Monitoring crop health is one of the most important things that farmers can do to ensure that their crops produce good yields. A few decades ago, farmers had to go into the field to manually check on the health of their crops and ensure that there were no pests or diseases within the fields. This process was time-consuming and labor-intensive, and most often, the field operators could miss some vital spots, which may cause a loss in yield. If the farm was very large, it could take hours and days to monitor them manually.
However, with the advent of remote sensing technology, it became possible for farmers to perform crop health imagery using satellites, drones, and aircraft (you can read more here). These monitoring devices are equipped with sensors and cameras that take pictures of the crops at regular intervals. The data collected from these devices are analyzed and processed by advanced AI technologies, giving farmers insights to make informed decisions.
Source: bearingtips.com
Three main types of devices are used for crop health imaging: drones, satellites, and aircraft.
- Satellite imagery is best used when the farmers are not restricted by time and when there is no emergency. This is because the images are provided at long intervals, about 10 – 14 days. Nowadays, quality crop satellite images can be obtained almost free with other services that can help farmers with analytics.
- Aerial or manned aircraft are best used when a higher resolution of images is needed. Usually, farmers who don’t own aircraft can order it when necessary. One of the main benefits of using aircraft is providing thermal crop images for pivot monitoring.
- Drones can also be used to collect aerial images of crops to monitor their health and yield. These devices are equipped with sophisticated cameras that provide high-resolution images. Also, clouds are not an issue with using drones for crop health imagery. The drones are piloted by FAA-certified remote pilots to take photos of the farms.
Effect of Cover Crop Mixtures
Source: sustainableagriculture.net
Cover crops have a lot of benefits to farming and agriculture, such as providing nutrients to cash crops. Another important function of cover crops is to keep the soil from washing off during winter and rainy months. This is especially evident when your farm is on a slope. For those who keep livestock, cash crops can also be used for grazing.
Studies have shown an increase in soybeans yields following the use of cover crops on the field. Other research in the US has shown an increase in corn yield by up to 30 percent following cover crop mixtures. However, there are also studies that show that cover crops can affect yield negatively. Therefore, it is important to understand that the use of cover crops may affect yield positively, neutrally, or negatively.
Crop performance and health are high priorities for all farmers. That is why Nebraska SHI farmers search for features and tools to measure these metrics. Usually, only getting the end-of-year crop performance metric does not tell the whole story. That is why remote sensing technology can be used to monitor every change and ensure that the farmers get detailed information about the life cycle of their crops. Remote sensing can also be used to monitor soil health, weather, crop pests, and diseases. Farmers use this information to make important and informed decisions.
SHI on-farm research report
Source: fertilux.lu
The Nebraska SHI report compares farming yields with cover crop mixture use and no-cover crop. The cover crop mixture drilled in September 2018 was made up of 9 different species recommended by NRCS. The farmers then harvested the cover crop aboveground biomass on the 10th of May, 2019. This was done before chemical termination. The total biomass for the cover crops amounted to 1.25 tons per acre. Soybeans were then planted two days following the cover crop termination at 30-inch row spacing. Now, the growth and health of the soybeans were monitored using high-resolution imagery weekly.
The results of this research showed no net increase in moisture, yield, and quality after the cover crop or no-cover crop use. To check how the use of cover crop mixtures made a difference, we need to analyze the Normalized Difference Vegetation Index (NDVI) during the growing season. This index represents the ratio between red to near-infrared, which gives a quantitative estimation of vegetation biomass and growth. NDVI ranges from 0 to 1, with low values showing infertile soil and high values for dense and healthy vegetation.
Digital crop monitoring
Source: xyonix.com
Digital sensors can pick up light wavelengths visible and invisible to the naked eye. These wavelengths range from ultraviolet to radar. For remote sensing in agriculture, the most commonly used wavelengths are red, blue, green, and near-infrared.
There are three alternatives when collecting multispectral light images when the wavelengths are obtained using on camera. The first cheaper variant is a multispectral camera made up of different cameras with individual lenses. The next two use a single-lens camera, which is divided into various wavelengths. There are three methods of collecting multispectral light images, where different wavelengths are collected with one camera.
Digital crop monitoring has the potential to predict or catch disease outbreaks before they occur. This is because the monitoring devices are equipped with advanced hyperspectral cameras that can capture up to 128 different light frequencies. According to some studies, some pests and diseases absorb and reflect specific frequencies.
Light Detection and Ranging (LiDAR) is another popular way of creating a digital image. Light waves are sent to the surface at regular intervals, and the time taken for the pulse to return is calculated. This procedure is done many times within one second, creating an accurate 3D cloud map.
Ways of Vegetation Monitoring
Source: ta-survey.nl
Monitoring vegetation is a system for observing and evaluating various impacts on plants and trees. Such influences include illegal logging, forest fires, the presence of pests, and errors in the economic activities of people in the forest or farm site.
For instance, forest monitoring reveals the level of forest damage, studies the causes and consequences of the deterioration of forest plants, helps in solving forest management problems, manages and controls forest resources.
The main purpose of forest monitoring is to provide forest management authorities with reliable and timely information about the state of forest ecosystems and all changes in the forest fund.
Forest monitoring methods include:
- Aviation monitoring
- Ground monitoring
- Satellite monitoring.
Aviation monitoring is carried out using non-contact shooting from various aircraft (soaring balloons, helicopters, airplanes).
Source: eanet.asia
Ground monitoring observes the state of the forest using towers, video surveillance cameras, and ground transport.
Satellite monitoring is needed for a quick assessment of the fire, meteorological, sanitary, and the pathological situation in the forest. It is carried out with the help of space-based observation tools and makes it possible to get an idea of individual changes in large forest areas that cannot be detected by other monitoring methods.
The image in the infrared range from the satellite is transmitted to the analytical station, which is located on Earth. The obtained data is processed by blocks (block of forest fires, sanitary-forest pathological forest block, reforestation block). For example, the difference between the temperature of the earth’s surface and the temperature of the area covered by the fire allows experts to determine its location.
With this method of monitoring on the map, experts can see the contours of the fire. The information is stored in databases in order to further perform statistical analysis and make predictions.
The advantages of this method of monitoring are the automation of the procedure for obtaining information, remoteness, the ability to track any part of the earth’s surface, the availability of data, and the low cost of monitoring.
