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Challenges in Providing Environmental & Geospatial Data for modelling processes in the Amazon Region. Biodiversity and Land Use and Land Cover Change for.

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Presentation on theme: "Challenges in Providing Environmental & Geospatial Data for modelling processes in the Amazon Region. Biodiversity and Land Use and Land Cover Change for."— Presentation transcript:

1 Challenges in Providing Environmental & Geospatial Data for modelling processes in the Amazon Region. Biodiversity and Land Use and Land Cover Change for GEOMA Project. Strategies for Open and Permanent Access to Scientific Information in Latin America: Focus on Health and Environmental Information for Sustainable Development Atibaia - SP, Brazil May, 2007 Silvana Amaral Image Processing Division – DPI National Institute for Space Research - INPE

2 2 Context GEOMA: “Rede Cooperativa de Modelagem Ambiental”  Cooperative Network for Environmental Modelling  Established by Ministry of Science and Technology  INPE/OBT, INPE/CPTEC, LNCC, INPA, IMPA, MPEG Long-term objectives  Develop computational­-mathematical models to predict the spatial dynamics of ecological and socio-economic systems at different geographic scales, within the framework of sustainability  Support policy decision making at local, regional and national levels, by providing decision makers with qualified analytical tools.

3 3 Priority Areas for conservation and sustainable use of the Brazilian Biodiversity -ARPA Context Processes are scale dependent  Human Dimension  Biodiversity  LUCC Data needings - Legal Amazonia scale

4 4 Permanent open access to S&T Challenges in Providing Environmental & Geospatial Data: Data Providing  Generation and description  Governamental Initiatives – MMA, SIPAM, INPE, etc. Free access in the internet

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11 11 Permanent open access to S&T Challenges in Providing Environmental & Geospatial Data: Multi-scale Data generation – scales and quality Data Availabity  Space and time scale and series  Data format  Free access / technology

12 12 Different Scales Data for regional modeling

13 13 Networks and connections Regional connectivity  Past and present process of land use occupation  Physical connections of the human settlement and proximity Rio Xingu RioIriri Transamazônica - BR 163 Novo Progresso São Felix do Xingu Apyterewa Kayapó Trincheira Bacajá Araweté/ Ig.Ipiuxuna Koatinemo Kararaô Cachoeira Seca doIriri Arara Menkragnoti Baú Curuá 200 Km 0 Rio Xingu RioIriri Transamazônica - BR 163 Novo Progresso São Felix do Xingu Apyterewa Kayapó Trincheira Bacajá Araweté/ Ig.Ipiuxuna Koatinemo Kararaô Cachoeira Seca doIriri Arara Menkragnoti Baú Curuá 200 Km 0 0 Different Scales

14 14 Networks and connections Field Work Physical network Urban network Different Scales

15 15 Biodiversity - Detailed Data Field Work  BR-319  Madeira - Purus

16 16 Areal Videography from Amazonia GEOMA - May/Jun de 2006 – Intergrated Expedition INPE, INPA, MPEG,WCS – 1, FUNCATE, CPT, FSP http://www.dpi.inpe.br/geoma/videografia/download.php

17 17 ZEE - BRAZIL “ Zoneamento Ecológico Econômico no Brasil” National Program to support territorial planning and Environmental Conservation. Planning, Diagnostic, Prognostic, Implementation Strategy Geographical Data Base (Medeiros & Crepani) INCRA, INPA, CCSIPAM, CODEVASF, Pertobras and others

18 18 ZEE - Scales FocusTerritorialAdministrationScales STRATEGY (Policy) ContinentalFederal 1:10.000.000 1:5.000.000 NacionalFederal 1:2.500.000 1.1000.000 RegionalFederal/Estadual 1:1.000.000 1:250.000 TATIC (Operational) EstadualEstadual/Municipal1:250.000 1:100.000 Municipal 1:100.000 / 1:50.000 LocalDistrital1:25.000 / 1:1.000

19 19 ZEE – Legal Amazon Data gathering Data Selection Import Data Verification Geographical Data Base SPRING Export Internet ZEE Brasil Other sources Dgn / partial Dxf / partial Shapefile Arc Info / E00, UNG Mid / Mif Tiff – Geotiff / Geojpg ASCII – SPRING DBF ASCII tables External Tables TerraLib ASCII Geo Shapefile ASCII – SPRING Geotiff Consulting TerraView Data Selection DATA BASE: ~ 40 Gigabytes 520 layers, 23 tables (+600 atributes)

