From Virtual Globes to Open Globes Gilberto Câmara (INPE, Brazil)

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Presentation transcript:

From Virtual Globes to Open Globes Gilberto Câmara (INPE, Brazil)

Open Globe (def) collection of trusted spatial data and services, available operationally and reliably on a open access policy

Virtual Globes Open Globes OpenStreetMap Wikimapia

Virtual Globes Open Globes Data + services (can only be provided reliably by organizations that are trusted) Scientists as policy-makers (peer-reviewed results) Citizens as sensors (perception, individual actions) visibility, communication, acessibility ?

The cat bonfire in the summer solstice Cats thrown into the bonfire in the Place de Greve, Paris, © Bridgeman Art Library

Burning cats is part of the emergence of the modern State State has the monopoly of violence

Sovereignty over a territory: monopoly of the State Cantino´s map (circa 1502)

The Godzilla effect Size matters! trust reliability operationality

source: IGBP How is the Earth’s environment changing, and what are the consequences for human civilization? The fundamental question of our time

Global Change Where are changes taking place? How much change is happening? Who is being impacted by the change?

sources: IPCC and WMO Impacts of global environmental change By 2020 in Africa, agriculture yields could be cut by up to 50%

Terrestrial Airborne Near- Space LEO/MEO Commercial Satellites and Manned Spacecraft Far- Space L1/HEO/GEO TDRSS & Commercial Satellites Deployable Permanent Forecasts & Predictions Aircraft/Balloon Event Tracking and Campaigns User Community Vantage Points Capabilities Global Earth Observation System of Systems

Will the Global Earth Observation System of Systems be based on free and open data policies?

Costs of EO satellites x benefits from EO data ENVISAT sat: US$ 3 billion ENVISAT images: US$ 5 million/year

What did we learn from our fathers? A penny saved is a penny earned

The Anti-Uncle Scrooge Principle A pixel unused is a penny wasted LANDSAT data archive (USGS)

Uncle Scrooge and the Internet Value comes from use!

The Internet has reduced the cost of data distribution to zero!

What is a public good? Non-rival...[goods] which all enjoy in common in the sense that each individual's consumption of such a good leads to no subtractions from any other individual's consumption of that good... (Samuelson) Non-excludable it is impossible to exclude any individuals from consuming the good

Images are public goods Rondonia, Brazil

NASA’s mission formerly began with “To understand and protect our home planet…”. Those words have now been replaced with “Pioneering the future…”. The aim of better exploring the moon and Mars has attractions, but we agree with the sentiment “The planet that has to matter most to us is the one we live on.”

How far are we from the Open Earth? US Earth Observation missions (source: NAS)

Are we doing it right? Budgets of EO satellites

“Scientists have models for estimating the amount of carbon released into the atmosphere when a given plot of land is razed. This information can now be extracted fairly accurately from satellite images. Access to information will be critical. A few satellites can cover the entire globe, but there needs to be a system in place to ensure their images are readily available to everyone who needs them. Brazil has set an important precedent by making its Earth-observation data available, and the rest of the world should follow suit.”

“If Brazil can do it, US can do it too”

Development as Freedom (Amartya Sen) Development can be seen…as a process of expanding the real freedoms that people enjoy. The goal of development is the “promotion and expansion of valuable capabilities.” Capability is the freedom to achieve valuable beings and doings”.

CBERS as a global satellite CBERS ground stations will cover most of the Earth’s land mass between 30 0 N and 30 0 S

29 TERRA (ASTER & MODIS) LANDSAT SPOT ALOS RESOURCESAT IRS CBERS A Potential Land Surface Imaging Constellation SAC-C Source: Daniel Vidal-Madjar (France)

Future of Open Globes 1. Mapping and sensing at large scales will remain under control of sovereign States 2. Open access is the best way to convert from today´s (mostly) closed earth to Open Earth 3. Open access is contagious and largely irreversible 4. Pressure from above (international organizations, global change) and pressure from below (citizens as sensors) will induce change in years 5. Success of Open Earth depends on world development

Virtual Globes Open Globes OpenStreetMap Wikimapia

Virtual Globes Open Globes Data + services (can only be provided reliably by organizations that are trusted) Scientists as policy-makers (peer-reviewed results) Citizens as sensors (perception, individual actions) visibility, communication, acessibility ?

GIScience provides crucial links between nature and society Nature: Physical equations Describe processes Society: Decisions on how to Use Earth´s resources

Slides from LANDSAT Aral Sea Bolivia source: USGS The priority of GIScience research on Open Earth is modeling change

What´s beyond mash-ups? Gapminders?

A sensor (data-centric view) Sensor measurements measure : (S x T) ⟶ V S is the set of location T is the set of times V is the set of values

What is a geo-sensor? measure (s,t) = v s ⋲ S - set of locations in space t ⋲ T - is the set of times. v ⋲ V - set of values Field (static) field : S ⟶ V The function field gives the value of every location of a space

Slides from LANDSAT Aral Sea Bolivia snap (1973) Snapshots snap : T ⟶ Field snap : T ⟶ (S ⟶ V) The function snap produces a field with the state of the space at each time. snap (1987)snap (2000) snap (1975)snap (1992)snap (2000)

Time series (deforestation in Amazonia) series : T ⟶ V The function gives a set of values in time

History Well 30 Well 40 Well 56 Well 57 hist : S ⟶ (T ⟶ V) hist : S ⟶ Series The function hist produces the history of a location in space

Trajectory trajectory : (T ⟶ S) a trajectory is a changing location in time

Moving data mdata : (T ⟶ S) ⟶ V mdata : Trajectory ⟶ V a point moving in space with changing values

Our aim.... state : (S x T) ⟶ V ) We want the state of the world at all locations and all times

In practice {hist 1 (s 1 ),...., hist n (s n )} We have a set of time series for fixed locations 2. {snap 1 (t 1 ),...., snap n (t n )} We have a set of space-based snapshots 3. {mdata 1 (s 1, t 1 ),...., mdata n (t n )} We have a set of moving data

In practice.... {hist 1 (s 1 ),...., hist n (s n )} a set of time series for fixed locations state : (S x T) ⟶ V ) the previous state of the world (or a theory about it) state : (S x T) ⟶ V ) (NEW) a new guess about the state of the world theory_time : (T ⟶ V ) a theory about the time evolution

In practice.... {snap 1 (t 1 ),...., snap n (t n )} a set of space-based snapshots state : (S x T) ⟶ V ) the previous state of the world (or a theory about) state : (S x T) ⟶ V ) (NEW) a new guess about the state of the world theory_space : (S ⟶ V ) a theory about the process that describe space

Models: From Global to Local Athmosphere, ocean, chemistry climate model (resolution 200 x 200 km) Atmosphere only climate model (resolution 50 x 50 km) Regional climate model Resolution e.g 10 x 10 km Hydrology, Vegetation Soil Topography (e.g, 1 x 1 km) Regional land use change Socio-economic changes Adaptative responses (e.g., 10 x 10 m)

Models: From Global to Local snap: T ⟶ (S 1 ⟶ V) {snap 1 (t 1 ),., snap n (t n )} space-based snapshots hist : S 2 ⟶ (T ⟶ V) the history of a location in space

Thank you!