Mapping irrigated areas using MODIS 250 meter time-series data: a study on Krishna river basin (India)
Mapping 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...
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| Format: | Journal Article |
| Language: | Inglés |
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MDPI
2011
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| Online Access: | https://hdl.handle.net/10568/165944 |
| _version_ | 1855543267499704320 |
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| author | Gumma, Murali Krishna Thenkabail, Prasad S. Nelson, Andrew |
| author_browse | Gumma, Murali Krishna Nelson, Andrew Thenkabail, Prasad S. |
| author_facet | Gumma, Murali Krishna Thenkabail, Prasad S. Nelson, Andrew |
| author_sort | Gumma, Murali Krishna |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Mapping 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). |
| format | Journal Article |
| id | CGSpace165944 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2011 |
| publishDateRange | 2011 |
| publishDateSort | 2011 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | CGSpace1659442025-02-19T14:27:11Z Mapping irrigated areas using MODIS 250 meter time-series data: a study on Krishna river basin (India) Gumma, Murali Krishna Thenkabail, Prasad S. Nelson, Andrew crop groundwater growth india irrigated conditions irrigated farming krishna basin moderate resolution imaging spectrometer mapping normalized difference vegetation index remote sensing sowing surface water time series watersheds Mapping 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). 2011-01-13 2024-12-19T12:55:39Z 2024-12-19T12:55:39Z Journal Article https://hdl.handle.net/10568/165944 en Open Access MDPI Gumma, Murali Krishna; Thenkabail, Prasad S. and Nelson, Andrew. 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 |
| spellingShingle | crop groundwater growth india irrigated conditions irrigated farming krishna basin moderate resolution imaging spectrometer mapping normalized difference vegetation index remote sensing sowing surface water time series watersheds Gumma, Murali Krishna Thenkabail, Prasad S. Nelson, Andrew Mapping irrigated areas using MODIS 250 meter time-series data: a study on Krishna river basin (India) |
| title | Mapping irrigated areas using MODIS 250 meter time-series data: a study on Krishna river basin (India) |
| title_full | Mapping irrigated areas using MODIS 250 meter time-series data: a study on Krishna river basin (India) |
| title_fullStr | Mapping irrigated areas using MODIS 250 meter time-series data: a study on Krishna river basin (India) |
| title_full_unstemmed | Mapping irrigated areas using MODIS 250 meter time-series data: a study on Krishna river basin (India) |
| title_short | Mapping irrigated areas using MODIS 250 meter time-series data: a study on Krishna river basin (India) |
| title_sort | mapping irrigated areas using modis 250 meter time series data a study on krishna river basin india |
| topic | crop groundwater growth india irrigated conditions irrigated farming krishna basin moderate resolution imaging spectrometer mapping normalized difference vegetation index remote sensing sowing surface water time series watersheds |
| url | https://hdl.handle.net/10568/165944 |
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