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HUBiTable

"Keep Earth habitable through interactive geospatial intelligence."

Atlantis Together

Last edited 793 days ago by Atlantis Together.

"Your hub to make the right habits for a habitable planet, because the Earth is all of ours"

In an era of global interconnectedness, HUBiTable emerges as a beacon of data democratization, fostering open access, exploration, and visualization of GIS information that spans across the globe. Unlike traditional centralized platforms that limit participation and data ownership, HUBiTable embraces a decentralized architecture, empowering users to contribute, share, and co-create a unified repository of spatial data.

This decentralized paradigm not only ensures the integrity and accessibility of GIS data but also paves the way for seamless interoperability among diverse data sources and platforms. By breaking down data silos and promoting data sharing, HUBiTable fosters collaboration among researchers, policymakers, businesses, and individuals, enabling them to harness the power of geospatial information to address pressing challenges and drive innovation.

With HUBiTable, the world's GIS data becomes a shared resource, fueling informed decision-making, empowering sustainable development, and enriching our collective understanding of the planet we call home. Join us in unlocking the boundless potential of Earth's data with HUBiTable, the decentralized platform that empowers a data-driven world for all.

User Stories

User Stories

User Role

User "Prompt"

Layers

Benefit

Individual seeking an off-grid lifestyle

“Based on my location and living space (city, county, house, flat, garden, balcony, etc) how could I achieve an independent off-grid lifestyle”

The user can make informed decisions about their off-grid living arrangements based on data-driven insights, ensuring the feasibility and sustainability of their lifestyle choices (using geospatial data, such as climate, sunlight, wind, soil quality, water resources, and proximity to amenities.).

Individual seeking an off-grid lifestyle

“Show suitable locations matching complex filter”

City Planner

“Identify rooftops suitable for urban agriculture”

"Show me parks and green spaces in the city"

Analyze land use patterns, soil quality, and potential water sources to identify suitable locations for urban agriculture.

Quickly visualize the distribution of parks and green spaces in the city.

Environmental Activist

"Combine historical climate data, soil maps, and crop yields to analyze the impact of climate change on agriculture"

“Monitor deforestation and forest fires in a particular region”

Search for and combine different GIS data layers to conduct a study on the impact of climate change on agriculture.

Track changes in forest cover using satellite imagery and overlay data layers to identify deforestation hotspots and potential fire risks.

Disaster Management Team

I want to see predictions on fire spread

Provide predictions on fire spread

Real Estate Developer

“Assess the potential impact of a new development project on nearby ecosystems”

Analyze data layers such as land use, topography, and biodiversity to assess the potential impacts of a new development project on the surrounding environment.

Business Analyst

"I want to see further areas with similar socio-economic metrics to identify target markets for a new product launch"

Analyze customer demographics and shopping patterns to identify target markets and create visualizations and maps to communicate insights to stakeholders.

Government Agency

“Develop a risk assessment map for potential natural disasters in a particular region”

Combine data layers on natural hazards, population density, and infrastructure to create a comprehensive risk assessment map for natural disasters.

Educational Institution

“Create interactive learning maps for teaching geography and environmental science”

Utilize GIS data to create engaging and interactive learning maps that illustrate geographical concepts, visualize environmental data, and support STEM education.

Tourists

When to visit X place or where is ideal weather expected at Y date?

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Layers

Layers

Layer

Source API/SDK link

2nd Source API/SDK link

3rd Source API/SDK link

4th Source API/SDK link

Price to get

Use cases by Bard

Project

real estate marketplaces (price)

https://api.developer.attomdata.com/home

https://www.realestateapi.com/

for the US: Zillow

US only Redfin:

https://www.redfin.com/news/data-center/

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socio-economic metrics

American Community Survey (ACS)

WorldPop: https://www.worldpop.org/

OpenStreetMap: https://www.openstreetmap.org/

European Commission Eurostat: https://ec.europa.eu/eurostat

Terrain

Elevation API

Google Earth Engine: https://code.earthengine.google.com/datasets

Landsat 8: https://www.usgs.gov/landsat-missions/landsat-8

Sentinel-2: https://sentinel.esa.int/web/sentinel/missions/sentinel-2

sunny hours

NASA Solar Radiation and Forecast (SOFA):

https://power.larc.nasa.gov/

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https://github.com/OPENDAP/NASA-tutorials

