INPE´s contribution to Statistics from Space: data, applications, and software

Gilberto CâmaraDirector General National Institute for Space Research (INPE)Brazil

“Statistics from Space”, Gates FoundationSeattle, 5-6 November 2008

Data: INPE´s vision for the future

A constellation of satellites and sensors will provide free earth observation data for all countries on Earth

“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”

CBERS as a global satellite

CBERS ground stations will cover most of the Earth’s land mass between 300N and 300S

INPE’s space technology agenda

“Global EO” – Brazil as global player in earth observation

Multilateral Agreements (CEOS, GEO)

Bilateral agreements(China, Germany, UK)

INPE´s Remote Sensing Satellites: 2007-2020

2016

2014

CBERS-5CBERS-4

Amazônia-1

CBERS-3

2015

Amazônia-2

CBERS-6

2017

2019

CBERS-SAR

Amazônia-3

2013

2012

2011

2010

2009

2008

2007

2018

CBERS-2B

N.B.: CBERS-2, launched 2003, is still operational

CBERS: China Brazil Earth Resources Satellite Amazônia-1: 100% Brazilian

Optical Satellites: Forestry and Agriculture

1

10

100

1 10 100 1000

Resolution (metres)

Revi

sit (

days

)

WFI CBERS-2

CCD CBERS-2/3/4

AWFI CBERS-3/4

MUX CBERS-3/4

Technology 2008

Technology 2015

Technology 2000

50

50

5AWFI

CBERS-5/6

MUXCBERS-5/6

Mapping Agriculture

Mapping Forestry

Deforestation Detection

Description Land Use

5

AWFI Amaz-1/2

LANDSAT

DMC-2

500

MODIS

Amazônia-1 AWFI780 km swath

120 km

40 m ground resolution 5 days global coverage

CBERS-3/4 MUX

CBERS-3/4 CCD

60 km

CBERS-3/4 AWFI

720 km swath

Sensors for monitoring tropical areas

60 m ground resolution 5 days global coverage

20 m ground resolution26 days global coverage

5 m ground resolution52 days global coverage(5 days with mirror)

CBERS-2B Sensor Configuration

m0.4 2.50.

71.10.

90.5 1.5 1.7 2.3

WFI 260 m (890 km)

CCD 20 m (120 km)

Built by China Built by Brazil

PAN 2.5 m (27 km)

CBERS-2 CCD, Minas Gerais, Brazil

CBERS-2B CCD-HRC combined image in São Felix (Pará, Brasil)

Approximate scale 1:10.000

CBERS 3 – 4 Sensor Configuration

µm0.4 2.30.7 1.10.90.5 1.5 1.7 2.1

WFI 73 m (860 km)

MSS 40 m (120 km)

CCD 20 m (120 km)

MUX 10 m (60 km)

PAN 5 m (60 km)

Built by China Built by Brazil

Amazônia-1 (cooperation with UK)

Global land imaging every 3 days together with CBERS-3 (RAL-UK will alsoinclude a 10-meter camera)

AWFI

Spectral Bands(m)

0,45-0,52 B

0,52-0,59 G0,63-0,69 R

0,77-0,89 NIR

Spatial resolution(m) 40Ground swath(km) 780Revisit (days) 5

SRTM DEM Coverage 90x90m Digital Elevation Model

(30x30m withheld by US govnt)

Data: SRTM for Africa

INPE will produce and distribute an STRM-based elevation data in 30 x 30 m for Africa

Interpolation of SRTM data

Original 90x90 m SRTM (9x zoom)

Interpolated 30x30 m Kriged SRTM

Shaded relief from SRTM

~230 scenes Landsat/year

Taxa anual de desmatamento

PRODES: Yearly detailed estimates of clear-cut areas

Applications: Deforestation monitoring

DETER: 15-day alerts of new large deforested areas

Applications: Deforestation monitoring

StateÁrea (ha) for 2007-2008

Crop Reform Total

Goiás 308.840 19.451 328.291

Minas Gerais 463.007 20.159 483.166

Mato Grosso 217.762 19.913 237.675

Mato Grosso do Sul

212.551 14.406 226.957

Paraná 514.678 26.525 541.203

São Paulo 3.946.37

0278.201

4.224.571

Total5.663.2

08378.655

6.041.863

Applications: Sugarcane area mapping

Software: Open source GIS

Visualization (TerraView)

Spatio-temporalDatabase (TerraLib)

Modelling (TerraME)

Data Mining(GeoDMA)Statistics (R interface)

166-112

116-113

116-112

TerraAmazon – open source software for large-scale land change monitoring

Spatial database (PostgreSQL with vectors and images)2004-2008 data: 5 million polygons, 500 GB images

RR data from geoRgeoR package.

Loaded into a TerraLibTerraLib database, and visualized with TerraViewTerraView.

Software: R-Terralib interface

Spatial statistics functions in R can access TerraLib database

Software: Land modelling with cellular automata

Cell Spaces

Generalized Proximity Matrix – GPM

Hybrid Automata model

Nested scales

TerraME: Develop dynamical models in cell spaces

Land Change in Amazonia (Scenario for 2015)

0.0 – 0.10.1 – 0.20.2 – 0.30.3 – 0.40.4 – 0.50.5 – 0.60.6 – 0.70.7 – 0.80.8 – 0.90.9 – 1.0

% deforested

Cell space model developed using TerraME

INPE´s results have worldwide impact...

…and scientific credibility

TerraAmazon

“Today, Brazil’s monitoring system is the envy of the world. INPE has its own remote sensing satellite, a joint effort with China, that allows it to publish yearly totals of deforested land that scientists regard as reliable.”