Irrigated Area Maps and Statistics of India Using Remote Sensing and National Statistics

Thenkabail, P S and Dheeravath, V and Biradar, C M and Gangalakunta, O R P and Noojipady, P and Gurappa, C and Velpuri, M and Gumma, M K and Li, Y (2009) Irrigated Area Maps and Statistics of India Using Remote Sensing and National Statistics. Remote Sensing , 1 (2). pp. 50-67. ISSN 2072-4292

[img] PDF - Published Version
Restricted to ICRISAT users only

Download (950kB) | Request a copy


The goal of this research was to compare the remote-sensing derived irrigated areas with census-derived statistics reported in the national system. India, which has nearly 30% of global annualized irrigated areas (AIAs), and is the leading irrigated area country in the World, along with China, was chosen for the study. Irrigated areas were derived for nominal year 2000 using time-series remote sensing at two spatial resolutions: (a) 10-km Advanced Very High Resolution Radiometer (AVHRR) and (b) 500-m Moderate Resolution Imaging Spectroradiometer (MODIS). These areas were compared with the Indian National Statistical Data on irrigated areas reported by the: (a) Directorate of Economics and Statistics (DES) of the Ministry of Agriculture (MOA), and (b) Ministry of Water Resources (MoWR). A state-by-state comparison of remote sensing derived irrigated areas when compared with MoWR derived irrigation potential utilized (IPU), an equivalent of AIA, provided a high degree of correlation with R2 values of: (a) 0.79 with 10-km, and (b) 0.85 with MODIS 500-m. However, the remote sensing derived irrigated area estimates for India were consistently higher than the irrigated areas reported by the national statistics. The remote sensing derived total area available for irrigation (TAAI), which does not consider intensity of irrigation, was 101 million hectares (Mha) using 10-km and 113 Mha using 500-m. The AIAs, which considers intensity of irrigation, was 132 Mha using 10-km and 146 Mha using 500-m. In contrast the IPU, an equivalent of AIAs, as reported by MoWR was 83 Mha. There are “large variations” in irrigated area statistics reported, even between two ministries (e.g., Directorate of Statistics of Ministry of Agriculture and Ministry of Water Resources) of the same national system. The causes include: (a) reluctance on part of the states to furnish irrigated area data in view of their vested interests in sharing of water, and (b) reporting of large volumes of data with inadequate statistical analysis. Overall, the factors that influenced uncertainty in irrigated areas in remote sensing and national statistics were: (a) inadequate accounting of irrigated areas, especially minor irrigation from groundwater, in the national statistics, (b) definition issues involved in mapping using remote sensing as well as national statistics, (c) difficulties in arriving at precise estimates of irrigated area fractions (IAFs) using remote sensing, and (d) imagery resolution in remote sensing. The study clearly established the existing uncertainties in irrigated area estimates and indicates that both remote sensing and national statistical approaches require further refinement. The need for accurate estimates of irrigated areas are crucial for water use assessments and food security studies and requires high emphasis.

Item Type: Article
Uncontrolled Keywords: GIAM; irrigated areas; India; remote sensing; irrigation statistics
Subjects: Others > Agriculture-Farming, Production, Technology, Economics
Depositing User: Mr Sanat Kumar Behera
Date Deposited: 24 Oct 2013 14:23
Last Modified: 18 Dec 2015 06:49
Official URL:
Projects: GIAM Project
Funders: Indian Council of Agricultural Research
Acknowledgement: Dr Gumma Muralikrishna is presently associated with ICRISAT, Authors are very grateful to Prof. Frank Rijsberman, former DG, IWMI, for great support for GIAM project. Authors also thankful to Indian Council of Agricultural Research (ICAR), India for encouraging an India-focused GIAM work. The encouragement of Director, National Bureau of Soil Survey & Land Use Planning (NBSS&LUP) is greatly acknowledged. The support of staff at IWMI (Delhi office) has greatly acknowledged. The help and suggestions received from Mr. Upali Amarasinghe (IWMI) in preparation of manuscript are much appreciated. Authors would like to thank the 2 anonymous reviewers for providing very helpful and positive comments that certainly improved Remote Sens. 2009, 1 66 the quality of this paper. The manuscript is not internally reviewed by USGS, so in no way does the views expressed in the paper can be attributed to USGS.
View Statistics

Actions (login required)

View Item View Item