Multispectral Imagery to Monitor Crop Health
Multispectral Imagery to monitor crop health as the name states is a project where the crop health is monitored since the time of sowing to the point of cultivation. But it happens most of the time that crops die before their time of cultivation. This may be due to natural disasters or due to insuff
2025-06-28 16:34:14 - Adil Khan
Multispectral Imagery to Monitor Crop Health
Project Area of Specialization Shared EconomyProject SummaryMultispectral Imagery to monitor crop health as the name states is a project where the crop health is monitored since the time of sowing to the point of cultivation. But it happens most of the time that crops die before their time of cultivation. This may be due to natural disasters or due to insufficient nutrients, water and because to pests. Not considering the natural causes, the other inadequacies can be reduced. The multispectral imagery can help regarding this problem. It works by capturing images and rays of light reflected from the surface after contact. When it is used on plant, the rays of light reflected can be checked. This method employs different vegetation index techniques like Normalized Difference Vegetation Index (NDVI), Optimized Soil-Adjusted Vegetation Index (OSAVI), Green Normalized Difference Vegetation Index (GNDVI) etc. These indexes help to see the amount of light reflected which can be a measure of whether the plant is healthy or not. These indexes utilize the reflected Red Light, Green Light and Infrared Red Light to calculate an index value. Plants that are missing the essential nutrients or if the pests are attacking them will show a smaller index value, while the healthy plants will have a higher index value. The spectral camera works at a height either using an airplane or using the satellite multispectral data from Earth Explorer website thus it is used to pinpoint where in the crop field the crops are sick which can then be dealt with.
Project Objectives- Using Multispectral Imagery to monitor Crop health throught the crop season.
- The nitrogen status, pest attacks and diseases will be monitored as the crop develops and reaches maturity.
- Time series analysis will be done that will give details regarding the growth and development of the crop
- The multispectral sources utilized for this are the satellite imagery data, drone data, and a ground manual sensor data.
- The vegetation data will be showed on a Google map, alongwith, the time series analysis on a Web App
Remote sensing i.e. the satellite's different lights bands data (Red, Green, Near InfraRed) is utilized to provide an inexpensive evaluation of a large acre of land to check crop health which can include any of its qualities including but not limited to Chlorophyll content, Water content, Fertilizer content etc. These images then will be analyzed according to different vegetation indexes mostly used are NDVI and TCARI. This data will be compared to the data acquired through ground based sensors like moisture sensor, PH sensor and the data acquired through destruction testing which will tell about the content in leaves. Finally the calibrated data will be shown on a Web Application.
Alongwith the satellite data, the data from a drone is also utilized to monitor the crop health. A spectral camera is mounted on it which provides with the different vegetation index data. This is then used to show the colored map of varying crop health on the Web Application using Google Maps.
The Web Application is a python based app. Flask is used as the python base. It has different sections for the Satellite and drone portions and a database is made to store the vegetaion values of an area and do time series analysis on it.
Benefits of the ProjectThe world today has progressed a lot compared to the days before. With the increase in health facilities, technology and other luxurious facilities for humans their lives has become much easier. With the improvements in technology this trend has also reached the field of Irrigation. Agriculture is one of the main sources of food while also being an important part of the economy of a country. A lot of the countries depend on it for their international trade namely the agricultural countries whose main exports are their crops. But due to this advancement in technology the human population is also continuing to increase which has resulted in the shortage of food. To fight this scarcity and also to better their economy every country is trying to improve their agricultural produce’s quality and quantity. One way is to help keep crops healthy and to not let them die which is the basic outcome and the desired result of this project.
Technical Details of Final Deliverable- Analyzing the data collected from the different sources according to the vegetation index. This is done in Python language which can then be used in the Web App. Multiple Vegetation Indexes values are calculated and their separate time series analysis as well as collective analysis is done. The differences between the vegetation indexes are calculated.
- Calibration of the relflectance data according to the available manual data to error correct any index values due to atmosphere and bringing on the different index values on a standard scale.
- Showing the Vegetation data as colored in a Web Application on the Google Maps with colors showing the different values of vegetation. This is for both the Satellite Data and the Drone data.
- For the Satellite data the USGS Earth Explorer website has to be integrated with the Web Application which will then automatically download the different bands data calculate the index values to be displayed on the Google Map.
- For the drone data a .kmz extension file will be uploaded which will give us the locations coordiates and then its spectral indexes will be calculated to be displayed on the map.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 22945 | |||
| Frame | Equipment | 1 | 1900 | 1900 |
| High Volt DC Charging Tip | Equipment | 1 | 350 | 350 |
| 4.2V Recharchable cell | Equipment | 4 | 220 | 880 |
| Arduino Mega 2560 | Equipment | 1 | 1350 | 1350 |
| Phototransistor | Equipment | 2 | 110 | 220 |
| Resistor | Equipment | 15 | 20 | 300 |
| Normal LED | Equipment | 50 | 3 | 125 |
| Specific Wavelength LED | Equipment | 2 | 3700 | 7400 |
| Fabrication | Equipment | 1 | 3000 | 3000 |
| Connecting Wires | Equipment | 1 | 120 | 120 |
| Connectors | Equipment | 3 | 20 | 60 |
| Headers | Equipment | 5 | 40 | 200 |
| Hosting | Equipment | 1 | 6000 | 6000 |
| Printing | Miscellaneous | 200 | 4 | 800 |
| LCD Screen | Equipment | 1 | 240 | 240 |