Global Solar Atlas:

https://globalsolaratlas.info/

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Google Earth Engine: https://code.earthengine.google.com/datasets

wind direction and strength

Wind map data from Global Wind Atlas

Global Wind Atlas: https://globalwindatlas.info/

Windyty: https://play.google.com/store/apps/details?id=com.windyty.android&hl=en&gl=US

Windfinder: https://www.windfinder.com/

estimation of species

iNaturalist: https://www.inaturalist.org/

Biodiversity Heritage Library (BHL): https://guides.library.harvard.edu/c.php?g=967370&p=7282814

Ebird: https://ebird.org/home

hi-res satellite (rooftops)

Google Earth Engine

Google Earth Engine: https://code.earthengine.google.com/datasets

DigitalGlobe: https://www.google.com/mymaps/viewer?mid=1dV8e-GtY422z3gr_c-9LnzDvLtY&hl=en_US

Planet: https://www.planet.com/

waters

OpenStreetMap

OpenStreetMap: https://www.openstreetmap.org/

USGS National Hydrography Dataset (NHD): https://www.usgs.gov/national-hydrography/national-hydrography-dataset

European Environment Agency Water: https://assets.publishing.service.gov.uk/media/60fad187d3bf7f044fbb0763/State_of_the_environment_water_resources_report.pdf

Soil quality

Web Soil Survey

NRCS Web Soil Survey: https://www.nrcs.usda.gov/resources/data-and-reports/web-soil-survey

Global Land Cover Facility (GLCF): https://geog.umd.edu/feature/global-land-cover-facility-%28glcf%29

FAO Global Soil Map: https://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/faounesco-soil-map-of-the-world/en/

land category (forest, grassland, building, etc.)

https://documentation.dataspace.copernicus.eu/APIs/On-Demand%20Production%20API.html

Copernicus Land Cover:

https://land.copernicus.eu/

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National Land Cover Database (NLCD): https://www.mrlc.gov/national-land-cover-database-nlcd-2016

FAO Global Land Cover Map: https://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/faounesco-soil-map-of-the-world/en/

precipitation

Global Precipitation Climatology Project (GPCP)

Global Precipitation Climatology Project (GPCP): https://www.nccs.nasa.gov/services/data-collections/atmosphere-based-products/gpcp

Climatic Research Unit (CRU): https://www.cmu.edu/ira/CDS/index.html

WorldClim: https://www.worldclim.org/

yields of what?

https://github.com/satellite-image-deep-learning/techniques?tab=readme-ov-file#11-crop-yield

FAOSTAT: https://www.fao.org/faostat/en/

Food and Agriculture Organization Water: https://assets.publishing.service.gov.uk/media/60fad187d3bf7f044fbb0763/State_of_the_environment_water_resources_report.pdf

Irrigation Management for Sustainable Use of Water Resources: https://www.iwmi.cgiar.org/about/cgiar/

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https://developers.google.com/earth-engine/datasets/catalog⁠

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https://code.earthengine.google.com/register⁠

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https://geo.fas.usda.gov/GADAS/pageDirectories/links/links.html⁠

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Use cases by Bard

Use cases by Bard

Use Cases 2

Description

Layers

Industries

Use Cases

Land Use Planning

Analyzes and manages land use patterns for urban planning, development, and environmental protection.

Government agencies, real estate developers, and environmental organizations.

Identifies areas for development and conservation, analyzes potential impacts of land use changes, and plans for sustainable land use practices.

Environmental Monitoring

Tracks environmental changes, such as pollution levels, deforestation, and natural disasters.

Environmental protection agencies, conservation organizations, and research institutions.

Monitors changes in air and water quality, tracks deforestation and habitat loss, and assesses the impacts of climate change and natural disasters.

Renewable Energy Estimator

Estimate the renewable energy at the given are from wind or solar

energy, government agencies, off-grid planners

Agriculture and Forestry

Maps farmlands, tracks crop yields, and identifies agricultural hazards.

