Agricultural plot growth analysis based on hyperspectral and drone technologies

With the continuous advancement of agricultural modernization, technological development plays an increasingly important role in improving crop yield and quality, as well as reducing resource waste and environmental pollution. Against this backdrop, crop growth monitoring methods based on hyperspectral imaging are becoming a hot topic in agricultural monitoring.

concept of crop growth

Crop growth vigor refers to the physiological state, growth rate, and biomass accumulation of crops during their growth and development. The quality of crop growth directly reflects the health status and yield potential of crops, and is an important monitoring indicator in agricultural production. Assessment of crop growth vigor typically includes multiple aspects such as plant height, leaf area, chlorophyll content, and biomass.

Monitoring crop growth is of great significance for agricultural production. By monitoring crop growth, problems during the growth process can be identified in a timely manner, allowing for appropriate management measures to promote healthy crop growth and improve yield and quality. Growth monitoring can also support agricultural production decision-making, such as adjusting planting density, fertilizer application, and irrigation levels, to achieve scientific planting and precision management.

Hyperspectral technology for agricultural monitoring

Hyperspectral imaging is a technology that maps the spectral information reflected or transmitted by an object into an image, and it has wide applications in various fields. In agriculture, hyperspectral imaging can acquire the reflectance spectral information of plants in different wavelength bands, providing information such as vegetation indices, chlorophyll content, and growth status.

Compared with traditional agricultural monitoring methods, hyperspectral imaging technology has the following advantages: First, it can acquire more vegetation information, including vegetation indices, plant height, and leaf area index, making monitoring more comprehensive and accurate. Second, it is a rapid monitoring method that can accurately acquire spectral information from thousands of pixels, improving the efficiency of crop growth monitoring. Third, it allows for non-contact monitoring of crop growth, avoiding damage to crops.

Drone technology + hyperspectral remote sensing for agricultural monitoring

With the development of China's drone industry, its applications in plant protection, forestry monitoring, and crop pollination are becoming increasingly widespread. Agricultural plant protection drones are dozens of times more efficient than conventional spraying, and drone-assisted pollination for hybrid rice seed production significantly reduces labor intensity and improves seed production efficiency. In recent years, the rapid development of drone technology combined with spectral technology has made it possible to macroscopically, dynamically, and rapidly monitor orchard growth dynamics. Agricultural drones fly at low altitudes, typically 50-100m, requiring no atmospheric correction, and their flight control systems are relatively simple, with the measurement and control space matching the orchard size. Exploring the application of NDVI obtained from multispectral cameras equipped on drones in growth monitoring and missing plant location is of great significance for supporting precise and digital orchard cultivation and improving fruit tree production efficiency.

Xi'an Institute of Optics and Precision Mechanics CAS Aerospace Science and Technology Group Co.,LTD - Agricultural Plot Growth Analysis

Visible light and hyperspectral data were collected using drones. After orthorectification, index calculation, and unsupervised clustering, the crop growth status of large-scale plots was visually displayed. The image shown is a drone image collected on March 19, 2024, during the wheat tillering stage. The right image is an NDVI vegetation index cluster map with buildings and roads removed.

The image above is a plot-level vegetation growth analysis report, with the legend showing the clustering results based on the NDVI vegetation index. The pie chart below the image displays the area percentage of crops with different growth rates. Areas with relatively good and poor growth are circled in red and yellow on the map for growers' reference.

As a novel information monitoring technology with high spatial and temporal resolution, UAV hyperspectral imaging offers significant advantages in spatial scale and accuracy compared to traditional monitoring methods, making it particularly suitable for the rapid acquisition of digital information in mesoscale farmland. In the foreseeable future, with the development and improvement of UAV flight platforms, airborne multi-source information acquisition technologies, data mining and modeling techniques, and decision support technology platforms, UAV hyperspectral technology is expected to find wider and deeper applications in agriculture and related fields.