@article{fdi:010079868,
  title = {{S}tudying land cover changes in a malaria-endemic {C}ambodian district : considerations and constraints},
  author = {{P}epey, {A}. and {S}ouris, {M}arc and {V}antaux, {A}. and {M}orand, {S}. and {L}ek, {D}. and {M}ueller, {I}. and {W}itkowski, {B}. and {H}erbreteau, {V}incent},
  editor = {},
  language = {{ENG}},
  abstract = {{M}alaria control is an evolving public health concern, especially in times of resistance to insecticides and to antimalarial drugs, as well as changing environmental conditions that are influencing its epidemiology. {M}ost literature demonstrates an increased risk of malaria transmission in areas of active deforestation, but knowledge about the link between land cover evolution and malaria risk is still limited in some parts of the world. {I}n this study, we discuss different methods used for analysing the interaction between deforestation and malaria, then highlight the constraints that can arise in areas where data is lacking. {F}or instance, there is a gap in knowledge in {C}ambodia about components of transmission, notably missing detailed vector ecology or epidemiology data, in addition to incomplete prevalence data over time. {S}till, we illustrate the situation by investigating the evolution of land cover and the progression of deforestation within a malaria-endemic area of {C}ambodia. {T}o do so, we investigated the area by processing high-resolution satellite imagery from 2018 (1.5 m in panchromatic mode and 6 m in multispectral mode) and produced a land use/land cover map, to complete and homogenise existing data from 1988 and from 1998 to 2008 (land use/land cover from high-resolution satellite imagery). {F}rom these classifications, we calculated different landscapes metrics to quantify evolution of deforestation, forest fragmentation and landscape diversity. {O}ver the 30-year period, we observed that deforestation keeps expanding, as diversity and fragmentation indices globally increase. {B}ased on these results and the available literature, we question the mechanisms that could be influencing the relationship between land cover and malaria incidence and suggest further analyses to help elucidate how deforestation can affect malaria dynamics.},
  keywords = {malaria ; deforestation ; remote sensing ; {GIS} ; land cover ; landscape ; metrics ; {C}ambodia ; {CAMBODGE}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {12},
  numero = {18},
  pages = {2972 [21 ]},
  year = {2020},
  DOI = {10.3390/rs12182972},
  URL = {https://www.documentation.ird.fr/hor/fdi:010079868},
}