From d18f0794de18f4242b8a0cfffeb174d7113d3711 Mon Sep 17 00:00:00 2001
From: Robbi Bishop-Taylor <Robbi.BishopTaylor@ga.gov.au>
Date: Thu, 17 Oct 2024 23:25:46 +0000
Subject: [PATCH] Update notebook

---
 docs/notebooks/Case_study_intertidal.ipynb | 25 +++++++++++++++++++++-
 1 file changed, 24 insertions(+), 1 deletion(-)

diff --git a/docs/notebooks/Case_study_intertidal.ipynb b/docs/notebooks/Case_study_intertidal.ipynb
index dc0c92e..9e9f26d 100644
--- a/docs/notebooks/Case_study_intertidal.ipynb
+++ b/docs/notebooks/Case_study_intertidal.ipynb
@@ -4,7 +4,30 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Mapping the intertidal zone"
+    "# Mapping the intertidal zone\n",
+    "\n",
+    "The intertidal zone (i.e. the land along the coast that is periodically inundated by the tide) support important ecological habitats (e.g. sandy beaches and shores, tidal flats and rocky shores and reefs), and provide many valuable benefits such as storm surge protection, carbon storage and natural resources for recreational and commercial use.\n",
+    "However, intertidal zones are faced with increasing threats from coastal erosion, land reclamation (e.g. port construction), and sea level rise.\n",
+    "Accurate mapping data describing the spatial extents of the intertidal zone are essential for managing these environments, and predicting when and where these threats will have the greatest impact. \n",
+    "However, the intertidal zone is challenging and expensive to map at large scale using intensive manual survey methods - particularly across large coastal regions.\n",
+    "\n",
+    "Satellite Earth observation (EO) data is freely available for the entire planet, making satellite imagery a powerful and cost-effective tool for mapping the intertidal zone at regional, national scale or global scale.\n",
+    "This case study will demonstrate a simple **intertidal mapping workflow that combines free and open Landsat satellite data with tide modelling from `eo-tides`**. \n",
+    "The workflow includes:\n",
+    "\n",
+    "1. Loading a time-series of cloud-free satellite data from the cloud using `odc-stac`\n",
+    "2. Converting our satellite data to a remote sensing water index (NDWI)\n",
+    "3. [Modelling tides for each satellite image](../Satellite_data) and inspecting how these observed tides match up to the full local astronomical tide range\n",
+    "4. Filtering our satellite imagery to low and high tide observations\n",
+    "5. Combining noisy individual images into clean low and high tide median NDWI composites\n",
+    "6. Using these composites to extract the extent of the intertidal zone\n",
+    "\n",
+    "<div class=\"admonition tip\">\n",
+    "    <p class=\"admonition-title\">More information</p>\n",
+    "    <p>\n",
+    "        For more information about the workflows described below, refer to <a href=\"https://www.sciencedirect.com/science/article/pii/S0034425717301591a\">Sagar et al. 2017</a>, <a href=\"https://www.mdpi.com/2072-4292/10/3/480\">Sagar et al. 2018</a>, and <a href=\"https://www.sciencedirect.com/science/article/pii/S0272771418308783\">Bishop-Taylor et al. 2019</a>.\n",
+    "    </p>\n",
+    "</div>"
    ]
   },
   {