1. Overview

Phenological observation refers to the observation of the occurrence time of growth and development phenomena in animals and plants. Observation of crop growth period is one of the main contents of agricultural meteorological phenology observation. This observation is the basic data for agricultural meteorological services and scientific research. The primary task of phenological observation is to confirm the appearance of phenological phases, and only then record phenological days and periods.

Phenological observations are generally selectedobservationThe object is:

1:Common and widely distributed animals and plants;

2:Unique animals and plants within this climate zone;

3:Animals and plants with strong indications, especially those that exhibit obvious phenological phenomena every few days;

4:Observation objects that are representative of the ecological environment such as terrain, vegetation, and conditions;

2. System composition

The NetCam phenological observation system consists of a data acquisition system, phenological cameras, as well as external remote transmission, brackets, and power supply equipment. In addition, the phenological camera can be separately mounted on each system to achieve multiple phenological observation schemes:

•Online automatic observation of plant growth rhythm

•Crop pest monitoring

•Research on Vegetation IndexNDVI,EVI

•Equipment security

•Natural disaster freezing monitoring

•wait

Support real-time display and statistics of agricultural meteorological observation data such as forest gradient, farmland microclimate, soil moisture, and real-life images; It can automatically calculate parameters such as crop development period, coverage, and density, support equipment status monitoring function, and generate analysis and processing products that meet user needs, making it easy for staff to grasp the dynamics of each site in real time.

Automatic observation and recognition system for crop development and growth:

The system is an automatic observation system for crop ecological parameters, including crop development period, crop coverage, and density. It can be applied to crops such as corn, wheat, rice, and cotton.

Example diagram of changes in corn growth

Monitoring of vegetation height changes:

Coverage monitoring:

Biomass monitoring:

Developmental monitoring:

Disaster monitoring ：

Xilinhot Natural Forage Growth and Development Dynamic Monitoring System:

3. Application Cases

Discipline Group of the Ministry of Agriculture21 sets of automatic weather stations

Image Monitoring by Urumqi Desert Meteorological Institute of China Meteorological Administration（3 sets)

Chengdu Plateau Institute of China Meteorological Administration（4 sets)

Shanghai Academy of Environmental Sciences Agricultural Gas Station, Forest Flux Station（2 sets)

Monitoring of Glacier Morphology in Tanggula Cryosphere

Monitoring of Forest Land by Jiangxi Academy of Forestry

4. Main technical parameters of phenological camera:

1.Image size:2592x1944，500Ten thousand pixels

2.Automatic day night infrared filter mechanism（IRMode)

3.DC automatic aperture

4.Exposure range:1/48000Seconds to0.7second

5.Equipped with video outputBNCConnector, allowing viewing of standard closed-circuit television surveillance,MUX, DVRvideo

6.built-inWebThe server

7.Supported protocols:TCP/IP、HTTP、FTP、ARP\NTPetc.

8.Working temperature:-40-60℃

*9.PCEnd image processing software, software algorithms can be embedded in secondary development platforms, and can be accessed throughRGBandIRImage calculationNDVI,GCC,EVI,RVIEqual Index

5. References:

1.The impact of annual plant functional groups on biomass and soil respiration in grazed grasslands---Wang Yingshun

2.Xilinhot GrasslandAnalysis of CO2 flux characteristics and influencing factors---Wang Wenya, Guo Jianxia, Wang Yingshun

3.Yushu near Xilingol League30-year phenological changes and their response to temperature changes---Wang Yingshun

4.Chinese phenological observation methods---Wanminwei Liu Xiuzhen

5. Analysis of vegetation phenological spatiotemporal characteristics on the Qinghai Tibet Plateau based on MODIS NDVI and multiple methods - Zhou Yuke, Liu Jianwen

6. Rapid extraction method of grassland vegetation coverage based on digital photos - Hu Jianbo, Zhang Lu, Huang Wei