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Money for Nature: Earth Observation for Natural Capital Accounting
This document discusses using earth observation data and machine learning to compile natural capital accounts according to the UN SEEA framework. It provides an overview of ecosystem accounting and applications, including examples from the Netherlands of accounts for carbon sequestration, water infiltration, and crop production. The document also demonstrates how remote sensing can be used to map land cover changes, detect fires, monitor flooding, and track rice growth for agricultural accounts. It concludes that while technology is advancing rapidly, scaling applications and connecting various data sources requires further testing and development.
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Money for Nature: Earth Observation for Natural Capital Accounting
- 1. Money for Nature:Earth Observation for Natural Capital Accounting @ SarVision Solutions for natural resources management @ SarVision – Solutions for natural resources management
- 2. A Sunday Brunch-Crunchconversation • Introduction of SarVision • The SEEA Ecosystem accounting approach • Application of SEEA EEA: the Netherlands • Using machine learning for compiling accounts • Using remote sensing for compiling accounts and monitoring the environment • Conclusions and future prospects • Am I missing something? How will we talk about nature tomorrow, and what will be the entry cost of that debate, and what adjectives will be used
- 3. The SEEA Framework:integrating environmental and economic information • SEEA = System of Environmental Economic Accounts • Connected to the System of National Accounts: economic statistics • Part of the statistical system, guidelines developed by the world’s statistical agencies (UNSC), UN, IMF, World Bank, OECD, European Commission. • Two complementary approaches: the SEEA Central Framework and the SEEA Ecosystem Accounts
- 4. SEEA - EcosystemAccounting • A systematic framework to measure the contributions of ecosystems to economic activity; • Aligned with the National Accounts; • In natural capital accounting, ecosystems are assets that provide ecosystem services to people. Assets can be measured using both physical and monetary units. In the international System of Environmental-Economic Accounting, ecosystem assets are generally valued on the basis of the net present value of the expected flow of ecosystem services. It includes physical and monetary information; • DEM-digital elevation model, soils, hydrology, land cover, vegetation type, crop production, NPP-net primary productivity, ecosystem use, values of services and assets, ecosystem users • Information in the form of maps and accounting tables
- 5. Applications of EcosystemAccounting approach, from micro to macro! • Monitoring changes in natural capital over time • Identifying areas, ecosystem types or ecosystem services under threat • Understanding the dependence of economic actors and activities on ecosystems • Understanding the contribution of ecosystems to the economy and the economic implications of ecosystem change • As a ready-to-use database for scenario analysis, designing policies, analysing policy effects, etc.
- 6. Structured information Ecosystem accountingmaps & tables Accounts Data, monitoring systems Indicators Accounting tables Maps
- 7. Countries testing orapplying SEEA ecosystem accounting • Canada: MEGS project • Australia: Land accounts, pilot ecosystem accounts for Great Barrier Reef • UK: national analysis of the value of natural capital and of the value generated by specific ecosystems (national parks, coast, farmland) • Netherlands: Full ecosystem account being developed • Peru: CI Project in San Martin region • Philippines (WB support): pilot account for two sites • South Africa: pilot focusing on natural ecosystems and rivers • Mexico • Japan: 3-year project to test the SEEA EEA approach • European Union • Colombia, Costa Rica, Rwanda, Indonesia, World Bank WAVES program (Wealth Accounting and the Valuation of Ecosystem Services partnership) • Norway (Greater Oslo area) • New countries: New Zealand, Brazil, China, India.
