diff --git a/notebooks/tutorials/zonal-statistics-validation.ipynb b/notebooks/tutorials/zonal-statistics-validation.ipynb
index e6c75a33..561a0406 100644
--- a/notebooks/tutorials/zonal-statistics-validation.ipynb
+++ b/notebooks/tutorials/zonal-statistics-validation.ipynb
@@ -296,7 +296,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 15/15 [00:07<00:00,  1.91it/s]\n"
+      "100%|██████████| 15/15 [00:07<00:00,  1.90it/s]\n"
      ]
     }
    ],
@@ -405,7 +405,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Compute zonal averages using TiTiler API"
+    "## Compute zonal averages using TiTiler API\n",
+    "\n",
+    "We make use of the option on TiTiler to reproject the data subset to an equal-area projection ([Equal Area Cylindrical](https://proj.org/en/9.3/operations/projections/cea.html)) before computing the statistics."
    ]
   },
   {
@@ -413,6 +415,15 @@
    "execution_count": 13,
    "metadata": {},
    "outputs": [],
+   "source": [
+    "WORKING_PROJECTION = \"+proj=cea\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "def generate_stats(item, geojson, asset_name, params=None):\n",
     "    params = params or {}\n",
@@ -434,7 +445,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {
     "tags": []
    },
@@ -443,7 +454,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 15/15 [00:06<00:00,  2.16it/s]\n"
+      "100%|██████████| 15/15 [00:15<00:00,  1.04s/it]\n"
      ]
     }
    ],
@@ -454,7 +465,7 @@
     "for item in tqdm.tqdm(items):\n",
     "    # generate stats with and without reprojection\n",
     "    stats_noproj = generate_stats(item, AOI, ASSET_NAME)\n",
-    "    stats_proj = generate_stats(item, AOI, ASSET_NAME, params={\"dst_crs\": \"+proj=cea\"})\n",
+    "    stats_proj = generate_stats(item, AOI, ASSET_NAME, params={\"dst_crs\": WORKING_PROJECTION})\n",
     "\n",
     "    timeseries_titiler_noproj.append(stats_noproj)\n",
     "    timeseries_titiler_proj.append(stats_proj)"
@@ -462,7 +473,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {
     "tags": []
    },
@@ -478,7 +489,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {
     "tags": []
    },
@@ -497,7 +508,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {
     "tags": []
    },
@@ -510,7 +521,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {
     "tags": []
    },
@@ -540,7 +551,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {
     "tags": []
    },
@@ -575,7 +586,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {
     "tags": []
    },
@@ -591,7 +602,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {
     "tags": []
    },