Mapping irrigated areas using MODIS 250 meter time-series data: a study on Krishna river basin (India)

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dc.creatorGumma, Murali Krishna
dc.creatorThenkabail, Prasad S.
dc.creatorNelson, Andrew
dc.date2011-01-13
dc.date2024-12-19T12:55:39Z
dc.date2024-12-19T12:55:39Z
dc.date.accessioned2026-06-27T04:16:14Z
dc.descriptionMapping irrigated areas of a river basin is important in terms of assessing water use and food security. This paper describes an innovative remote sensing based vegetation phenological approach to map irrigated areas and then the differentiates the ground water irrigated areas from the surface water irrigated areas in the Krishna river basin (26,575,200 hectares) in India using MODIS 250 meter every 8-day near continuous time-series data for 2000–2001. Temporal variations in the Normalized Difference Vegetation Index (NDVI) pattern obtained in irrigated classes enabled demarcation between: (a) irrigated surface water double crop, (b) irrigated surface water continuous crop, and (c) irrigated ground water mixed crops. The NDVI patterns were found to be more consistent in areas irrigated with ground water due to the continuity of water supply. Surface water availability, on the other hand, was dependent on canal water release that affected time of crop sowing and growth stages, which was in turn reflected in the NDVI pattern. Double cropped and light irrigation have relatively late onset of greenness, because they use canal water from reservoirs that drain large catchments and take weeks to fill. Minor irrigation and ground water irrigated areas have early onset of greenness because they drain smaller catchments where aquifers and reservoirs fill more quickly. Vegetation phonologies of 9 distinct classes consisting of Irrigated, rainfed, and other land use classes were also derived using MODIS 250 meter near continuous time-series data that were tested and verified using groundtruth data, Google Earth very high resolution (sub-meter to 4 meter) imagery, and state-level census data. Fuzzy classification accuracies for most classes were around 80% with class mixing mainly between various irrigated classes. The areas estimated from MODIS were highly correlated with census data (R-squared value of 0.86).
dc.identifierhttps://hdl.handle.net/10568/165944
dc.identifier.urihttp://hdl.handle.net/123456789/27212
dc.languageen
dc.publisherMDPI
dc.rightsOpen Access
dc.sourceGumma, M.K., Thenkabail, P.S. and Nelson, A. 2011. Mapping irrigated areas using MODIS 250 meter time-series data: a study on Krishna river basin (India). Water, Volume 3 no. 1 p. 113-131
dc.subjectcrop
dc.subjectgroundwater
dc.subjectgrowth
dc.subjectindia
dc.subjectirrigated conditions
dc.subjectirrigated farming
dc.subjectkrishna basin
dc.subjectmoderate resolution imaging spectrometer
dc.subjectmapping
dc.subjectnormalized difference vegetation index
dc.subjectremote sensing
dc.subjectsowing
dc.subjectsurface water
dc.subjecttime series
dc.subjectwatersheds
dc.titleMapping irrigated areas using MODIS 250 meter time-series data: a study on Krishna river basin (India)
dc.typeJournal Article

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Instituto Internacional de Investigación del Arroz (IRRI)