From 3b163667d6a4c23befbf10ea0a1e91975b979ab5 Mon Sep 17 00:00:00 2001
From: "Azadpour, Elmera" <eazadpour@usgs.gov>
Date: Fri, 4 Oct 2024 14:20:25 -0700
Subject: [PATCH] add python notebook to make slider
---
...t 9 Slider - Unequal access to water.ipynb | 226 ++++++++++++++++++
1 file changed, 226 insertions(+)
create mode 100644 2021 NLCD Pasture and Croplands vs Landsat 9 Slider - Unequal access to water.ipynb
diff --git a/2021 NLCD Pasture and Croplands vs Landsat 9 Slider - Unequal access to water.ipynb b/2021 NLCD Pasture and Croplands vs Landsat 9 Slider - Unequal access to water.ipynb
new file mode 100644
index 0000000..756f9e7
--- /dev/null
+++ b/2021 NLCD Pasture and Croplands vs Landsat 9 Slider - Unequal access to water.ipynb
@@ -0,0 +1,226 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "1",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# pip install geemap\n",
+ "# pip install ee "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "2",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Import the Earth Engine (ee) module, which allows interaction with Google Earth Engine.\n",
+ "import ee\n",
+ "\n",
+ "# Import the geemap module, which provides a Python interface for interactive mapping with Google Earth Engine.\n",
+ "import geemap"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "3",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "c6e926d803204b36ac0901c05b331082",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Map(center=[40, -100], controls=(WidgetControl(options=['position', 'transparent_bg'], widget=HBox(children=(T…"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Add baseamp\n",
+ "# Note: Earth Engine will notify you to authorize access from a google account. More info here: https://developers.google.com/earth-engine/guides/access\n",
+ "Map = geemap.Map(center=[40,-100], zoom=4)\n",
+ "Map.add_basemap('CartoDB.DarkMatterNoLabels')\n",
+ "Map"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "id": "02297066",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Import the NLCD collection\n",
+ "dataset = ee.ImageCollection('USGS/NLCD_RELEASES/2021_REL/NLCD')\n",
+ "\n",
+ "# Filter collection\n",
+ "nlcd2021 = dataset.filter(ee.Filter.eq('system:index', '2021')).first()\n",
+ "\n",
+ "# Select land cover band\n",
+ "landcover = nlcd2021.select('landcover')\n",
+ "\n",
+ "# Load US states FeatureCollection\n",
+ "states = ee.FeatureCollection('TIGER/2018/States')\n",
+ "\n",
+ "# Filter the states to include only the specified states, West of the Mississippi River \n",
+ "state_list = ['Washington', 'Oregon', 'California', 'Idaho', 'Nevada', \n",
+ " 'Utah', 'Arizona', 'Montana', 'Wyoming', 'Colorado', \n",
+ " 'New Mexico', 'North Dakota', 'South Dakota', 'Nebraska', \n",
+ " 'Kansas', 'Oklahoma', 'Texas', 'Minnesota', 'Iowa', \n",
+ " 'Missouri', 'Arkansas', 'Louisiana']\n",
+ "\n",
+ "selected_states = states.filter(ee.Filter.inList('NAME', state_list))\n",
+ "\n",
+ "# Clip the land cover data to the selected states\n",
+ "landcover_clipped = landcover.clipToCollection(selected_states)\n",
+ "\n",
+ "# Create a mask for Pasture/Hay (81) and Cultivated Crops (82)\n",
+ "mask = landcover_clipped.eq(81).Or(landcover_clipped.eq(82))\n",
+ "\n",
+ "# Apply the mask to keep only the desired classes\n",
+ "landcover_filtered = landcover_clipped.updateMask(mask)\n",
+ "\n",
+ "# Display the filtered land cover data - select \n",
+ "Map.addLayer(landcover_filtered, {'min': 0, 'max': 82, 'palette': ['white', 'green', 'green']}, 'NLCD 2021 Pasture/Hay & Cultivated Crops')\n",
+ "\n",
+ "# Center the map over the filtered data\n",
+ "Map.centerObject(landcover_filtered)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "id": "c9f2b271",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "c6e926d803204b36ac0901c05b331082",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Map(bottom=992.0, center=[50.28933925329178, -82.08984375000001], controls=(WidgetControl(options=['position',…"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Load the Landsat 9 ImageCollection (Level 2, Tier 1 data) from Google Earth Engine.\n",
+ "collection = ee.ImageCollection(\"LANDSAT/LC09/C02/T1_L2\")\n",
+ "\n",
+ "# Compute the median value for each pixel across the collection. This helps to reduce noise like clouds.\n",
+ "median = collection.median()\n",
+ "\n",
+ "# Function to apply scale factors to the Landsat image bands for optical and thermal corrections.\n",
+ "def apply_scale_factors(image):\n",
+ " # Scale optical bands (surface reflectance) by multiplying by 0.0000275 and adding an offset of -0.2.\n",
+ " opticalBands = image.select(\"SR_B.\").multiply(0.0000275).add(-0.2)\n",
+ " \n",
+ " # Scale thermal bands (brightness temperature) by multiplying by 0.00341802 and adding an offset of 149.0.\n",
+ " thermalBands = image.select(\"ST_B.*\").multiply(0.00341802).add(149.0)\n",
+ " \n",
+ " # Add the scaled optical and thermal bands back to the image, replacing the original bands.\n",
+ " return image.addBands(opticalBands, None, True).addBands(thermalBands, None, True)\n",
+ "\n",
+ "# Apply the scale factors to the median Landsat image.\n",
+ "landsat = apply_scale_factors(median)\n",
+ "\n",
+ "# Clip the Landsat image to a selected region (in this case, to the selected states).\n",
+ "landsat_clipped = landsat.clipToCollection(selected_states)\n",
+ "\n",
+ "# Define visualization parameters for displaying the image in natural color (bands 4, 3, and 2 for red, green, blue).\n",
+ "vis_natural = {\n",
+ " \"bands\": [\"SR_B4\", \"SR_B3\", \"SR_B2\"], # Specify the bands for the true color image (red, green, blue).\n",
+ " \"min\": 0.0, # Minimum reflectance value for visualization.\n",
+ " \"max\": 0.3, # Maximum reflectance value for visualization.\n",
+ "}\n",
+ "\n",
+ "# Add the clipped Landsat image to the map using the true color visualization.\n",
+ "Map.addLayer(landsat_clipped, vis_natural, \"Landsat 9 True Color (432)\")\n",
+ "\n",
+ "# Display the map.\n",
+ "Map"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "id": "2bbe12a5",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "m = geemap.Map(center=[40, -100], zoom=4)\n",
+ "m.add_basemap('CartoDB.DarkMatterNoLabels')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "id": "c374e86f",
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "4a9aec747ad94aa4ab01a251dcde18c5",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Map(center=[40, -100], controls=(ZoomControl(options=['position', 'zoom_in_text', 'zoom_in_title', 'zoom_out_t…"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Create split panel map with NLCD 2021 Pasture/Hay & Cultivated Crop on left and Landsat 2021 on right\n",
+ "# Apply teal color pallete for NLCD that corresponds to Living Conditions \n",
+ "left_layer = geemap.ee_tile_layer(landcover_filtered,{'min': 0, 'max': 82, 'palette': ['white', '#45a196', '#45a196']}, name= 'NLCD 2021 Pasture/Hay & Cultivated Crops')\n",
+ "right_layer = geemap.ee_tile_layer(landsat_clipped, vis_natural, name=\"Landsat 2021\")\n",
+ "\n",
+ "m.split_map(left_layer, right_layer)\n",
+ "m\n"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.15"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
--
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