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Remote sensing of industrial palm groves in Cameroon
Prune Christobelle Komba Mayossa1, Sébastien Gadal2, Jean-Marc Roda3.
The measurement of biomass can be obtainedfrom remote sensing analysis and modelling , the impacts
of which are related to oil palm cultivation in industrial plantations. Our study aims at producing a spatial
model for oil palm biomass estimation, at different scales of spatial analysis. The study was carried out
in the industrial plantations of the Cameroonian Society of Palm Groves (SOCAPALM). The developed
methodology combined: (i) the mapping of palm groves (Kumar, 2015), (ii) the characterisationof palm
groves (Gadal, 2013), (iii) biomass estimation, and (iv) the comparison of the obtained results with
Spot6, Landsat 7 ETM+ and Landsat 8 OLI images from 2001 to 2015. The first results were obtained
for the mapping of the SOCAPALM industrial palm groves between 2001 and 2015. The obtained maps
were highly correlated (Kappa of 0.91 for Spot 6, 0.92 for Landsat 7 and 0.82 for Lansat8), however,
because of the presence of mixed pixels, some confusion between oil palm and other classes were
observed. One of the factors affecting biomass estimation is spatial accuracy. Several improvements
have been suggested : (1) mapping palm groves at a subpixel scale using super-resolution mapping; (2)
developing a classification system of cartographic products. The use of satellites images with different
spatial resolutions may also help to generate new data taking into account the level of spatial analysis.
Affiliation:
- Aix-Marseille Universite, France
- Aix-Marseille Universite, France
- French Agricultural Research Centre for International Development (CIRAD), France
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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2 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (0.3) |
Rank |
Q4 (Multidisciplinary) |
Additional Information |
SJR (0.12) |
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