MS400 (4-Bands) Multispectral Camera

Product features

• 4 Multispectral & 1 RGB
• 1.3M & 8M pixels
• 12bit Global & 8bit Rolling Shutter
• Gigabit Ethernet/TTL serial port
• Standard downlink light sensor (DLS)
• ≤175g aluminum alloy lightweight body
• ≤7W@12V power supply, 64G TF card
• Convenient parameter setting in WEB interface under WIFI connection
• Multiple triggering modes: external, timed, and overlap rate
• Compatible with multiple small UAV platforms

Technical parameter

• Configuration: 4 multi-spectral channels + 1 RGB channel
• Target surface size Multi-spectrum & RGB: 1/4″
• Effective pixels Multi-spectral: 1.3Mpx; RGB: 8.0Mpx
• Shutter type Multi-spectral: global; RGB: roll-off
• Quantization Bit Multi-spectral: 12bit; RGB: 8bit
• Field of view Multi-spectral: 36.7° x 31.3°; RGB: 37.5° x 28.6°
• Ground resolution Multi-spectral: 6.23cm@h120m; RGB: 2.49cm@h120m
• Coverage width Multi-spectral: 80m×67m@h120m; RGB: 82m×61m@h120m
• Spectral channel ^[1] 555nm@27nm,660nm@22nm, 720nm@10nm,840nm@30nm, RGB
• Optical Window: Optical Glass Window
• Dimensions: ≤55mm×65mm×50mm
• Weight: ≤175g
• Mounting interface: 7×M3
• Power supply: 12V (please contact Yuchen marketing staff for details if other voltage is used)
• Power consumption: ≤7W@12V
• Image format Multi-spectrum: 16bit raw TIFF & 8bit reflectivity JPEG; RGB: 8bit JPEG (including GPS, ambient light information)
• Video Format:
• Storage media Standard and maximum: support 64G capacity (transfer speed U3 and above rating) micro SD card
• Processing Software: Yusense Map/Yusense Map Plus/Yusense Net
• Parameter settings: WIFI (WEB interface access)/Ethernet/UART
• Shooting: Trigger External Trigger, Timer Trigger, Overlap Rate Trigger
• Shooting frequency: 1Hz (related to the actual read/write speed of storage media)
• Working environment temperature: -10℃~+50℃(Relative wind speed≥1m/s)
• Storage Ambient Temperature: -30℃~+70℃
• Ambient Humidity: RH(%)≤85%(non-condensing)
• Product Certification: CE, FCC, RoHS

Benefits for agriculture:

• Crop health monitoring: Identify nutrient deficiencies, diseases, and stress early on.
• Yield estimation: Predict crop yields more accurately.
• Variable rate application: Optimize fertilizer and water usage based on specific needs of different areas within a field.
• Precision scouting: Target problem areas efficiently for further investigation.

Additional considerations:

• The MS400 is compatible with various small UAV platforms.
• It requires Yusense Map or Yusense Map Plus software for data processing and analysis.
• While the product description mentions customization options for spectral bands, specific details and pricing might require contacting Yusense directly.

Overall, the Yusense MS400 offers a powerful and affordable solution for farmers and agricultural professionals looking to leverage multispectral imaging for improved crop management and decision-making.

Applications

Vegetation growth assessment

Using NDVI, LAI and other vegetation factors, we quantitatively describe the consistency of the vegetation canopy state at different spatial scales, assist the characteristic spectra of vegetation in different health states, quantitatively assess the vegetation’s longevity, and provide data support for irrigation, fertilizer application, plant protection, and yield assessment.

 

 

 

Seedling rate assessment

Based on the spectral differences between crops, weeds, soil and other environments, it can complete the precise identification of crop seedlings and plant segmentation, quantitatively assess the area of crop plants within a unit area, and measure the regional seedling emergence rate, providing data support for scientific research and breeding, and agricultural seedling replenishment.

Pest and Disease Assessment

Based on the characteristic spectra of pests and diseases and crop growth, we can quantitatively determine the severity of pests and diseases and the spatial distribution of crop health status, providing data support for disaster assessment, crop yield estimation, and agriculture, forestry and plant protection.

 

 

 

Crop Failure Assessment

Based on the differences in canopy spectra and leaf texture of vegetation, a crop collapse assessment model is constructed, which, combined with statistical data from ground sampling points, quantitatively describes the degree of crop collapse and the spatial distribution of different degrees of collapse, and provides data support for disaster assessment, crop yield estimation, and so on.