@article{fdi:010071430,
  title = {{E}valuation and aggregation properties of thermal infra-red-based evapotranspiration algorithms from 100 m to the km scale over a semi-arid irrigated agricultural area},
  author = {{B}ahir, {M}. and {B}oulet, {G}illes and {O}lioso, {A}. and {R}ivalland, {V}. and {G}allego-{E}lvira, {B}. and {M}ira, {M}. and {R}odriguez, {J}. {C}. and {J}arlan, {L}ionel and {M}erlin, {O}livier},
  editor = {},
  language = {{ENG}},
  abstract = {{E}vapotranspiration ({ET}) estimates are particularly needed for monitoring the available water of arid lands. {R}emote sensing data offer the ideal spatial and temporal coverage needed by irrigation water management institutions to deal with increasing pressure on available water. {L}ow spatial resolution ({LR}) products present strong advantages. {T}hey cover larger zones and are acquired more frequently than high spatial resolution ({HR}) products. {C}urrent sensors such as {M}oderate-{R}esolution {I}maging {S}pectroradiometer ({MODIS}) offer a long record history. {H}owever, validation of {ET} products at {LR} remains a difficult task. {I}n this context, the objective of this study is to evaluate scaling properties of {ET} fluxes obtained at high and low resolution by two commonly used {E}nergy {B}alance models, the {S}urface {E}nergy {B}alance {S}ystem ({SEBS}) and the {T}wo-{S}ource {E}nergy {B}alance model ({TSEB}). {B}oth are forced by local meteorological observations and remote sensing data in {V}isible, {N}ear {I}nfra-{R}ed and {T}hermal {I}nfra-{R}ed spectral domains. {R}emotely sensed data stem from {A}dvanced {S}paceborne {T}hermal {E}mission and {R}eflection {R}adiometer ({ASTER}) and {MODIS} sensors, respectively, resampled at 100 m and 1000 m resolutions. {T}he study zone is a square area of 4 by 4 km(2) located in a semi-arid irrigated agricultural zone in the northwest of {M}exico. {W}heat is the dominant crop, followed by maize and vegetables. {T}he {HR} {ASTER} dataset includes seven dates between the 30 {D}ecember 2007 and 13 {M}ay 2008 and the {LR} {MODIS} products were retrieved for the same overpasses. {ET} retrievals from {HR} {ASTER} products provided reference {ET} maps at {LR} once linearly aggregated at the km scale. {T}he quality of this retrieval was assessed using eddy covariance data at seven locations within the 4 by 4 km(2) square. {T}o investigate the impact of input aggregation, we first compared to the reference dataset all fluxes obtained by running {TSEB} and {SEBS} models using {ASTER} reflectances and radiances previously aggregated at the km scale. {S}econd, we compared to the same reference dataset all fluxes obtained with {SEBS} and {TSEB} models using {MODIS} data. {LR} fluxes obtained by both models driven by aggregated {ASTER} input data compared well with the reference simulations and illustrated the relatively good accuracy achieved using aggregated inputs (relative bias of about 3.5% for {SEBS} and decreased to less than 1% for {TSEB}). {R}esults also showed that {MODIS} {ET} estimates compared well with the reference simulation (relative bias was down to about 2% for {SEBS} and 3% for {TSEB}). {D}iscrepancies were mainly related to fraction cover mapping for {TSEB} and to surface roughness length mapping for {SEBS}. {T}his was consistent with the sensitivity analysis of those parameters previously published. {T}o improve accuracy from {LR} estimates obtained using the 1 km surface temperature product provided by {MODIS}, we tested three statistical and one deterministic aggregation rules for the most sensible input parameter, the surface roughness length. {T}he harmonic and geometric averages appeared to be the most accurate.},
  keywords = {energy balance ; {T}hermal {I}nfra-{R}ed ; scaling ; {MEXIQUE} ; {ZONE} {SEMIARIDE}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {9},
  numero = {11},
  pages = {art. 1178 [27 p.]},
  ISSN = {2072-4292},
  year = {2017},
  DOI = {10.3390/rs9111178},
  URL = {https://www.documentation.ird.fr/hor/fdi:010071430},
}