Phenology Online Automatic Observation System

The verification basis for vegetation phenology remote sensing identification method based on carbon exchange data of flux tower net ecosystem. In recent years, new technologies have brought vitality to traditional phenological observations, and new observation technologies using automatic photography and data network transmission have emerged. The use of digital repetitive photography to observe phenology not only saves human resources, but also facilitates the adoption of unified observation standards and data management models for phenological phenomena. Combining phenological observations with observation data from automatic meteorological recorders can supplement the problems of low accuracy and long distance of meteorological station data in traditional phenological research, and is conducive to more accurately grasping various aspects of the impact of climate change on biological phenology. In terms of observation methods, in recent years, people often combine the new achievements of geographic information science in remote sensing observations with ground observations in phenological observations. Remote sensing data is a beneficial supplement to ground observations, and the combination of the two can achieve spatial scale transformation of geographic phenomena.

1、 System Introduction

System composition: The online automatic observation system for plant growth and phenology is composed of high pixel cameras, large capacity data collectors, and multispectral imagers as the core components of the system. Adopting to achieveA 5-megapixel network camera is used to obtain high-quality image data, and the system is equipped with a Netcam camera that supports white balance settings. The multispectral imager uses a MicaSense RedEdge-M multispectral camera, which can reach 3.2 million pixels and weighs only 90 grams. The entire system uses a high-strength field professional bracket for camera installation to ensure system stability.

MicaSense RedEdge-M Multispectral imaging system

Overview Description:MicaSense RedEdge-M has five independent imagers, each equipped with a specially designed filter, which allows each imager to receive spectra within a precise wavelength range.

The output value of each pixel in the image output by the MicaSense RedEdge-M imager represents the reflectivity of a specific wavelength of light. Concatenate the images to form a precise map with multiple layers of spectral data. By mathematically calculating these multispectral data, various plant indices can be obtained to measure various plant properties. Some indices are used to measure the chlorophyll content in plant leaves, which can accurately reflect the nitrogen content of plants and can be used to determine how to fertilize. Some indices are used to estimate the leaf area per unit area of land, which helps determine the growth and health status of crops in farmland. By combining the reflectance of red and near-infrared light, a commonly used index, Normalized Difference Vegetation Index (NDVI), can be obtained.

Product performance:

lCompact design, small size, can be integrated with various types of drones

lFast capture rate, able to accept faster flight speeds and lower flight altitudes

lGlobal shutter design ensures that the results collected on each platform are not distorted

lCan generate arranged vegetation indices andRGB output

lSturdy design with no loose parts throughout the entire body

2、 System software

The system software can automatically calculate and display multiple vegetation indices online, and monitor the operating status of the equipment through the software.

Data example:

The following picture shows the installation at Beijing Botanical GardenData from June to July, same location but different coverage areas of two cameras