Research

Engineering Sciences

Title :

Crop Identification and Health Monitoring using UAV data and Satellite Imagery

Area of research :

Engineering Sciences

Principal Investigator :

Dr. Mesapam Shashi, National Institute Of Technology, Warangal, Telangana

Timeline Start Year :

2023

Timeline End Year :

2026

Contact info :

Equipments :

Details

Executive Summary :

Agriculture is one of the major resources for food production and several types of crops are being cultivated in different regions as per their suitability each year. The yield of any crop depends upon the health of the crops which is affected by many parameters, including climatic parameters, plant to water stress conditions, soil parameters, insects and plant diseases and that may vary for various crops. Out of these parameters, plant to water stress is the major contribution to the yield, and if detected early, can improve crop yield drastically. Monitoring crop growth and its health conditions can be evaluated by estimating plant density, crop height, canopy area, water stress, and nitrogen content of the crops. Remote sensing is widely used to study these parameters effectively because of its high spatial and spectral resolution and can be used in discriminating plants and monitoring crop health metrics, such as crop phenological growth, diseases, chlorophyll, biomass and so on. Remote sensing data from satellites has the advantage of monitoring the health parameters of different crops effectively, but it is insufficient for studying the health parameters at the plant level. Unmanned aerial vehicles, on the other hand, has been widely used in recent years to capture high resolution images that, when compared to satellite remote sensing data, can be used to classify different crops, extract biophysical parameters such as leaf area index, chlorophyll content, and so on at the plant level and for each crop. Sentinel - 2 data was released in 2015, with spatial resolutions of 10m, 20m and 60m, 13 spectral bands, and a temporal resolution of 5 days. Sentinel -2 data was collected for evaluating the Vegetation Indices (VI’s) such as Normalised Difference Vegetation Indices (NDVI), Soil Adjusted Vegetation Index (SAVI), Green Vegetation Index (GVI), to estimate the density of vegetation, chlorophyll, nitrogen, soil condition, and so on. Because of its high spatial resolution, UAV data can be classified more precisely than satellite data. This data can also be used to estimate other parameters for a specific crop, such as canopy cover, canopy height, chlorophyll content, and biomass. In this research, it is proposed to use both UAV images and satellite data to monitor crop health, study the water stress conditions of each crop, estimate crop yield, and suggest methods to increase crop yield during the growth stage, thereby benefitting farmers.

Co-PI:

Dr. Keesara Venkata Reddy, National Institute Of Technology (NIT) Warangal, Telangana-506004

Total Budget (INR):

38,39,264

Organizations involved