20 20 Geomorphology Data

21 21 Geomorphology and Landsat Data

22 22 Geomorphology and SRTM Data

23 23 Geographic Data Base and Geographic Information System SGBDMySQL BD SPRING Terralib BD Terralib Web Service TerraPHP Client Spatial Data Terraview SPRING Client Challenge/Commitment: National/ Free Softwares

24 24 ZEE – Legal Amazon Scenario: Systematic and Update Information MMA-SDS Source: MMA/SDS

25 25 ZEE – Project Status Source: MMA/SDS (2006) 1:250.000 products (2006) Legend Working Concluded

26 26 ZEE - Results Products:  Technical Reports  Geographical Data Base  Consulting System Data Dissemination  CDROM (Data Base) – under request  Internet – MacroZEE Consulting and map server (Other scales - forthcoming)

27 27 Permanent open access to S&T Barriers in Providing Environmental & Geospatial Data: TI capacity building and investments – Data Base and internet services  Herbarium of Instituto de Botânica – SP Data policy - institutional and personal  “What would I receive as profit from making my data free?” Differences between Advertising, Consulting (Map Server) & Free data access

28 28 A “Model” for providing access Earth observation data for everyone: the CBERS experience (Camara, 2007)  The world is changing rapidly Climate Change is here to stay  Global land observation is a crucial need for the world, but its future is uncertain MODIS is very useful,but has no future What will happen to LANDSAT? public good  Global land observation systems are a public good  PRODES, DETER, DETEX – environmental monitoring systems (INPE´s strategy and data policy)

29 29 Altamira (Pará) – LANDSAT Image – 22 August 2003

30 30 Altamira (Pará) – MODIS Image – 07 May 2004

31 31 Imagem Modis de 2004-05-21, com excesso de nuvens Altamira (Pará) – MODIS Image – 21 May 2004

32 32 Altamira (Pará) – MODIS Image – 07 June 2004

33 33 6.000 hectares deforested in one month! Altamira (Pará) – MODIS Image – 22 June 2004

34 34 Altamira (Pará) – LANDSAT Image – 07 July 2004

35 35 Go to the field....

36 36...and get the bad guys!

37 37 20032004200520062007200820092010 LANDSAT-51984 LANDSAT-82010? SPOT41998 SPOT52002 CBERS-22003 CBERS-2B2007 CBERS-32009 IRS-P62003 Land Remote Sensing: 20 to 50 meter resolution

38 38 Land Remote Sensing: 50 – 300m resolution Resolution 2004200520062007200820092010 MODIS Terra Aqua 2001250 m 1 dia MERIS2002300 m 2 dias WFI Cbers-2 Cbers-2B 2003250 m 4 dias AWFIS Irs-P6 200270 m 4 dias AWFI Cbers-3 200970 m 4 dias AWFI SSR-1 2009 ? 70 m 4 dias

39 39 Strategy for CBERS How do we obtain support for funding Earth Observation Missions (300+ million dollar question)?  Our answer: Make all sectors of society use publically funded EO data... ...by providing EO data for free! CBERS images received in Brazil are freely available on the Internet for Brazilian and Latin American users CBERS images received in China are freely available on the Internet for Chinese users A high-quality image processing software (SPRING) is also available free on the Internet in Brazil

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42 42 FTP area for User

43 43 CBERS-2 CCD, Minas Gerais, Brazil Government Institutions23% Educational Sector26% Private Companies51%

44 44 Free CBERS data Enables new business and technology development Facilitates trial uses for new clients and students Planning new applications and scientific projects becomes easier Satellite imagery became a popular and affordable environmental data for business, education and scientific research.

45 45 Free CBERS data The CBERS data policy has been extremely well-received by government and society in Brazil There is an enormous demand for remote sensing and environmental data in developing countries Free on-line data access can significantly increase the number of users of earth observation data

46 46 Final Comments There are Environmental and Geospatial data available  BUT … data quality, metadata, scale has to be considered GEOMA demands data of high quality and several scales  AND is providing some basic data  AND is working on publishing and data availability (internet and Newsletters) Environmental and Geospatial data as public good can create demands for services and research, what promote a positive feed-back for free data access.

47 47 Thank you! Slides and photos also provided by: Ana Paula Aguiar Gilberto Camara José S. de Medeiros Mario Cohn-Half INPE´s team silvana@dpi.inpe.br


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