inpe´s contribution to statistics from space: data, applications, and software
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“ Statistics from Space ”, Gates Foundation Seattle, 5-6 November 2008. INPE´s contribution to Statistics from Space: data, applications, and software. Gilberto Câmara Director General National Institute for Space Research (INPE) Brazil. Data: INPE´s vision for the future. - PowerPoint PPT PresentationTRANSCRIPT
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.”