Case Study: Rezatec Amazonas Project

Transcription

1 Case Study: Rezatec Amazonas Project Fraser Harper Product Director, Rezatec Ltd. 20 May 2013

2 Uncertainty - why is it important?...inventories consistent with good practice are those which contain neither over- nor underestimates so far as can be judged, and in which uncertainties are reduced as far as practicable IPCC Good Practice Guidelines for LULUCF, all methodologies must impose confidence deductions when the uncertainty exceeds +/-15 percent of the mean at the 95 percent confidence level or +/-10 percent of the mean at the 90 percent confidence level VCS Standard version 3.1 (Section 4.1) 2

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4 Accuracy and Precision Important concepts in estimating REDD uncertainties Accurate Precise Accurate Precise Accurate Precise 4

5 Cut your coat according to the cloth Two basic inputs for calculating GHG inventories Activities Approaches for estimating change in area of land categories Total area per category Net changes only Total area per category Estimate conversion rates Spatially explicit tracking of conversions over time Emission factors GHG inventory estimates for each land category Tier 1: IPCC default factors Tier 2: Country-specific data for key factors Increasing accuracy and precision Increasing complexity Increasing monitoring costs Tier 3: Modelling, plus repeated measurement of key stocks through time 5

6 Cut your coat according to the cloth Different approaches and tiers can apply at different times Activities Approaches for estimating change in area of land categories Suitable for REDD+ Total area per category Net changes only Total area per category Estimate conversion rates Spatially explicit tracking of conversions over time Emission factors GHG inventory estimates for each land category Tier 1: IPCC default factors Tier 2: Country-specific data for key factors Project Idea Note (PIN) Increasing Project accuracy pre-screening and precision Increasing complexity Increasing monitoring costs Tier 3: Modelling, plus repeated measurement of key stocks through time Project Design Document (PDD) 6

7 Cut your coat according to the cloth Uses for different resolution sensors in REDD monitoring Resolution Cost Use Coarse ( m) Generally free Consistent monitoring of wide areas Large clearings Identify hotspots for further analysis Medium (10-60 m) Free to ~ $0.5/km 2 Primary mapping tools for area change and deforestation mapping Fine (<5m) $2-30 /km 2 Results validation Algorithm training 7

8 Cut your coat according to the cloth Brazilian Legal Amazonia forest monitoring systems PRODES Annual wall-to-wall assessment of the gross deforestation rate Moderate resolution imagery (30 meters) DEGRAD/DETEX Annual wall-to-wall assessment of the forest degradation Moderate resolution imagery (30 meters) DETER Near real time detection of deforestation and forest degradation Coarse resolution imagery (250 meters) 8

9 Uncertainty in biomass distribution Largest source of uncertainty (20% variation to baseline between sources) Dry season Dry season Dry season Jul Jan Jul Jan Jul Jan 9

10 Best practices for reducing uncertainty GOFC-GOLD Sourcebook recommendations For Activity assessment: Use consistent data Same season images Time-phased data using the same sensor Choose data with quality data provided Apply consistent and transparent processes Cartographic and thematic standards Accepted interpretation methods Provide initial data and intermediate data products Document processing steps Apply proper treatment of no data areas For Emission Factors Identify the significant carbon pools ( key categories ) Varies by country/region If significant, use higher tiers If not, Tier 1 may be enough Use conservativeness Consideration during estimation phase helps with cost-effective resource allocation Design and deploy sound statistical sampling methods Local values can vary greatly from country or ecosystem averages Target ground truthing to areas of highest uncertainty 10

11 Rezatec s process Earth Information for business value Platform-as-a-Service (PaaS) Source Data Transform Earth Information Assimilate Collate Model Analyse Disseminate Discover Target Data Extracted Data Analytical Models Regressions Data Products Visualisations Primary Source Data Formatted Data Simulation Models Classifications Data extracts Spatial Analysis Ancillary Data Metadata Temporal (Time) Analysis 11

12 Case Study: Rezatec Amazonas Project Fraser Harper Product Director, Rezatec Ltd. 16 May 2013

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