- 8. The Netherlands account Source:CBS the Netherlands and Wageningen University
- 9. Dutch Condition account:15 key indicators Source: CBS the Netherlands and Wageningen University
- 10. Ecosystem services in NLSEEA account Provisioning services • Crop production • Fodder production • Timber production • Other biomass • Water supply Regulating services • Carbon sequestration • Erosion control • Air filtration • Water infiltration • Pollination • Pest control Cultural services • Nature recreation (hiking) • Nature tourism Multiple datasets and models per service Source: CBS the Netherlands and Wageningen University
- 11. High resolution allows zoomingin locally Example: water infiltration Source: CBS the Netherlands and Wageningen University
- 12. The carbon account •Stocks, emissions and sequestration of CO2 Source: CBS the Netherlands and Wageningen University
- 13. From accounts topolicy support • CO2 emission peat ~4% of national emissions • Depend upon drainage • Different management leads to major emission reductions • The carbon account is supporting policy actions Source: CBS the Netherlands and Wageningen University
- 14. Using remote sensingto compile accounts • Ecosystem extent / land use • Conversion of forest in plantations • Smallholders versus plantations • Condition • Fire • Water/flooding • Carbon • Stocks and flows • Supply and use account • Rice production
- 15. Land cover (ha) Production (ton) Forest175,000Timber 1,575,000 Carbon sequestration 1,050,000 Plantation 25,000Oilpalm fruit 500,000 Annual crops 85,000Paddy rice 1,020,000 Urban 25,000- Total 310,000 Land cover (ha) Production (ton) Forest 165,000Timber 1,485,000 Carbon sequestration 990,000 Plantation 35,000Oilpalm fruit 700,000 Annual crops 85,000Paddy rice 1,020,000 Urban 25,000- Total 310,000 Land cover (ha) Production (ton) Forest 150,000Timber 1,350,000 Carbon sequestration 900,000 Plantation 50,000Oilpalm fruit 1,000,000 Annual crops 85,000Paddy rice 1,020,000 Urban 25,000- Total 310,000 Land cover (ha) Production (ton) Forest 140,000Timber 1,260,000 Carbon sequestration 840,000 Plantation 60,000Oilpalm fruit 1,200,000 Annual crops 85,000Paddy rice 1,020,000 Urban 25,000- Total 310,000 Land cover (ha) Production (ton) Forest 125,000Timber 1,125,000 Carbon sequestration 750,000 Plantation 75,000Oilpalm fruit 1,500,000 Annual crops 85,000Paddy rice 1,020,000 Urban 25,000- Total 310,000 Land cover (ha) Production (ton) Forest 115,000Timber 1,035,000 Carbon sequestration 690,000 Plantation 85,000Oilpalm fruit 1,700,000 Annual crops 85,000Paddy rice 1,020,000 Urban 25,000- Total 310,000 Land cover (ha) Production (ton) Forest 109,000Timber 981,000 Carbon sequestration 654,000 Plantation 91,000Oilpalm fruit 1,820,000 Annual crops 85,000Paddy rice 1,020,000 Urban 25,000- Total 310,000 Compiling extent accounts with satellite data Case study showing expansion of oil palm plantations in Johor, Malaysia 2016-2018 Detail of map Plantation Forest
- 16. Condition account: Firedamage detection July – Nov 2015 Mapping burned areas, 12 days interval 16 FIRE HOTSPOTS Mapping burned areas (fire scars), 12 day interval
- 17. Water monitoring We monitorsurface water to support: Wetlands monitoring Hydrological modelling Assessment of flooding risk and damage on crops and plantations Monitoring, reporting and verification of GHG emissions Day and night and weather-independent observations : service continuity even in cloudy conditions Monitoring service also available under the vegetation canopy (radar capacity to penetrate vegetation) Flood map @ SarVision – Solutions for natural resources management 17 Sentinel-1 image, 21/04/2017
- 18. Condition account: Monitoringand recording flooding Flood monitoring – Haor region, Bangladesh Sentinel-1 images 02/2017 – 05/2017
- 19. Overlay with existingmap of canals Peatland We assess the hydrology and flooding regime of peat. We monitor drainage canals (opening, closing) and fires. We support: Public entities in charge of peat land sustainable management and restoration. Agro-businesses in the management of assets in peat land. Day and night and weather- independent observations : service continuity even in cloudy, hazy and smoky conditions Monitoring service also available on peat forest (radar capacity to penetrate vegetation) @ SarVision – Solutions for natural resources management 19 Drainage canals patterns detected by Sentinel-1 image New canals detection
- 20. Biomass time series overthe years 2000-2012 Small section of the East Kalimantan map (50 km wide). Carbon account: Mapping carbon stocks and flows (above ground vegetation) New, EU space agency project also emissions from peat drainage included
