Wheat Acreage, Productivity and Production Estimation through Remote Sensing and GIS Techniques

Remote Sensing (RS) and Geographical Information System (GIS) technologies were used to estimate the acreage, productivity and production of wheat in Karlawad village of Karnataka, India. Such estimations are important for taking management decisions in precision farming. A cloud free LISS IV multispectral digital image of 5.8 m resolution of orbit 26798, path 202 and row 96, from IRS P6 satellite acquired on December 15th, 2008 was used for the investigation. ERDAS IMAGINE 9.0 image analysis software and Arc GIS 9.0 software were used for data processing and analyses. Vegetation indices such as Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI) and Transformed Vegetation Index (TVI) were computed from spectral reflectance values of wheat crop recorded at selected ground truth (GT) sites. The Leaf Area Index (LAI) of wheat crop at GT sites was recorded by using the equipment AccuPAR LAI meter of Decagon Devices Inc. USA. The estimated values of RS and GIS based wheat acreage, productivity and production were, 82.64 ha, 2801.5 kg per ha and 231.52 tons, respectively. The values of the correlation (r) between wheat productivity and NDVI, LAI, RVI and TVI were 0.892, 0.924, 0.892 and 0.890, respectively. Three productivity models using NDVI and LAI values either alone or in combination were compared for their performance. Among these models, a multiple regression model based on combination of NDVI and LAI with R2 value of 0.87 was found to explain the yield variability better than simple regression models based on either NDVI (R2 of 0.80) or LAI (R2 of 0.85). The study further revealed that the RS and GIS based estimations of acreage, productivity and production deviated from the data of Karnataka State Department of Agriculture (KSDA) by +3.19, +10.76 and +13.61 percent, respectively