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| 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) | |