@article{PAR00022923,
  title = {{I}dentifying seasonal groundwater-irrigated cropland using multi-source {NDVI} time-series images},
  author = {{S}harma, {A}. and {H}ubert-{M}oy, {L}. and {B}uvaneshwari, {S}. and {S}ekhar, {M}. and {R}uiz, {L}aurent and {M}oger, {H}. and {B}andyopadhyay, {S}. and {C}orgne, {S}.},
  editor = {},
  language = {{ENG}},
  abstract = {{G}roundwater has become a major source of irrigation in the past few decades in {I}ndia, but as it comes from millions of individual borewells owned by smallholders irrigating small fields, it is difficult to quantify the actual irrigated area across seasons and years. {T}his study's main goal was to monitor seasonal irrigated cropland using multiple optical satellite images. {T}he proposed research was performed over the {B}erambadi watershed, an experimental site in southern peninsular {I}ndia. {W}hile cloud cover during crop growth is the greatest obstacle to optical remote sensing in tropical regions, the cloud-free images from multiple optical satellite platforms ({L}andsat-8 ({OLI}), {EO}1 ({ALI}), {IRS}-{P}6 ({LISS}3 and {LISS}4), and {S}pot5{T}ake5 ({HRG}2)) were used to fill data gaps during crop growth periods. {T}he seasonal cumulative normalized difference vegetation index ({NDVI}) was calculated and resampled at 5 m spatial resolution for various cropping seasons. {T}he support vector machine ({SVM}) classification was applied to seasonal cumulative {NDVI} images for irrigated cropland area classification. {V}alidation of the classified irrigated cropland was performed by calculating kappa coefficients for three cropping seasons (summer, kharif, and rabi) from 2014-2016 using ground observations. {K}appa coefficients ranged from 0.81-0.96 for 2014-2015 and 0.62-0.89 for 2015-2016, except for summer 2016, when it was 1.00. {G}roundwater irrigation in the watershed ranged from 4.6% to 16.5% of total cropland during these cropping seasons. {T}hese results showed that multi-source optical satellite data are relevant for quantifying areas under groundwater irrigation in tropical regions.},
  keywords = {groundwater irrigation ; optical remote sensing ; {NDVI} ; support vector ; machine classifier ; {K}abini critical zone observatory ; {INDE} ; {KABINI} {BASSIN} ; {BERAMBADI} {BASSIN} {VERSANT}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {13},
  numero = {10},
  pages = {1960 [21 p.]},
  year = {2021},
  DOI = {10.3390/rs13101960},
  URL = {https://www.documentation.ird.fr/hor/{PAR}00022923},
}