Transcript Free Earth Observation Data on a Global Scale: A View from

Monitoring Deforestation
in Amazonia
Gilberto Câmara, INPE, Brazil
How much land change is happening?
Global Change
Where are land changes taking place?
Who is causing the change?
What are the impacts of public policies?
What will happen in the future?
photo source: Edson Sano (EMBRAPA)
Agricultural Trade in Brazil
photo source: Edson Sano (EMBRAPA)
Cattle in Amazonia and Brazil
Unidade
Amazônia Legal
Brasil
Fonte: PAM - IBGE
1992
29915799
154,229,303
2001
51689061
176,388,726
%
72,78%
14,36%
Cattle in Amazonia and Brazil
1992
Amazonia
Brasil
2007
30 million
75 million
154 million
207 million
Processes of deforestation
Slash and burn
Progressive degradation
Slash and burn
Slash: start of dry season
Burn: end of dry season
Progressive degradation
Barlow and Peters (2008)
Selective logging
Wood extraction and burning
Further burning and pasture
Clear cut
Progressive degradation
T1 – Selective logging
T2 – Loss of smaller trees
T3 – Loss >50% of forest
T4 – Loss >90% of forest
Severely degraded forest
Pasture
Deforestation as an event
Forest
Clear cut
Clear cut – end of deforestation
(objective and definitive)
PRODES: Clear-cut deforestation mapping
~230 scenes
Landsat/year
Yearly detailed estimates of clear-cut areas
Is deforestation an event or a process?
Clear cut
Forest
?
What happens between the pristine forest and the
clear cut?
DETER: Real -time Deforestation Monitoring
15-day alerts of newly deforested large areas
Exploração exploitation
intensiva
Intensive
time
How far is detection time
from real-world time?
Perda
Loss >50%
>50%do dossel
DETER – alert 1
Perda
Loss >90%
>90%do dossel
DETER – alert 2
Corte
Clearraso
cut
Floresta
DETER – final alert
How hard is to use MODIS images to
detect deforestation?
Landsat/TM
Alerta MODIS
DETER nov-2007
August 2007
November 2007
Checking DETER´s data (February 2008)
Clear-cut for pasture
Monthly reports: May 2008
Clear-cut
Intensive impact
Moderate impact
Low impact
Error
TerraAmazon – open source software
for large-scale land change monitoring
116-112
116-113
166-112
Spatial database (PostgreSQL with vectors and images)
2004-2008: 5 million polygons, 500 GB images
Comparison between Segmentation
A comparison of segmentation programs for high resolution remote sensing data, G. Meinel,
M. Neubert, ISPRS Congress, 2004
INPE’s space technology agenda
“Global EO” – Brazil as global player in earth observation
Bilateral agreements
(China, Germany, UK)
Multilateral Agreements
(CEOS, GEO)
CBERS as a global satellite
CBERS ground stations will cover most of the Earth’s land
mass between 300N and 300S
“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.”
INPE´s Remote Sensing Satellites: 2007-2020
CBERS-2B
CBERS-3
Amazônia-1
CBERS-4
CBERS-SAR
Amazônia-2
N.B.: CBERS-2, launched 2003, is still operational
CBERS-5
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
CBERS: China Brazil Earth Resources Satellite
Amazônia-1: 100% Brazilian
CBERS-6
Amazônia-3
Optical Satellites for Tropical Forests
100
Technology 2000
MUX CBERS-3/4
50
Technology 2008
Revisit (days)
Forestry
Mapping
10
CCD CBERS-2/3/4
MUX
CBERS-5/6
Land Use
Description
Technology 2015
LANDSAT
Deforestation
Detection
5
AWFI
CBERS-5/6
AWFI CBERS-3/4
AWFI
Amaz-1/2
WFI CBERS-2
MODIS
1
1
5
10
50
Resolution (metres)
100
500
1000
Sensors for monitoring tropical areas
Amazônia-1 AWFI
40 m ground resolution
5 days global coverage
780 km swath
720 km swath
CBERS-3/4 AWFI
60 m ground resolution
5 days global coverage
120 km
CBERS-3/4 CCD
20 m ground resolution
26 days global coverage
CBERS-3/4 MUX
5 m ground resolution
52 days global coverage
(5 days with mirror)
60 km
CBERS-2B Sensor Configuration
WFI 260 m (890 km)
CCD 20 m (120 km)
PAN 2.5 m (27 km)
0.4
0.5
0.7
0.9
Built by China
1.1
1.5
Built by Brazil
1.7
2.3
2.5
mm
CBERS-2 CCD, Macapá
CBERS-2B CCD-HRC combined image in São
Felix (Pará, Brasil)
Approximate scale 1:10.000
CBERS 3 – 4 Sensors (under construction)
Visible – Near IR
Medium wave IR
Short wave IR
Thermal IR
AWFI 60 m (720 km)
IRMSS 40 m (120 km)
CCD 20 m (120 km)
MUX 5/10 m(120 km)
0.4 0.5
0.7
0.9
1.5
Built by China
1.7
2.1
2.3
3.5
Built by Brazil
3.7
3.9
10
12
µm
Amazônia-1 (under construction)
AWFI
0,45-0,52 B
Spectral Bands(mm)
Spatial resolution(m)
Ground swath(km)
Revisit (days)
0,52-0,59 G
0,63-0,69 R
0,77-0,89 NIR
40
780
5
Global land imaging every 3 days together with CBERS-3
(UK will include a 10-meter camera)
CBERS 5 – 6 Sensors (under discussion)
Visible – Near IR
Medium wave IR
Short wave IR
Thermal IR
IRMSS 20 m (120 km)
AWFI-2 20 m (720 km)
MUX 5/10 m
(120 km)
0.4 0.5
0.7
0.9
1.5
Built by China
1.7
2.1
2.3
3.5
Built by Brazil
3.7
3.9
10
12
µm
INPE´s results have worldwide impact
Society is watching!
International credibility helps…
“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.”
TerraAmazon
...especially when real money is involved!
Until 2015, Norway will give up to US$ 1 billion to reduce
deforestation in the Amazon. Norway’s contribution will
depend on how successful Brazil will be in reducing
deforestation. Brazil has the largest rain forest and one of
the world’s most advanced systems for surveillance of
deforestation.