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SUMMARY:Identifying direct deforestation drivers in sub-Saharan Africa usi
 ng deep learning and high-resolution satellite imagery  - Amandine Debus
DTSTART:20230728T120000Z
DTEND:20230728T130000Z
UID:TALK202495@talks.cam.ac.uk
CONTACT:114742
DESCRIPTION:Deforestation rates in sub-Saharan Africa have received less a
 ttention than those in other tropical regions\, despite evidence for incre
 asing rates in the last twenty years. For example\, in Cameroon\, forests 
 are threatened by foreign investments in large agro-industrial concessions
 \, the expansion of small-scale agriculture\, and increasing mining activi
 ty. However\, there is a current lack of a detailed and comprehensive auto
 mated classification for the land-use changes leading to deforestation\, w
 hich is crucial to prioritise interventions. Earth observation (EO) and de
 ep learning offer a promising solution for effective monitoring\, but\, so
  far\, proposed approaches in the Congo Basin have not been able to go bey
 ond ‘broad’ categories of deforestation drivers and are not adapted to
  country-specific dynamics. In this talk\, I present the challenges faced 
 when building a newly-consolidated satellite imagery reference dataset for
  Cameroon and a new approach to automatically classify direct drivers of d
 eforestation for this case study.\n\nAmandine Debus is a second-year PhD s
 tudent in the Department of Geography. Amandine’s PhD focuses on using h
 igh-resolution optical (e.g. PlanetScope) satellite data\, machine learnin
 g and deep learning techniques\, and socio-economic data (e.g. governance\
 , demographic) to better understand and monitor land-use changes in sub-Sa
 haran Africa. Using Cameroon as a case study\, Amandine’s project aims t
 o model the spatial and temporal dynamics of transitions from forest to mu
 ltiple land-use types\, and the socio-economic drivers behind them. She is
  working with the International Institute for Sustainable Development (IIS
 D) and in-country partners to ensure her models are tailored to maximise t
 heir reusability for ongoing policy-making and conservation programmes.
LOCATION:FW 11\, William Gates Building. Zoom link: https://cl-cam-ac-uk.z
 oom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&amp\;from=addon 
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