@article{fdi:010091541,
  title = {{E}xploring fine-scale urban landscapes using satellite data to predict the distribution of {A}edes mosquito breeding sites},
  author = {{T}eillet, {C}laire and {D}evillers, {R}odolphe and {T}ran, {A}. and {C}atry, {T}hibault and {M}arti, {R}. and {D}essay, {N}adine and {R}wagitinywa, {J}. and {R}estrepo, {J}. and {R}oux, {E}mmanuel},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ackground {T}he spread of mosquito-transmitted diseases such as dengue is a major public health issue worldwide. {T}he {A}edes aegypti mosquito, a primary vector for dengue, thrives in urban environments and breeds mainly in artificial or natural water containers. {W}hile the relationship between urban landscapes and potential breeding sites remains poorly understood, such a knowledge could help mitigate the risks associated with these diseases. {T}his study aimed to analyze the relationships between urban landscape characteristics and potential breeding site abundance and type in cities of {F}rench {G}uiana ({S}outh {A}merica), and to evaluate the potential of such variables to be used in predictive models. {M}ethods {W}e use {M}ultifactorial {A}nalysis to explore the relationship between urban landscape characteristics derived from very high resolution satellite imagery, and potential breeding sites recorded from in-situ surveys. {W}e then applied {R}andom {F}orest models with different sets of urban variables to predict the number of potential breeding








sites where entomological data are not available. {R}esults {L}andscape analyses applied to satellite images showed that urban types can be clearly identified using texture indices. {T}he {M}ultiple {F}actor {A}nalysis helped identify variables related to the distribution of potential breeding sites, such as buildings class area, landscape shape index, building number, and the first component of texture indices. {M}odels predicting the number of potential breeding sites using the entire dataset provided an {R}-2 of 0.90, possibly influenced by overfitting, but allowing the prediction over all the study sites. {P}redictions of potential breeding sites varied highly depending on their type, with better results on breeding sites types commonly found in urban landscapes, such as containers of less than 200 {L}, large volumes and barrels. {T}he study also outlined the limitation offered by the entomological data, whose sampling was not specifically designed for this study. {M}odel outputs could be used as input to a mosquito dynamics model when no accurate field data are available. {C}onclusion {T}his study offers a first use of routinely collected data on potential breeding sites in a research study. {I}t highlights the potential benefits of including satellite-based characterizations of the urban environment to improve vector control strategies.},
  keywords = {{GUYANE} {FRANCAISE}},
  booktitle = {},
  journal = {{I}nternational {J}ournal of {H}ealth {G}eographics},
  volume = {23},
  numero = {1},
  pages = {18 [20 ]},
  ISSN = {1476-072{X}},
  year = {2024},
  DOI = {10.1186/s12942-024-00378-3},
  URL = {https://www.documentation.ird.fr/hor/fdi:010091541},
}