MINUTES OF MEETING

Usage of MODIS imagery in previous works

Chippy has downloaded and used modis images and has come to a conclusion that much can’t be done with these images because the spatial resolution of the images is 250 meters, hence, we can map vegetation only on district level or state level.

Requirement of previous years’ data for reference for the current study

Chippy does not have any field level data from 2018. National crop forecasting center gathers all the field level data (latitude longitude, crop cutting etc.), but they are hard to communicate with and they rarely reply to emails.

The premilinary data required is the Latitude, Longitude data for a few fields in Aland taluk in kalaburagi district for kharif season from june to December of 2018. Gulbarga kharif season crop does not exist much since the analysis done on 15 years of MODIS imagery revealed that fields during kharif season are severely drought affected.

Current Method of Accessing Satellite Imagery Data

Currently NRSC provides satellite imagery at around INR 4k-7k per tile (70kmx70km) with a resolution of around 5.4 meter for latest imagery. The pricing is less for older image requests. However, to access imagery it is required to request it from them every time through emails with a complete request form. Sometimes they don’t even consider providing satellite imagery and it is a very big hassle to get the imagery from them periodically.

Rough roadmap of the work

Before june 2019, Krishi vigyan Kendra will help Chippy get fields for the proposed study. All the study will be done on these fields. Chippy is planning to take taluk level fields, at least a minimum of 6 farms. Images will be taken from Farmonaut periodically for each stage of crop growth, simultaneously Chippy will work on her data as well. The suggested study will have at least two to three crops for separability.

Devices to be used for ground level analysis

Leaf area index meter, Chlorophyll meter, Temperature meter etc.

Macro Level Objective and Expectations

The objective will be to correlate the ground level data with satellite data and create a yield prediction model.

If any kind of change that happens in a farm field in a particular time, the objective will be to identify how it will affect the farm. For example, if too much rainfall happens then, the objective will be to predict what could possibly happen and how much it will affect the yield.

Farmonaut currently provides two satellite imagery based products, namely:

Satellite Based Crop Health Monitoring System For Farmers (Android):

Farmonaut provides satellite based crop health monitoring system, through which farmers can select their field and identify the regions of the field at which the crop growth is not normal. Upon identifying that region of their fields, they can simply pay a visit to that part of the field and identify if the problem has already started. If it has not, the farmer can take preventive remedies by applying more fertilizers, plant growth regulators etc. If the problem has already started, they can simply explain their problem to Farmonaut’s crop issue identification system and get real-time govt. approved remedies.