Bamu prof innovates technology, system to predict drought, crops identification, classification

By Mehboob Inamdar

Aurangabad, Feb 27:

Our country’ economy is based on agriculture. The sector produces food for crores of people, has faced many problems like non-availability drought condition forecast, lack of identification of crops using technology, and monitoring and timely forecasting of crop production.

A professor from the Computer Science and Information Technology Department of Dr Babasaheb Ambedkar Marathwada University (Bamu), Dr Karbhari Kale and his team have researched to help farmers enhance productivity, save time and money.

In his first research, he developed an Internet of Things (IoT) based agro-metrological weather station devices that have been designed for the system to predict and monitor agricultural droughts.

Dr Karbhari College said that the developed drought assessment system will be used to access the drought severity, crop health, soil moisture. “Additionally, the system will help predict the droughts, which will be used by the decision-makers for planning, monitoring and management the droughts,” he said.

In another innovation, he invented a method to evaluate crops' spectral signatures to improve nutritional diagnosis of the crop spatially. The invention titled ‘Enlargement of Crops Spectral Signature Using Multiband Frequencies.’

He said that the identification of agriculture crops is a tedious task using conventional methods. The research describes the enlargement of crops spectral signature using multiband frequencies for crop discrimination to be used for crop insurance policy schemes and identified spectral signatures of crops will be used as an end number extraction for hyperspectral imagery.

The collective methods significantly improve the accuracy of targeted yield acreage to increase crop productivity. The present invention provides a facile method for identifying and inexpensively discriminating crops types using geospatial data.

The third research is about crop classifications which very important for agricultural monitoring and timely forecasting of crop production.

He said that remote sensing techniques were successfully applied in classifications of arable crops and quantification of vegetation characteristics at different spatial and temporal scales. The crop discrimination and mapping using space data are carried out either by visual or digital interpretation techniques.

“Airborne, as well as space-borne remote sensing data, particularly Synthetic Aperture Radar (SAR) data, has shown promising results in crop monitoring and classification with reasonably high accuracy. This study shows that classification of remotely sensed imagery gives valuable information about crop discrimination. The proposed method is applied to the extracted single date approach. Based on the available reference crop map, data of several types of crops was collected. In our study, we have collected ground truth points using an application through a mobile device of various villages including Tajnapur, Sherodi, Yesgoan, Phulambri, Khuldabad, Nirgudi etc. with various crop fields’ latitude and longitude,” he added.