Genetically modified Cotton species detection by LISS-III satellite data

Abstract

It is possible to infer the genetically modified species by using remotely sensed data. Using ERDAS software the algorithm of BT (Bacillus thuringiensis) Cotton in Punjab, India was developed successfully. GPS enabled space technology has the potential to identify the exact location of Bt Cotton by generating Normalized Difference Vegetation Index (NDVI) for the calculation of total area covered by this species. It was possible to develop a correlation in between genetically modified Cotton crop and NDVI value. In parts of Bhatinda district of Punjab the yield of Bt Cotton and NDVI showing R 2 value of more than 4.5 in regression analysis. A correlation matrix was also generated which shows that NDVI values of BT cotton has reasonably acceptable correlation with Total Dissolved Solids (TDS) of soil and water also. Through remote sensing it is possible to quantify on a global scale the total acreage dedicated to these and other crops at any time. Of greater importance is accurately (best case 90%) estimating the expected yields of each crop locally, regionally or globally. It can be done by first computing the areas dedicated to each crop and then incorporating reliable yield assessment per unit area, which can be measured at representative ground truth sites. Usually, the yield estimates obtained from satellite data are more comprehensive and earlier (often by weeks) than determined conventionally as harvesting approaches 1 . Use of Satellite data for genetically modified crop needs to generate location specific spectral anomalies 2,3 . Use of multispectral satellite data helps to generate NDVI (Normalized Difference Vegetation Index), which can be correlated with the landuse, landcover, soil moisture, soil quality and groundwater quality to estimate the deterministic yield of BT cotton crops 4,5,6 .