Assessing the role of EO in biodiversity monitoring: options for integrating in-situ observations with EO within the context of the EBONE concept

摘要: The European Biodiversity Observation Network (EBONE) is a contribution on terrestrial monitoring to GEO BON, the Group Earth Observations Network. EBONE’s aims are develop system of biodiversity observation at regional, national and levels by assessing existing approaches in terms their validity applicability starting Europe, then expanding regions Africa. objective EBONE deliver: 1. A sound scientific basis for production statistical estimates stock change key indicators; 2. development estimating past changes forecasting testing policy options management strategies threatened ecosystems species; 3. proposal cost-effective system. There consensus that (EO) has role play biodiversity. With its capacity observe detailed spatial patterns variability across large areas regular intervals, our instinct suggests EO could deliver type temporal coverage beyond reach with in-situ efforts. Furthermore, when considering emerging networks observations, prospect enhancing quality information whilst reducing cost through integration compelling. This report gives realistic assessment integrating observations within context concept (cfr. EBONE-ID1.4). mainly based set targeted pilot studies. Building this assessment, presents series recommendations best using an effective, consistent sustainable scheme. The issues we faced were many: 1. Integration can be interpreted different ways. One possible interpretation is: combined use independent data sets but improved set; another one complement dataset. 2. improvement will vary stakeholder group: some seek more efficiency, others reliable (accuracy and/or precision); detail space time or everything. 3. requires link between datasets (EO in-situ). strength reflected electromagnetic radiation habitats observed function many variables, example: scale observations; timing adopted nomenclature classification; complexity landscape composition, structure physical environment; habitat land cover types under consideration. 4. available varies (function e.g. budget, size location region, cloudiness, international investment airborne campaigns technology) which determines capability required output. EO ways, depending wanted achieve improvement. We aimed accuracy (i.e. reduction error indicator estimate calculated environmental zone). would also provide correlated data. EBONE initial development, focused three main indicators covering: (i) extent interest general assessment; (ii) abundance distribution selected species (birds, butterflies plants); (iii) fragmentation natural semi-natural areas. For extent, decided it did not matter how was integrated as long demonstrate acceptable accuracies achieved precision consistently improved. used map General Habitat Classification. considered following where roles: using samples re-calibrate independently derived from EO; improving sampled statistics, post-stratification data; train classification into delivers full larger number samples. For above cases impact sampling strategy employed have achieved. Restricted access wide prevented work ‘abundance species’. With respect ‘fragmentation’, investigated ways delivering measures meaningful observations.