Opendata, web and dolomites

FOREST 3D - ECOCARB SIGNED

Integration of innovative remote sensing techniques for optimum modelling of tropical forest primate habitat and carbon storage

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

Project "FOREST 3D - ECOCARB" data sheet

The following table provides information about the project.

Coordinator
BOURNEMOUTH UNIVERSITY 

Organization address
address: FERN BARROW BOURNEMOUTH UNIVERSITY
city: POOLE
postcode: BH12 5BB
website: www.bournemouth.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website https://go-leap.wixsite.com/home
 Total cost 183˙454 €
 EC max contribution 183˙454 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2014
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2015
 Duration (year-month-day) from 2015-10-01   to  2017-09-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    BOURNEMOUTH UNIVERSITY UK (POOLE) coordinator 183˙454.00

Map

 Project objective

Tropical forests are being destroyed at a rate of 1.5 acres every second due to human activities, thereby accelerating climate change through impacts on the carbon cycle and causing the extinction of species dependent on these habitats. Over the past 20 years the EU has been the largest net importer of 'embodied deforestation', significantly ahead of trading powers like China or North America. This trend is at odds with EU commitments to halt forest loss and mitigate climate change over the next 20 years. In the face of such immediate and globally significant issues, there is a lack of robust scientific knowledge on how tropical deforestation and degradation affects ecosystem stability and carbon pools. There is a need to develop systems that can rapidly assess tropical forest structure and relate this to carbon stocks stored in tree biomass and to habitat quality for keystone species, like primates. Remote sensing systems, such as those available from Earth observation satellites or aircraft, can deliver data on forest structure and composition. This project will utilise innovative new methods of acquiring detailed 3-dimensional data of tropical forests at a landscape-scale, using remote sensing systems on aircraft and unmanned aerial vehicles (UAVs), in order to model primate habitat and measure forest carbon stocks. The project will, for the first time, link forest structure in 3-D directly to primate behaviour and forest use, and will develop cost-effective remote sensing methods using UAVs for monitoring changes in habitats and forest carbon stocks. This innovative project brings together a researcher with expertise in the processing and analysis of data from airborne remote sensing systems, with an internationally recognised group with expertise in remote sensing, geospatial analysis, ecological modelling and primate ecology to evaluate and develop new methods to support a managed and appropriate balance of conservation and economic aims for tropical forests.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "FOREST 3D - ECOCARB" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "FOREST 3D - ECOCARB" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.3.2.)

MarshFlux (2020)

The effect of future global climate and land-use change on greenhouse gas fluxes and microbial processes in salt marshes

Read More  

MetAeAvIm (2019)

The Role of the Metabolism in Mosquito Immunity against Dengue virus in Aedes aegypti

Read More  

SingleCellAI (2019)

Deep-learning models of CRISPR-engineered cells define a rulebook of cellular transdifferentiation

Read More