XST-SCI-in-One Scientific Research Observation in One

XST-SCI-in-One Scientific Research Observation in One

Product Overview

For a long time, the most commonly used automatic monitoring instruments for field ecological experiments have mostly focused on the monitoring of state quantities and variables of environmental elements of vegetation growth, such as meteorology, soil, hydrology and many other ecological environment elements. However, traditional observation techniques have neglected the direct, long-term continuous, non-contact and non-destructive monitoring of vegetation ontogenetic growth parameters: such as plant phenology and vegetation index, vegetation structural parameters such as vegetation cover and leaf area index, and continuous automatic monitoring of sunlight-induced chlorophyll fluorescence (SIF). From the point of view of industrial application, these parameters are more intuitive and accurate in describing the growth status and changes of vegetation.

Currently, the common solution to the observation of vegetation ontology is to utilize portable instruments and manually collect data in the field. This approach not only consumes human resources, is not suitable for continuous monitoring, and limits the in-depth understanding of ecosystem dynamic processes, but also causes data errors due to operator variability and human interference with the environment.

The application of such technologies as online automatic monitoring, sensor network monitoring, high-precision in situ monitoring and remote data transmission in the field of ecosystem monitoring has solved the above problems to a great extent. At present, such technologies have been widely applied to the observation of ecosystem environmental elements and material and energy fluxes, and their application to the observation of vegetation ontogeny is bound to develop as well, representing a new trend in ecosystem observation.

The environment determines the survival and reproduction of vegetation populations. If environmental parameters are considered as "causes", then vegetation growth parameters are "effects"; at the same time, vegetation growth parameters affect environmental parameters in the same way as "causes", for example, by changing the surface roughness, regulating air and soil temperature and humidity, and affecting water and carbon fluxes. At the same time, vegetation growth coefficients affect environmental coefficients in the form of "causes", such as changing surface roughness, regulating air and soil temperature and humidity, and influencing water and carbon fluxes. The application of in situ automatic monitoring and remote transmission technology in plant ontology monitoring can realize the synergistic layout of the two observation systems of environment and vegetation, which will be more helpful for long-term monitoring of the natural evolution of terrestrial ecosystems and their response to environmental climate change, and realize the synchronization of "cause and effect" control, which will help scientific researchers to monitor and record the ecological processes in an all-round way. The system will help researchers to monitor and record the ecological process in a comprehensive way.

Beijing StarView Technology Co., Ltd. independent research and development of scientific research observation of a rod is to allow users to one-stop match, that is, an observation of the main rod, to complete a variety of target parameter measurements, in order to solve the natural environment of the growth of vegetation for long-term comprehensive monitoring problems and design: both the closely related to the plant environmental factors to monitor, but also at the same time on the vegetation itself the important growth parameters to monitor, and the two major parts of a synchronized observation of a host to complete the perfect solution to the problem of matching the parameters of time and space. The two main parts of the system are synchronized with one host, which perfectly solves the problem of time-space matching of each parameter.

At the same time, One Pole can make full use of the arithmetic power of the intelligent data collector to carry out preliminary data pre-processing while completing the data collection to achieve the effect of "observation is gained", and reduce the workload of the user's later data calculation and parameter processing.

Features

One system.how (what extent)arrangement of ideasdeploymentsobservation (scientific etc)

Top-down integration of spectral climate cameras, vegetation canopy structure parameter cameras, multi-element weather sensors, and multi-parameter soil sensors, unified by a data collector to control and collect data to ensure data integrity.

One deployment.Synchronized access to a total of four areas of plant indicators, meteorological environment, soil and hydrology24kindupperResearch Parameters

Obtain time-series plant images: visualize plant growth at various stages from images, customizable with multiple viewing angles

Automatically calculate 5 types of climatic vegetation indices: NDVI (Normalized Vegetation Index), GCC (GCC), RCC (RCC), BCC (BCC), GVI (GVI) and other colorimetric vegetation indices, which can reflect the growth stage and health status of the plants from the data.

Automatically calculates two vegetation structure parameters: LAI leaf area index and FVC cover (or degree of depression), reflecting plant growth and population distribution from the data.

7 meteorological elements: air temperature, air humidity, atmospheric pressure, wind speed, wind direction, rainfall, total solar radiation

3 soil parameters: temperature, humidity, conductivity, any number of probes can be selected to observe the three parameters at multiple depths.

Seven additional parameters can be added as options: directly plant growth-related parameters such as photosynthetically active radiation, infrared canopy temperature, leaf temperature and foliar humidity; hydrological parameters such as water level, water velocity and flow rate.

anIntelligent Data CollectorTaking edge computing into accountwith wireless transmission

Built-in programmable modules for real-time data field calibration and calculation of various vegetation indices and structural parameters.

One set of data, localcap (a poem)Dual Backup in the Cloud

Observations are saved in real time in local and cloud databases and support intermittent transmission.

Technical Parameters

spectrographic weather camera

Vegetation canopy structure parameter camera

All-in-one weather sensors

Soil temperature, humidity and salt sensors