- 21. Agriculture Rice growth stagemonitoring, Mekong Delta, Vietnam @ SarVision – Solutions for natural resources management 21
- 22. Agriculture Sentinel-1 images, July2017 – December 2017 Area of Bogra, Bangladesh Rice growth stage maps, July 2017 – December 2017 Area of Bogra, Bangladesh @ SarVision – Solutions for natural resources management 22
- 23. Agriculture Multi-data online platformfor crop damages assessment Support to national rice crop insurance program in Indonesia @ SarVision – Solutions for natural resources management 23
- 24. Conclusions • Technology forusing machine learning, earth observation and open data for informing natural resource management and compiling accounts is developing VERY rapidly; • High resolution, high accuracy and weekly/monthly updates present unprecedented policy use options for monitoring and planning resource use; • Methods have been developed! But scaling up and further testing is required; • Opportunities challenges when connecting to more data sources & users are infinite: land registry, civil administration, healthcare institutions, school system, chambers of commerce, credit bureaux, telephone network, fiscal authority, civil society org-s, agricultural/forestry/aquaculture/paludiculture scientists, transport companies, food manufacturers, retailers/supermarkets etc.; • BUT the rigour of accountants remains the basis of the verifiable, trustworthy, transparent connection between knowing the landscape and effectively being able to protect its value.
- 25. Thank you @ SarVision @SarVision – Solutions for natural resources management 25
Editor's Notes
- #2 Good morning. First I’d like to thank the organisers of the Global Landscapes Forum, especially the Government of Germany, CIFOR and Wageningen University & Research. What the organisers say is true, they really stimulate a mood that stimulates enthusiastic, engaged conversation. And indeed, if we really want to achieve the goals of the UN-SDG and the UNFCCC Paris Agreement, we better do everything in a transparent, scientific manner so that all stakeholders, especially all citizens, can see reality changing due to our actions. And if and how citizens will change their conversation with governments and experts when they know what reality & what policy costs what. Professors of the world’s No. 1 ranked Agricultural University, Wageningen, founded and manage SarVision, a private company. It uniquely combines Earth Observation technologies with Environmental Economic Accounting. After a study in Law in the Netherlands and a post-grad in European Law and International Trade at the College of Europe in Bruges, I started work in the Legal Services Division of Agriculture in the European Commission. In the EU I learnt a lot about land reform, farming and how fanatically national governments protect their farmers and avoid criticising them, and how the farm & forestry lobby became Europe’s strongest. I also learnt that I was not public service material. Since 1994 I worked in Africa and Asia, living in several places from the year 2000, mainly in central banks and finance ministries, supporting the integration of rural areas, farmers and “marginalised people” in good quality financial services from providers who want to and can be held accountable. On Sundays I would regularly watch BBC’s Dateline – I would be happy if I could create that atmosphere with you, for a Brunch-Crunch conversation, after a first introduction.
- #3 While I lived in Africa & Asia, from 2000 to last year, I often watched BBC – Dateline on Sunday morning. What I would like to do is prepare us for such a conversation on how satellite Earth Observation and Environmental Economic Accounting form the basis for Efficient Spatial Planning & Sustainable (social, environmental and economic) land management
- #4 The SNA (system of National Accounts) is a United Nations framework that is used by all countries in the world to produce economic statistics including GDP. The SEEA is part of the SNA
- #5 The SEEA Ecosystem accounting approach is about analysing and recording (changes in) ecosystems and human use and economic benefits from ecosystems.
- #9 The extent account shows the type pof ecosystems in a country adn the area that they cover
- #10 The condition account uses a set of indicator o express the health or state of the ecosystem
- #12 Water infiltration is relevant when it is about understanding risks of high rainfall events, if water cannot enter the soil you will have flooding which may damage houses or crops.