Agriculture, forestry, and agricultural research institutions.

Maps and manages agricultural land and resources, monitors crop health and productivity, and identifies and addresses agricultural pests and diseases.

Foraging

Heatmap the probability of the set species

Campers, foragers, and research institutions.

Education and Learning

Creates interactive learning maps, visualizes geographic data, and supports educational curriculums.

K-12 schools, universities, and educational organizations.

Teaches geography and spatial concepts, engages students with interactive maps and data visualizations, and supports inquiry-based learning and STEM education.

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GIS platforms compared (by Bard)

GIS platforms compared (by Bard)

GIS Data Visualization Platforms

Copy of Interoperable Formats

it provides

Collaboration

Interoperable Formats

Google Earth Engine

Google collaborates with NASA Worldview by providing access to their data through the Earth Engine API and vice versa with NASA Worldview providing access to their data through Google Earth Engine.

GeoTIFF, Mapbox GL JS, 3D Viewer

NASA Worldview

NASA Worldview integrates with ArcGIS Online, QGIS, Mapbox, Carto, and OpenStreetMap by providing access and tools to interact with their data. As a result, NASA Worldview serves as a centralized platform for accessing and visualizing geospatial data retrieved from various sources.

GeoTIFF, Web Map Service (WMS), Web Coverage Service (WCS)

ArcGIS Online

ArcGIS Online integrates with Google Earth Engine by providing a bridge to access and visualize data stored in Google Earth Engine. This integration allows users to easily incorporate Google Earth Engine data into their ArcGIS Online projects and maps.

GeoTIFF, ArcGIS JSON, Feature Service

QGIS

QGIS integrates with NASA Worldview by providing tools to download and visualize data from NASA Worldview. This integration enables users to seamlessly incorporate satellite imagery and other geospatial data from NASA Worldview into their QGIS maps and analyses.

GeoTIFF, Shapefile, OpenStreetMap (OSM)

Mapbox

Mapbox collaborates with OpenStreetMap by providing access to their geospatial data through the Mapbox API. In turn, OpenStreetMap benefits from Mapbox's technology and infrastructure, making their data more accessible and user-friendly.

Mapbox GL JS, Mapbox GL Native

Carto

Carto integrates with OpenStreetMap by providing access to and tools for visualizing data from OpenStreetMap. This integration allows users to easily incorporate OpenStreetMap data into their Carto maps and analyses.

Mapbox GL JS, GeoJSON

OpenStreetMap

OpenStreetMap collaborates with NASA Worldview by providing access to their data through the OSM API. In turn, NASA Worldview benefits from OpenStreetMap's crowdsourced data, which can be used to improve the accuracy and comprehensiveness of their maps.

OSM XML, OSM PBF

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3D Representation of Directed Graph:

The 3D representation of the directed graph would be a globe with each of the GIS data visualization platforms represented as a node. The nodes would be connected by links that represent the data flow between the platforms. The size of the nodes would be proportional to the amount of data that is shared between the platforms. The color of the nodes would represent the type of data that is shared. For example, Google Earth Engine could be represented by a blue node, NASA Worldview could be represented by a green node, ArcGIS Online could be represented by a yellow node, and OpenStreetMap could be represented by a red node.

The links between the nodes would be colored according to the type of data that is being shared. For example, links between Google Earth Engine and NASA Worldview would be purple, links between Google Earth Engine and ArcGIS Online would be orange, links between Google Earth Engine and QGIS would be white, links between Google Earth Engine and Mapbox would be pink, links between Google Earth Engine and Carto would be brown, links between NASA Worldview and ArcGIS Online would be cyan, links between NASA Worldview and QGIS would be light blue, links between NASA Worldview and Mapbox would be dark blue, links between NASA Worldview and Carto would be indigo, links between ArcGIS Online and QGIS would be olive green, links between ArcGIS Online and Mapbox would be maroon, links between ArcGIS Online and Carto would be purple, links between QGIS and Mapbox would be dark gray, and links between QGIS and Carto would be light gray.

This 3D representation would provide a clear and concise way to visualize the relationships between the GIS data visualization platforms. It would also be visually appealing and would make it easy to see which platforms are most connected.