Application of remote sensing for detection of stress in Cotton induced by pests in Hisar

The study emphasizes the application of remote sensing approach in complement with weather based statistical forewarning for taking effective IPM. Forecasts based on meteorological parameters and crop phenology helps to prepare pest weather calendar for predicting the pest attack in advance and this can be monitored with the remote sensing technique on real-time basis. In this study pest infestation in the research field in Hisar, India is assessed with the help of LANDSAT images for the year 2013–18. Vegetation indices such as NDVI and Ndwiis calculated for area of interest after cloudmasking. These indices were further analysed with the crop calendar and validated with the field observations. The NDVI and NDWI values is minimum for the year 2013, 2015 and 2018 in comparison to 2014, 2016 and 2017, respectively, which is reflective of stress the crop was experiencing which was corroborated as pest attack above ETL as per field observations. The peak in the values are gained during the September 2017 showing good plant health during the year. As observed in the year 2013 and 2015, the major threat was Cotton Leaf Curl Disease (CLCuD) transmitted through whitefly and accompanied by other sucking pests like thrips, leaf hopper etc. and in the year 2018 the crop was majorly affected by the cotton leaf hoppers, Jassids. Thus, for strengthening network programmes monitoring the pest dynamics along with statistical forecasts and pest models is needful.