0)