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WP3 Improving tools and methods for data analysis and interface

Objectives

  • Developing and refining analytical  and presentational tools for application in other segments of the EU BON
    workplan,  and for wider use  by the research and policy community,  specifically:
  • To develop practical tools for assessing vegetation status and trends by combining  remote sensing and environmental datasets
  • To refine biodiversity up-scaling and population  downscaling tools for non-specialist use  to increase accessibility
  • To develop new distributional  models to improve applicability for poorly documented species and those exhibiting strong  spatial  patterning
  • To develop new and improved  tools for preparing and mining biodiversity data  from the published literature

Key messages

  • By combining remotely sensed images with environmental data, we can improve our ability to map European habitats, allowing improved biodiversity informatics and mapping of uncertainty.
  • Specialist tools developed in macro-ecological research can be applied to estimating fine-scale occupancy and biodiversity at finer and coarser spatial scales.
  • Tools can be developed both for use on poorly-studied (e.g. marine, and many terrestrial invertebrate) systems and for data-rich (e.g. terrestrial vertebrate) systems.
  • The published literature can be a productive source of untapped biodiversity records for global biodiversity informatics, especially for the little known species which constitute the majority of biodiversity.

Tasks

Task 3.1 Advanced tools for interpreting satellite or aerial imagery using environmental datasets and machine learning methods 
Task 3.2 Techniques for up-scaling and downscaling biotic datasets 
Task 3.3 Enhanced methods for species distribution modelling 
Task 3.4 Developing tools to prepare, extract and mine published legacy and prospective biodiversity literature 
 
Outcomes
  • HieRanFor -- An R package implementing a hierarchical RandomForest approach for habitat and land-cover/land-use classification models (D3.1).
  • Fourier transforms -- A method to detect landscape fragmentation changes using multi-temporal remotely sensed images (D3.1).
  • LST -- Land Surface Temperature datasets at fine spatial (250m) and temporal (monthly) resolution, which may be used for SDMs and other environmental analyses (D3.1).
  • UpScaling -- An R package implementing several published and novel tools that predict species richness at coarse spatial scales using local biodiversity data (D3.1).
  • downscale -- An R package implementing 10 downscaling models for estimating fine scale species occupancy, alongside atlas creating tools (D3.1).
  • VirtualEcologist -- An R application to identify optimal monitoring and sampling approaches by mimicking the process of field sampling from simulation model outcomes (D3.1).
  • Create-Your-Own-Map -- An AquaMaps based tool that streamlines the input of expert opinions in editing modelled species distribution maps (D3.2).
  • rAquaMaps -- An R package implementing the AquaMAps algorithm for robust species distribution mapping and associated tools (D3.2).
  • Hybrid SDMs -- An R application of four different models that predict species distribution while accounting while accounting for both environmental and spatial aspects (D3.2).
  • Improved freshwater SDMs -- A guideline framework to adapt species distribution modelling techniques to freshwater environments (D3.2).
  • Diversity calculator -- a software package facilitating the calculation of alpha and beta diversity on a large stack of raster (grid) data (D3.2)
  • Data mining tool -- Development of tools to prepare, extract and mine published legacy and prospective biodiversity literature (MS341).
  • A remote-sensing task force has been established.
  • Cross linkage with other work-packages and other projects/institutes was established.

 

Contact us

Prof. William Kunin  Dr. Duccio Rocchini  Dr. Donat Agosti  Dr. Yoni Gavish 
WP Leader Deputy Leader Deputy Leader EU BON Researcher
University of Leeds  Fondazione Edmund Mach (FEM) PLAZI University of Leeds 
Upscaling and downscaling of ecological information Remote sensing applications Biodiversity informatics Biodiversity Patterns, Community Modelling. Species Distribution Models, Spatial Ecology 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


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flag big This project has received funding from the European Union’s Seventh Programme for research, technological development and demonstration under grant agreement No 308454.