INPE s Brazilian Amazon Deforestation and Forest Degradation Program. Dalton M. Valeriano Program Manager

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1 INPE s Brazilian Amazon Deforestation and Forest Degradation Program Dalton M. Valeriano Program Manager

2 Summary PRODES Yearly deforestation inventory DETER - Daily detection of deforestation and forest degradation DEGRAD Yearly Inventory of forest degradation (International capacity building program)

3 INPE s Amazon Deforestation Monitoring Project - PRODES

4 PRODES: INPE s Amazon Monitoring Program Fact Sheet Coverage: Wall-to wall Frequency: Yearly Integration period: Aug-Jul Brazilian Legal Amazon Region: 5 million km 2 Original forest cover: 4 million km 2 Present gross deforested area: ~ km 2 Proportion of secondary forest: ~20% (TerraClass) Resolution Landsat-class (Landsat, CBERS, DMC, SPOT) Method: Visual interpretation Minimum mapping area: 6.25 ha Delivery Schedule: 1 st estimate -90% of previous year, ~100 Scenes : November Complete map: April, next year

5 233 Landsat Images

6 PRODES: INPE s Amazon Monitoring Program A brief history st Brazilian Amazon deforestation inventory 1: Landsat B&W Hardcopies Visual interpretation Digital area calculation

7 PRODES: INPE s Amazon Monitoring Program A brief history Yearly Inventory 1: Landsat Color composites Visual interpretation Digital area calculation

8 PRODES: INPE s Amazon Monitoring Program A brief history INPE s new development in the 90 s Three bands color composite SPRING Geographic Information Processing System Features applied to PRODES: SOIL Linear Mixing Model Image Segmentation Object Oriented Classification SHADOW Raster and Vector Edition GREEN VEGETATION

9 OF (RGB) TM IMAGE PRODES: INPE s Amazon Monitoring Program A brief history SPRING based digital Landsat image analysis Linear Mixing Algorithm Image Segmentation Object oriented classification + editing Typical deforestation

10 PRODES: INPE s Amazon Monitoring Program A brief history 2005-Present: Visual intepretation in TerraAmazon GDBM Platform TerraAmazon overview: Alllows multisource and multitemporal data Allows multiple interpreters Real-time GDB update Lock-in lock-out control TerraLib open code Interpretation time: (SPRING) DIP+Edition: hs (TerraAmazon) VI: 5-10 hs

11 Multidata approach CCD/CBERS DMC LANDSAT LANDSAT CBERS SISPRODES State boundaries

12 PRODES schedule: 1st Semester: April :Complement of 2011 inventory 2nd Semester First deforestation estimate Data Acquisition: Jun-Aug Product delivery: November (in time for UNFCCC COP)

13 Alternative to lack of Landsat DMC coverage National scale at INPE s Data Archival and Distribution Center Free access - US$ 3 Mi

14 o s Peixoto de Azevedo/MT - Landsat 225/67 Set/2010 Jul/2011

15 o s Porto dos Gaúchos/MT Landsat 227/68 Jun/2010 Ago/2011

16 PRODES: INPE s Amazon Monitoring Program Internet Access Full access to source images,maps and statistics

17 PRODES: INPE s Amazon Monitoring Program Transparency paradigm (since 2003): Public awareness Basis for spatial/temporal analysis Basis for carbon emission report Government decision making

18 Km2/year Benchmarks of PRODES products and engagement in national deforestation control program: Release of PRODES products in the internet 2003 PPCDAm conceiving and implementation - Proposal of DETER 2004 PPCDAm formalized DETER implemented 2005 on Reduced deforestation - Agreement with Norway Government AMAZON FUND (a) Yearly Deforestation in Brazilian Amazon (b) (b) (d) Year

19 Média = km

20 PRODES in PPCDAm Global and regional indicator of policy efficiency Criterion for list of critical municipalities

21 Main consequences of PRODES Evaluation of efectivity of deforestation control policies Public awareness of the deforestation in the amazon (www.obt.inpe.br/prodes) Means for the concerned society to demand governmental action on the issue Support for policy making at regional and local scales

22 But PRODES is not enough... Results are obtained and published after the damage is done Difficulty of the government to punish ilegal deforestation after it is installed Demands for faster information production