- #13 The maps show sequestration of carbon (C) in vegetation (forests are in blue since they capture the most), and the emissions from the peatlands of the Netherland. Peatlands emit CO2 when they are drained, as is the case with most peat areas of the NLs.
- #16 Note that this demonstration links deforestation patterns to an account: with every time step the accounting table is adjusted. IT shows how palm oil increases and forest cover decreases. Time steps are 12 days, and the system is fully automated.
- #17 This video shows the development of forest fires during the period July – Nov 2015 in Jambi, Sumatra. Colored areas (from yellow to red) show areas impacted by fires during the period July-November 2015, during the last severe El Nino event. Each color corresponds to a different month. In the top right window, burnt areas detected with our algorithm are overlayed with fire hotspots detected by MODIS. There is a high agreement between both data sources.
- #18 On the right a Sentinel-1 image (blue areas = flooded areas) and a flood map (blue areas = flooded areas) over the Haor region in Bangladesh in April 2017. Massive flooding flooded 30% of the region and destroyed thousands of hectares of rice crops.
- #19 Flooding is also a condition indicator, and flood models can be linked to the SEEA condition account. Flooding of course directly affects production, in this case of rice.
- #21 The demonstration shows observed above ground biomass in forests and plantations. The red areas represent forest that is cleared for plantation development. These areas grow back gradually up to 80 to 90 ton Carbon/ha, which is the biomass content of a mature oil palm plantation. By analysing stocks on an annual basis also the flows (i.e. changes between years) can be modelled.
- #22 This video shows our online rice monitoring platform. New maps are updated every 6 days : Rice crop extent and growth stage of the rice (seedling, tillering, booting, flowering, milking, ripening, harvesting, fallow) Flooding extent Crop height Statistics on rice area, distribute per growth stage, and crop height are extracted on the fly for every date (right window). Day & night, weather-independent observations (radar sensors) enables continuous monitoring; High resolution (15 m.) enables small fields (0.5 ha) monitoring. Example from Sat4Rice project: Sat4Rice (Satellite data for rice farmers) aims to improve the effectiveness of existing extension services and output of (smallholder) rice farmers in the Mekong Delta. This is done by enriching the existing basic agricultural information with advanced geodata. Crop growth stage maps and floods maps are combined with in-situ data in a mobile application used by fields officers to provide more effective advice to smallholder rice farmers. https://sat4rice.wordpress.com/ https://youtu.be/nppH86fNNw8
- #23 On the left: rice growth stage maps over the District of Bogra in Bangladesh, for the Aman rice season of 2017 On the right: Sentinel-1 satellite images from which the maps are generated Example from IDSS project: IDSS aims at providing relevant information to farmers in Bangladesh in a convenient, relevant, timely and effective way using technology that would enable farmers to produce better crops, optimally and increase their incomes. The project is leveraging geo-data to gather, target and disseminate relevant information to farmers when they need it, in a sustainable way. Services offered through IDSS apps include Crop suitability, Crop growth monitoring, Pest and Diseases alert, and Weather alerts. http://idss.com.bd/ https://youtu.be/sK4RV4X5L_4
- #24 Online platform developed by SarVision to support the national rice crop insurance in Indonesia. Users can click on any location in Java and generate a crop biomass growth temporal profile (see right graph window) from both radar (green curve) and optical (purple curve) satellite data. A blue curve also shows flooding. Users can also browe through maps and visually check crop damages. A polygon drawing tool allows to estimate the area of crop damage. The data is high resolution (10 to 15 m), allowing the assessment of small size fields (less than 1 hectare). Example from G4Indo project: The G4INDO project assists the Government of Indonesia in providing insurance to rice smallholder farmers. State of the art remote sensing technology (radar and optical images) is combined with hydrological data of concrete river basins, and with crop growth models in a digital platform that will allow the insurer to monitor crop growth and assess abnormalities. http://www.g4indo.org/about