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Earth Observation in Support of the City Biodiversity Index

2016

Today, we are living in an urban world. For the first time in history, there are now more people living in cities than in rural areas. In Europe their share has reached almost three quarters. Urban areas supposedly will absorb almost all the population growth expected over the next decades. This will pose a range of challenges for cities and their surroundings, not only on resource availability and the quality of urban environments, but also on biodiversity in cities. Capturing the status and trends of biodiversity and ecosystem services in urban landscapes represents an important part of understanding whether a metropolitan area is developing along a sustainable trajectory or not. Actions to conserve biodiversity should start with stock-taking and identifying baselines, followed by regular monitoring of conservation initiatives. The City Biodiversity Index (CBI), also known as the Singapore Index on Cities‘ Biodiversity (or Singapore Index) because of Singapore‘s leadership in its ...

EO4CBI: Earth observation in support of the City Biodiversity Index Stefan Kleeschulte space4environment Project context • Urban population: • Today > 50% globally & > 70% in Europe • 2050 projections 66% globally Project context • Urban areas cover only 2-3% of the global surface, but consume about 75% of all resources • Sustainable urban development  Cities need to re-think their approach to management and conservation of biodiversity Project context • Singapore Index on Cities’ Biodiversity • Reply to a lack of indices to measure urban biodiversity • Proposal at CBD COP-9 in Bonn (2008), prepared by Singapore National Parks Board • Endorsed at CBD COP-10 in Nagoya (2010) • Support to Aichi Biodiversity Targets 2011 – 2020 Project context • Link between CBI and Aichi targets • Almost each Aichi target has one or more links to the CBI indicators (see Annex B in CBI User Manual) • Link to the Sustainable Development Goals CBI Framework © Dr. Lena Chan CBI Factsheet - example Application of the index • Self-assessment tool, not for comparisons between cities as context is key to performance • Helps cities to accomplish their biodiversity goals by … • Creating a baseline that supports the identification of policy priorities and can be monitored over time • Serving as public platform (biodiversity awareness raising) • Acting as collaboration portal between different stakeholders Project objectives • Since its establishment, the number of participating cities remained limited  lack of data, personnel and GIS skills • EO4CBI provides support for four of the indicators: User involvement • Institutional international user organisations • ICLEI European Secretariat (Germany) • ICLEI City Biodiversity Center (South Africa) • Singapore National Parks Board • European Environment Agency • Convention on Biological Diversity User involvement • Cities as direct beneficiaries • Phase 1 (prototyping): Barcelona, Tallinn, Edmonton • Phase 2 (roll-out): 6-10 cities across the globe (currently confirmed or discussed are e.g. Addis Ababa, Lisbon, Cape Town, Lilongwe, Suwon, Kaohsiung) General approach & timing • Phase 1 (04/2015 – 03/2016) • Requirements baseline  finalised • Technical specifications in progress • Prototyping of indicators in progress • Test the use of Urban Atlas/other Copernicus data for European cities (Barcelona and Tallinn) • Processing of satellite images, possibly making use of local ancillary data • Quality control/first evaluation • Develop validation plan  not started General approach • Phase 2 (04/2016 – 03/2017) • Roll-out of production  Apply method to other cities • Validation • User utility assessment  evaluation of usability and quality • Roll-out analysis beyond the project Data • SPOT-5 / TAKE 5 • Rapid Eye • Pleiades • … Sentinel-2 Methodology • Indicator 1 (natural areas) • Multi-temporal land cover classification • Integration of OSM street network • Indicator 2 (connectivity) • Based on effective mesh size method by J. Jaeger • Indicator 11 (permeability) • Based on Copernicus HRL imperviousness • Indicator 12 (city trees) • Still on-going methodological research First results Tallinn – Indicator 1 Land cover map First results Tallinn – Indicator 1 Candidate natural areas First results Tallinn – Indicator 11 Not only 0 or 1, but degrees of permeability. Connectivity (Indicator 2) • New method compared to first implementations of CBI • Annex D of CBI User Manual • Based on effective mesh size  probability that 2 points randomly chosen in a landscape are in the same patch or are connected (incl. barriers and intra-patch connectivity) Connectivity (Indicator 2) Challenges • Definition of natural areas varies between cities and is often very much related to land use  difficult to map from satellite images • Balancing between wishes from cities and the general nature of the CBI as an index (indicator) that is based on a standardised method and applicable world-wide • Availability of EO time series to better discriminate vegetation types and phenological development stages  SPOT-5 Take 5 over Tallinn very helpful • Availability of local ancillary data required for the production (e.g. land use related information, barrier data for connectivity) Conclusions / Outlook • Proof of concept in non-European countries • Very high interest from city networks and individual cities • Baseline mapping • Update & monitoring • Sentinel-2 data to overcome 2 important bottlenecks • Free data • Multi-temporal coverage Thank you! http://www.space4environment.com/?id=89