23 DETER Near Real Time Deforestation Detection with MODIS

24 EXTENSÃO TOTAL_AGOSTO 2003 SOBRE IMAGEM MODIS (22abr-07maio 2004)

25 CLASSIFICAÇÃO DA IMAGEM MODIS (mosaico 22 abril a 07 maio de 2004) EXTENSÃO TOTAL_AGOSTO MUDANÇA ATÉ 07 MAIO + IMAGEM

26 NOVA EXTENSÃO TOTAL ATÉ 07 DE MAIO DE 2004 SOBRE IMAGEM MODIS (22abr-07maio)

27 EXTENSÃO TOTAL ATÉ 07 DE MAIO DE 2004 SOBRE IMAGEM DE 21 MAIO

28 CLASSIFICAÇÃO DA IMAGEM MODIS DIÁRIA DE 21 DE MAIO DE 2004

29

30

31 Report by automatic of New deforestation detected in Conservation Unities and municipalities

32 Impact of DETER Information for strategic decisions by deforestation control agencies - Federal, State and Municipal levels Better efficiency in law enforcement Immediate public awareness by monthly information dissemination (www.obt.inpe.br/deter)

33 DETER New Paradigm MODIS 25 ha minimum mapping unity is today very limiting Need to move to better sensors Options ResourceSat/AWiFS DMC Future: CBERS3/AWFI (60m, 5 days) Amazonia-1 (40m, 5 days)

34 DETER-based Policies for Deforestation Control: Law Enforcement

35 Deforestation hotspots DETER 2011/INPE

36

37

38

39 Monitoring the State of the Forest: DEGRAD e DETEX

40

41

42

43

44

45 Corte seletivo Resultados Finais: 85 cenas UF 2007(KM2) 2008(KM2) Acre Amazonas Amapá Maranhão Mato Grosso Pará Rondônia Roraima Tocantins TOTAL

46 Corte seletivo Resultados Finais 2007 e 2008 Degradação em 2007 convertida a corte raso em 2008: UF Acre Amazonas Amapá Maranhão Mato Grosso Pará Rondônia Roraima Tocantins KM TOTAL

47

48 Thank you

49 INPE s Capacity Building Program in Remote Sensing Based Tropical Forest Monitoring Claudio Aparecido de Almeida Head, INPE - Regional Center for Amazonia )

50 Amazon Regional Center, Belem

51 Mission: INPE - Amazon Regional Center To assimilate and operate INPE s Amazon Monitoring Program To become an international reference in capacity building for satellite based tropical forest monitoring

52 INPE Amazônia Equipe Staff INPE Hired Scholarship Trainee Total

53 INPE Amazonia Staff/ Function 2011

54 Course Program (2 weeks) 1. Experience acquired with Amazon Program: PRODES, DETER, DEGRAD, TERRACLASS 2. Data base management 3. Terra family software 4. Cartography 5. Geographic data processing 6. TerraAmazon System Database administrator Digital image processing, edition, data analysis

55 INPE s open source image processing and geographic information analysis and management: TerraLib based Terra* family: SPRING

56 Participant profiles 1 - Database Administrator IT background Experience in data base management Government employee 2 - Remote Sensing Background in any Environmental Science Basic knowledge in remotes sensing Government employee

57 Current cooperation and training programs: FAO - 2 years,; 6 courses/year ; target : 200 students (Tropical countries) JICA-ABC 3 years, 3 course/year; IBAMA staff and Amazonian Countries 108 students already ACTO 2 years, 2 courses/year; ACTO countries; target 35 students and continued help-desk

58 JICA 2010 Bolivia, Colombia, Ecuador, Guatemala, Peru

59 JICA 2011 Angola, Mozambique, Paraguai

60 JICA 2011 Malasia, Thailand, Indonesia, Philippines, Cambodja e Vietnam

61 FAO Mexico, Ecuador, Guiana, FAO Headquarter

62 OTCA-2011 Bolivia, Ecuador, Colombia, Venezuela, Peru

63 FAO Inge Jonckheere (FAO) Claudio Almeida (INPE) Democratic Republic of Congo, Papua-New Guinea, Vietnam

64 Forests are not just Carbon! Biodiversity Environmental services People

65 Thank you again

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