Opendata, web and dolomites

MF-RADAR

Multi-frequency RADAR imaging for the analysis of tropical forest structure in the Amazon

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 MF-RADAR project word cloud

Explore the words cloud of the MF-RADAR project. It provides you a very rough idea of what is the project "MF-RADAR" about.

systematic    tapajos    impacts    probability    rainforest    researcher    training    maximum    postgraduate    emissions    ro1    basin    satellites    gas    brazil    stabilising    learning    participate    explanatory    machine    ro2    communicate    modules    ro4    observation    estimation    ro    career    complementary    class    techniques    associations    integration    threat    stores    academic    forest    fellowship    synthetic    greenhouse    senior    skills    frequency    biodiversityof    amounts    preserve    species    entropy    mapping    marie    world    structural    data    maps    enforce    hotspot    richness    amazon    tree    she    disturbances    biomass    witha    structure    international    satellite    public    deforestation    to1    radar    abundance    geomorphometry    regional    earth    to4    stocks    global    geomorphometric    acquire    secondments    to3    estimate    carbon    map    variables    transfer    leadership    posing    floristic    curie    climate    degradation    remote    aboveground    scientific    ro3    biodiversity    expertise    reduce    position    aperture    sensing    diversity    fellow    power    areto    tropical    courses    to2   

Project "MF-RADAR" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITY OF LEICESTER 

Organization address
address: UNIVERSITY ROAD
city: LEICESTER
postcode: LE1 7RH
website: www.le.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://www2.le.ac.uk/departments/geography/research/projects/mf-radar/mf-radar
 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 2016
 Duration (year-month-day) from 2016-01-01   to  2017-12-31

 Partnership

Take a look of project's partnership.

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

Map

 Project objective

The tropical rainforest of the Amazon basin is a global biodiversity hotspot and stores significant amounts of carbon, stabilising the regional and global climate. Deforestation, forest degradation and climate change impacts are posing a threat to its future. This Marie Curie fellowship will develop a systematic integration of geomorphometry methods with satellite remote sensing techniques from Synthetic Aperture Radar to study the floristic-structural associations in the tropical forest of the Amazon, map disturbances and degradation, reduce greenhouse gas emissions and preserve floristic diversity. Its research objectives (RO) areto identify geomorphometric variables related to tree species abundance and richness in Tapajos, Brazil, and structural forest variables from multi-frequency radar satellites (RO1); to analyse tree species, radar data and geomorphometry witha machine-learning (maximum-entropy) approach to produce species probability maps (RO2); to determine the explanatory power of the integrated radar/geomorphometry approach for biomass mapping (RO3); and to estimate the aboveground carbon stocks (RO4). The technical and complementary training objectives (TO) are to learn advanced radar processing skills for forest structure estimation (TO1); to learn effective data integration techniques for multi-frequency radar data and geomorphometric parameters (TO2); to learn how to communicate scientific research to the wider public (TO3); and to acquire complementary and leadership skills (TO4). The fellow will undertake a world-class programme of research and training in Earth Observation research methods, several international secondments, participate in postgraduate training modules and specific researcher development courses in complementary skills. She will transfer her expertise in tropical forest structure and biodiversityof the Amazon to Europe and develop her academic career to reach and enforce a senior academic position.

 Publications

year authors and title journal last update
List of publications.
2016 Polyanna da Conceição Bispo, João Roberto dos Santos, Márcio de Morisson Valeriano, Paulo Maurício Lima de Alencastro Graça, Heiko Balzter, Helena França, Pitágoras da Conceição Bispo
Predictive Models of Primary Tropical Forest Structure from Geomorphometric Variables Based on SRTM in the Tapajós Region, Brazilian Amazon
published pages: e0152009, ISSN: 1932-6203, DOI: 10.1371/journal.pone.0152009
PLOS ONE 11/4 2019-06-18
2017 Polyanna da Conceição Bispo, Heiko Balzter, Yadvinder Malhi, J. W. Ferry Slik, João Roberto dos Santos, Camilo Daleles Rennó, Fernando D. Espírito-Santo, Luiz E. O. C. Aragão, Arimatéa C. Ximenes, Pitágoras da Conceição Bispo
Drivers of metacommunity structure diverge for common and rare Amazonian tree species
published pages: e0188300, ISSN: 1932-6203, DOI: 10.1371/journal.pone.0188300
PLOS ONE 12/11 2019-06-18

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "MF-RADAR" 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 "MF-RADAR" are provided by the European Opendata Portal: CORDIS opendata.

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

DGLC (2019)

Domain-general language control: Evidence from the switching paradigm

Read More  

MTrill (2019)

Machine Translation Impact on Language Learning

Read More  

LiquidEff (2019)

LiquidEff: Algebraic Foundations for Liquid Effects

Read More