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GEOBENE Benefit Assessment Now, Next and Emerging.

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Presentation on theme: "GEOBENE Benefit Assessment Now, Next and Emerging."— Presentation transcript:

1 GEOBENE Benefit Assessment Now, Next and Emerging

2 2 © GEOBENE 2008 Objective of GEOBENE … to develop methodologies (Ph1) and analytical tools (Ph2) to assess societal benefits of GEO and to perform benefit assessments (Ph3).

3 3 © GEOBENE 2008 COSTSBENEFITS

4 4 © GEOBENE 2008

5 Most operational area: weather

6 2nd most obvious areas: Water & Agriculture: still mostly in planning!!? ( huge benefits …)

7 7 © GEOBENE 2008 CASE I: Value of Land cover uncertainty reduction Biofuels – Food Security – Water - GHG – Ecosystem Trade-off

8 8 © GEOBENE 2008 Integrated Data-Modeling System benefits, costs performance indicators economic surpluses HRU scale DMU scale daily weather records soil profiles topographical data land use and management (crop rotations, fertilization, irrigation, etc.) bio-physical impacts resource endowments economic data (e.g. prices, products, costs) Economic Valuation model comparative static/dynamic bio-physical impact analysis

9 GLC-2000

10 10 © GEOBENE 2008 MODIS 2000

11 11 © GEOBENE 2008 IFPRI – percentage cropland

12 12 © GEOBENE 2008 Ramankutty/Foley – percentage cropland

13 13 © GEOBENE 2008 Scenario to compute value of land availability uncertainty GLOBIOM calculations 2030 estimated food and wood demand + Substitution of up to 10% of transport oil energy consumption according to IPCC/GGI A2r baseline scenario 2030 in each of the 11 regions by ethanol. Variants a) WITH additional land (explicit supply function) b) WITOUT additional land + avoided deforestation

14 14 © GEOBENE 2008 AgLand Use Scenario

15 15 © GEOBENE 2008 Water Use

16 16 © GEOBENE 2008 GHG Balance

17 17 © GEOBENE 2008 Hot Spotting REDD

18 18 © GEOBENE 2008 Expenditures under Information Asymmetry

19 19 © GEOBENE 2008 Accuracy 10,000km ² (est.) Analysis Costs (4.00/km²) MODIS RapidEye Landsat Biomass Estimation based on the integration of different ground truth models Biome Low # SPlots MODIS/Landsat: Low resolution No data availability guaranteed Cloud coverage unknown 80% LiDAR High # SPlots over 1 Million ha (10,000km²) 50% 1,80 Equal analysis costs RapidEye: 5m pixel spacing Data availability guaranteed 4 Million km²/daily Cloud free > 95% Data Costs/km² Ground Truth Costs

20 20 © GEOBENE 2008 Crop Prices

21 21 © GEOBENE 2008 III. Illustrative application

22 22 © GEOBENE 2008 Land availability uncertainty is a USD 350 billion Gas bill Question in the scenario

23 23 © GEOBENE 2008 III. Illustrative application Further applications: Ethanol production x Food security (Obesity)

24 24 © GEOBENE 2008 Undernourished children Source: Keyzer 2006

25 25 © GEOBENE 2008 Human Cost Further applications: Ethanol production x Food security (Obesity)

26 26 © GEOBENE 2008 CASE II: Value of Climate sensitivity uncertainty reduction Energy Investment Problem

27 27 © GEOBENE 2008 Observations Benefits Chain Cloud Observation NASA CloudSat Global Climate Models Long-term Emission Reduction Target Climate Policy CO 2 prices Optimal Technology Choice Investments Profit

28 28 © GEOBENE 2008 Meeting the 2°C objective Source: Mainshausen, Hare 2004

29 29 © GEOBENE 2008 Net present value costs for atmospheric CO 2 stabilization by the year 2100 Green~ BECCS is included Blue~ fossil CCS only Red~ no CCS Trillions of 2000 US$ Source: Azar et al. 2007

30 30 © GEOBENE 2008 Global Energy Portfolio

31 31 © GEOBENE 2008 Real Options Model in the Power Generation Setup add CCS module switch ON CCS module switch OFF CCS module options to add Carbon Capturing and Sequestration module and switch it on/off during the operation

32 32 © GEOBENE 2008 Purpose of the Real Options Approach Maximizing of expected discounted profit facing uncertainty due to incomplete information on future prices and find: 1. Optimal time for investment in CCS module 2. Optimal control of the CCS module

33 33 © GEOBENE 2008 Results from the Real Options Model

34 34 © GEOBENE 2008 PricesProfit distributions … Electricity CO 2 Fuel Real Options Model … Coal Biomass Wind CVaR Portfolio Model Robust Investment Strategy Combined Real Options & Risk Management Framework Robust Investment Strategy describes shares of different technologies in the investors portfolio according to risk aversion preferences

35 35 © GEOBENE 2008 Impact of Uncertainty Reduction on Returns

36 36 © GEOBENE 2008 Impact of Uncertainty Reduction on Returns

37 37 © GEOBENE 2008 Impact of Uncertainty Reduction on Returns

38 38 © GEOBENE 2008 CASE III: Banda Aceh Case Study Determine value of information used by Space Charter Assess value of information in disaster recovery – Banda Aceh case study

39 39 © GEOBENE 2008 Relief Effort According to the RAN Database (Recovery Aceh Nias rand.brr.go.id), as of a total of 490 agencies have commited 3.8 billion USD. Among this vast amount of support are various types of Earth Observation (EO) data (ie. orthophotos, satellite scenes and the creation of a group – SimCenter, to administer this data).

40 40 © GEOBENE 2008 Preliminary Efforts Accomplished initial round of interviews Met with 20 different groups, over 50 people All organizations using to some extent spatial data Identified organizations with specific examples for further analysis

41 41 © GEOBENE 2008 Org. TypeOrganisationContact Nat. GovBRR, PusdatinMr. E. Darajat Nat. GovBRR, BakosurtanalMr. Darmawan UniversityUNSYIAH, GIS & RSMr. M. Affan UniversityUNSYIAH, Vice RectorMr. Dhalan UniversityUNSYIAH, TDMRCMr. Dirhamsyah Local GovBPNMr. G. Suprato Local GovAGDCMr. S. Gan NGOABD - ETESPMr. E. Van Der Zee NGOSea Defence Cons.Mr. J. Kraaij UNUN ORCMr. H. Busa UNUNICEFMr. B. Cahyanto UNUNFAOMr. Sugianto NGOLOGICAMr. D. Hurst NGOGTZ-SLGSRMr. M. Widodo NGOManGEONADMr. T. Rehman NGOLeuser Int. Fnd. (YLI)Ms. D. R. Sari NGOFlora Fauna Int. (FFI)Mr. Syaifuddin NGOSogreahMr. B. Coiron

42 42 © GEOBENE 2008 Preliminary Findings Several main issues repeating (ranked)… Frequency of receiving data low Access to data Need for more/better trained staff Need for higher resolution data in some cases Sharing data - Vendor restrictions Downloading speed A lot of uninformed decisions are made => inefficient allocation of 3.8 Billion $

43 43 © GEOBENE 2008 Conclusions Integrated Long-run benefits can be measured in the trillions - demand pull Is this pull matched by an adequate supply push ?


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