start-ver=1.4
cd-journal=joma
no-vol=18
cd-vols=
no-issue=1
article-no=
start-page=14
end-page=21
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2024
dt-pub=2024
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Efficient agricultural monitoring: a methodology for assessing individual farmer adherence to rice-planting schedule for tertiary irrigation system under the Muda Irrigation Scheme using Earth observation datasets
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=The tertiary irrigation system (TIS) was designed for the Muda Irrigation Scheme (MIS) to distribute irrigation water to farmers' fields to ensure the reliability of water supply for cultivating rice paddies twice a year. Variability in farming practices, influenced by farmer autonomy along the tertiary canal adds complexity and uncertainty to adherence monitoring. Traditional on -site data collection methods are limited in scope and efficiency, whereas Earth observation (EO) enables continuous monitoring. In this study, we introduced a methodology that uses EO datasets to monitor individual field adherence to rice -planting schedules under TIS. These tools improve the monitoring of rice -planting schedule adherence by identifying non -adherent fields for further countermeasures. This study highlights the potential use of EO datasets and advanced data processing techniques for efficient agricultural monitoring.
en-copyright=
kn-copyright=

en-aut-name=ZahirAliya Mhd
en-aut-sei=Zahir
en-aut-mei=Aliya Mhd
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=

en-aut-name=SomuraHiroaki
en-aut-sei=Somura
en-aut-mei=Hiroaki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=

en-aut-name=MoroizumiToshitsugu
en-aut-sei=Moroizumi
en-aut-mei=Toshitsugu
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=

affil-num=1
en-affil=Graduate School of Environmental and Life Science, Okayama University
kn-affil=

affil-num=2
en-affil=Graduate School of Environmental and Life Science, Okayama University
kn-affil=

affil-num=3
en-affil=Graduate School of Environmental and Life Science, Okayama University
kn-affil=
en-keyword=Google Earth Engine
kn-keyword=Google Earth Engine
en-keyword=agricultural practices
kn-keyword=agricultural practices
en-keyword=irrigation
kn-keyword=irrigation
en-keyword=remote sensing
kn-keyword=remote sensing
en-keyword=Sentinel-1
kn-keyword=Sentinel-1
END