import ee import streamlit as st import geemap.foliumap as geemap WIDTH = 1060 HEIGHT = 600 def function(): st.write("Not implemented yet.") Map = geemap.Map() Map.to_streamlit(WIDTH, HEIGHT) def lulc_mrb_floodplain(): Map = geemap.Map() State_boundaries = ee.FeatureCollection( 'users/giswqs/MRB/State_Boundaries') State_style = State_boundaries.style(** {'color': '808080', 'width': 1, 'fillColor': '00000000'}) MRB_boundary = ee.FeatureCollection('users/giswqs/MRB/MRB_Boundary') MRB_style = MRB_boundary.style(** {'color': '000000', 'width': 2, 'fillColor': '00000000'}) floodplain = ee.Image('users/giswqs/MRB/USGS_Floodplain') class_values = [34, 38, 46, 50, 62] class_palette = ['c500ff', '00ffc5', '00a9e6', '73004d', '004d73'] img_1950 = ee.Image('users/giswqs/MRB/Major_Transitions_1941_1950') img_1950 = img_1950.set('b1_class_values', class_values) img_1950 = img_1950.set('b1_class_palette', class_palette) img_1960 = ee.Image('users/giswqs/MRB/Major_Transitions_1941_1960') img_1960 = img_1960.set('b1_class_values', class_values) img_1960 = img_1960.set('b1_class_palette', class_palette) img_1970 = ee.Image('users/giswqs/MRB/Major_Transitions_1941_1970') img_1970 = img_1970.set('b1_class_values', class_values) img_1970 = img_1970.set('b1_class_palette', class_palette) img_1980 = ee.Image('users/giswqs/MRB/Major_Transitions_1941_1980') img_1980 = img_1980.set('b1_class_values', class_values) img_1980 = img_1980.set('b1_class_palette', class_palette) img_1990 = ee.Image('users/giswqs/MRB/Major_Transitions_1941_1990') img_1990 = img_1990.set('b1_class_values', class_values) img_1990 = img_1990.set('b1_class_palette', class_palette) img_2000 = ee.Image('users/giswqs/MRB/Major_Transitions_1941_2000') img_2000 = img_2000.set('b1_class_values', class_values) img_2000 = img_2000.set('b1_class_palette', class_palette) Map.addLayer(floodplain, {'palette': ['cccccc']}, 'Floodplain', True, 0.5) Map.addLayer(img_2000, {}, 'Major Transitions 1941-2000') Map.addLayer(img_1990, {}, 'Major Transitions 1941-1990') Map.addLayer(img_1980, {}, 'Major Transitions 1941-1980') Map.addLayer(img_1970, {}, 'Major Transitions 1941-1970') Map.addLayer(img_1960, {}, 'Major Transitions 1941-1960') Map.addLayer(img_1950, {}, 'Major Transitions 1941-1950') Map.addLayer(State_style, {}, 'State Boundaries') Map.addLayer(MRB_style, {}, 'MRB Boundary') Map.to_streamlit(WIDTH, HEIGHT) def global_mangrove_watch(): """https://samapriya.github.io/awesome-gee-community-datasets/projects/mangrove/ """ Map = geemap.Map() gmw2007 = ee.FeatureCollection( "projects/sat-io/open-datasets/GMW/GMW_2007_v2") gmw2008 = ee.FeatureCollection( "projects/sat-io/open-datasets/GMW/GMW_2008_v2") gmw2009 = ee.FeatureCollection( "projects/sat-io/open-datasets/GMW/GMW_2009_v2") gmw2010 = ee.FeatureCollection( "projects/sat-io/open-datasets/GMW/GMW_2010_v2") gmw2015 = ee.FeatureCollection( "projects/sat-io/open-datasets/GMW/GMW_2015_v2") gmw2016 = ee.FeatureCollection( "projects/sat-io/open-datasets/GMW/GMW_2016_v2") gmw1996 = ee.FeatureCollection( "projects/sat-io/open-datasets/GMW/GMW_1996_v2") Map.addLayer(ee.Image().paint(gmw1996, 0, 3), { "palette": ["228B22"]}, 'Global Mangrove Watch 1996') Map.addLayer(ee.Image().paint(gmw2007, 0, 3), { "palette": ["228B22"]}, 'Global Mangrove Watch 2007') Map.addLayer(ee.Image().paint(gmw2008, 0, 3), { "palette": ["228B22"]}, 'Global Mangrove Watch 2008') Map.addLayer(ee.Image().paint(gmw2009, 0, 3), { "palette": ["228B22"]}, 'Global Mangrove Watch 2009') Map.addLayer(ee.Image().paint(gmw2010, 0, 3), { "palette": ["228B22"]}, 'Global Mangrove Watch 2010') Map.addLayer(ee.Image().paint(gmw2015, 0, 3), { "palette": ["228B22"]}, 'Global Mangrove Watch 2015') Map.addLayer(ee.Image().paint(gmw2016, 0, 3), { "palette": ["228B22"]}, 'Global Mangrove Watch 2015') Map.to_streamlit(WIDTH, HEIGHT) def app(): st.title("Awesome GEE Community Datasets") st.markdown(""" This app is for exploring the [Awesome GEE Community Datasets](https://samapriya.github.io/awesome-gee-community-datasets). Work in progress. """) datasets = { "Population & Socioeconomic": { "High Resolution Settlement Layer": "function()", "World Settlement Footprint (2015)": "function()", "Gridded Population of the World": "function()", "geoBoundaries Global Database": "function()", "West Africa Coastal Vulnerability Mapping": "function()", "Relative Wealth Index (RWI)": "function()", "Social Connectedness Index (SCI)": "function()", "Native Land (Indigenous Land Maps)": "function()", }, "Geophysical, Biological & Biogeochemical": { "Geomorpho90m Geomorphometric Layers": "function()", }, "Land Use and Land Cover": { "Global Mangrove Watch": "global_mangrove_watch()", "Mississippi River Basin Floodplain Land Use Change (1941-2000)": "lulc_mrb_floodplain()", }, "Hydrology": { "Global Shoreline Dataset": "function()", }, "Agriculture, Vegetation and Forestry": { "Landfire Mosaics LF v2.0.0": "function()", }, "Global Utilities, Assets and Amenities Layers": { "Global Power": "function()", }, "EarthEnv Biodiversity ecosystems & climate Layers": { "Global Consensus Landcover": "function()", }, "Weather and Climate Layers": { "Global Reference Evapotranspiration Layers": "function()", }, "Global Events Layers": { "Global Fire Atlas (2003-2016)": "function()", }, } row1_col1, row1_col2, _ = st.columns([1.2, 1.8, 1]) with row1_col1: category = st.selectbox("Select a category", datasets.keys(), index=2) with row1_col2: dataset = st.selectbox("Select a dataset", datasets[category].keys()) Map = geemap.Map() if dataset: eval(datasets[category][dataset]) else: Map = geemap.Map() Map.to_streamlit(WIDTH, HEIGHT)