@article{fdi:010086062,
  title = {{M}odeling evapotranspiration at larger temporal scales : effects of temporal aggregation and data gaps},
  author = {{A}thira, {K}. {V}. and {E}swar, {R}. and {B}oulet, {G}illes and {N}igam, {R}. and {B}hattacharya, {B}. {K}.},
  editor = {},
  language = {{ENG}},
  abstract = {{E}vapotranspiration ({ET}) at weekly and monthly time scales is often needed for various applications. {W}hen using remote sensing ({RS})-based models, this can be achieved either by averaging all the required input variables to the intended time scale and simulating {ET} using models (input aggregation), or by estimating daily {ET} from the models and averaging to weekly or monthly {ET} (output aggregation). {I}t is not clear if both these aggregation approaches yield the same outcome when using {RS}-based models for the estimation of {ET}. {A}nother issue in obtaining {ET} at longer time scales is the lack of enough satellite observations to estimate {ET} with reasonable accuracy. {T}his study aimed to compare the input and output aggregation approaches to obtain {ET} at weekly and monthly time scales using three {RS} {ET} models, namely, {P}riestley-{T}aylor {J}et {P}ropulsion {L}ab ({PT}-{JPL}), {S}oil {P}lant {A}tmosphere and {R}emote {S}ensing {E}vapotranspiration ({SPARSE}), and {S}urface {T}emperature {I}nitiated {C}losure ({STIC}) models. {T}he study was conducted using in situ data over six sites of different agro-climatic conditions in {I}ndia, {T}unisia, and {F}rance. {T}he results indicate that the input aggregation provided relatively better results for monthly and weekly {ET} values than the output aggregation, having a lower {RMSE} (1-40%). {F}urther, it was found that at least seven to eight satellite observations per month are required to obtain reliable {ET} estimate when using {RS}-based models.},
  keywords = {evapotranspiration ; temporal aggregation ; {FRANCE} ; {TUNISIE} ; {INDE}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {14},
  numero = {17},
  pages = {4142 [14 p.]},
  year = {2022},
  DOI = {10.3390/rs14174142},
  URL = {https://www.documentation.ird.fr/hor/fdi:010086062},
}