Christophe Proisy
Christophe
Proisy
Head of the Department
:
2231650
:
2231605

Select Publications

Books

(1)
BURGOS A., [et al.] and PROISY C., 2018. Mangrove. Une forêt dans la mer, CNRS & Le Cherche-Midi, Paris, 168 pages, ISBN: 978-2-7491-5764-1, Sous la direction de F. Fromard, E. Michaud, M. Hossaert-McKey.

Book chapters

(1)
PLOTON P., PÉLISSIER R., BARBIER N., PROISY C., RAMESH B.R. and COUTERON P., 2013. Canopy Texture Analysis for Large-Scale Assessments of Tropical Forest Stand Structure and Biomass, In: Lowman M., Devy S., Ganesh T. (ed), Treetops at Risk : Challenges of Global Canopy Ecology and Conservation, Springer, New York, p. 237-245, ISBN: 978-1-4614-7160-8. [Publisher link]

Peer-reviewed journal articles

(7)
WALCKER R., GANDOIS L., PROISY C. and [et al.], 2018. Control of ‘blue carbon’ storage by mangrove ageing: evidence from a 66-year chronosequence in French Guiana, Global Change Biology, doi : 10.1111/gcb.1410. [Publisher link]
MUTHUSANKAR G., PROISY C., BALASUBRAMANIAN D., BAUTES N., BHALLA R.S., MATHEVET R., RICOUT A., SENTHIL BABU D. and VASUDEVAN S., 2018. When socio-economic plans exacerbate vulnerability to physical coastal processes on the South East Coast of India, Journal of Coastal Research, 85 : 10.2112/SI85-001.1.
PROISY C., [et al.], MUTHUSANKAR G., [et al.] and RICOUT A., 2017. Monitoring mangrove forests after aquaculture abandonment using time series of very high spatial resolution satellite images: A case study from the Perancak estuary, Bali, Indonesia, Marine Pollution Bulletin, DOI : http://dx.doi.org/10.1016/j.marpolbul.2017.05.056. [Publisher link]
GUSMAWATI N., [et al.], PROISY C. and [et al.], 2017. Surveying shrimp aquaculture pond activity using multitemporal VHSR satellite images - case study from the Perancak estuary, Bali, Indonesia, Marine Pollution Bulletin, http://dx.doi.org/10.1016/j.marpolbul.2017.03.059. [Publisher link]
PLOTON P., AYYAPPAN N., BALACHANDRAN N., BARATHAN N., PROISY C., RÉJOU-MÉCHAIN M., PÉLISSIER R. and [et al.], 2017. Toward a general tropical forest biomass prediction model from very high resolution optical satellite images, Remote Sensing of Environment, 200 : 140-153, DOI : http://dx.doi.org/10.1016/j.rse.2017.08.001. [Publisher link]
VEGA C., VEPAKOMMA U., MOREL J., BADER J.-L., RAJASHEKAR G., JHA C.S., FERET J., PROISY C., PÉLISSIER R. and DADHWAL V.K., 2015. Aboveground-Biomass Estimation of a Complex Tropical Forest in India Using Lidar, Remote Sensing, 7 : 10607-10625, DOI: 10.3390/rs70810607. [Publisher link]
PLOTON P., PÉLISSIER R., PROISY C., FLAVENOT T., BARBIER N., RAI S.N. and COUTERON P., 2012. Assessing aboveground tropical forest biomass using Google Earth canopy images, Ecological Applications, 22 (3) : 993-1003. [Publisher link]