VLMP platform for tracking health
and forecasting sugarcane yields.
Thailand's agricultural sector needs to improve cultivation efficiency to meet the world's growing food demand.
Therefore, technology plays a major role in helping work and improving the quality of life of Thai farmers. Varuna, the leader in smart agricultural technology, offers a VLMP platform that used to monitor health and predict sugarcane yields for the Smart Farmer group to apply technology to the farmland to reduce the limitations in various aspects
Sugarcane is a cash crop that has a lot of market demand. Therefore, Thai farmers have searched for ways to improve the cultivation system and technology to improve productivity. The technology that is currently being watched the most is the use of satellites, unmanned aerial vehicles or drones, platform and applications continuing to the use of AI technology to analyze and predict problems that arise during cultivation and harvesting. The issue is also consistent with the policy of government and private support in creating AgTech startup and DeepTech startup in agriculture, which is a new dimension that will help creating value and confidence for the better future of Thai agricultural industry.
Varuna Land Monitoring Platform (VLMP) (for Sugarcane)
Varuna Land Monitoring Platform (VLMP) is an end-to-end automated processing of sugarcane growth monitoring and yield prediction platform by using remote sensing technology from satellites together with AI and machine learning technologies to support crop cultivation to be most effective from the beginning of the season, analyze soil moisture , plan start cultivation date, monitor and analyze growth and health of the crops, forecast harvesting date and area, and including predict the seasonal yield of crops such as sugarcane, cassava, rice and many other crops in the future.
VLMP offers a wide range of vegetation index analysis systems obtained by analyzing satellite imagery to help more efficient plant growth analysis
Normalized Difference Vegetation Index (NDVI)
that can be used to monitor the health of plants at all stages of growth, especially for use in time series such as the NDVI Time Series. It can also be applied in the study of the phenology of each plant, for example, the phenotype from the NDVI index of rice during its maturity period, etc. In addition, in environmental side, the NDVI index can also be used to accurately monitor changes in green areas.
Normalized Difference Water Index (NDWI)
is an index that can indicate the amount of water absorbed by plants. This can be used to analyze crop water stress. It can also indicate differences in humidity, which is one of the factors for assessing the risk of drought for environmental applications, the NDWI Index can indicate areas of water or vegetation.
Soil-Adjusted Vegetation Index (SAVI)
is an index that can indicate soil moisture by reflecting surface waves,which was used in the analysis together with the other vegetation indexto indicate the activities of the cutting or harvesting field crops. Also,the productivity can be predicted every 10 days.
Soil Moisture Active Passive (SMAP)
satellite can indicate the soil surface moisture content and is used to monitorthe water supply of agricultural crops which directly affect their growth.It is also used to monitor natural disaster situations such as flooding or drought, etc.
In addition, users can also monitor crop production capacity at the individual field level to the total area of crop cultivation. VMLP also helps categorize the crop quality level, specify the number of cultivated areas, and predicting yields to allow users to see an overview of crop cultivation, including monitoring, editing, and improving at the individual field level and can find deformities within those fields.
The VLMP is part of the Varuna Land Monitoring Service (VLMS), a data processing service based on high resolution satellite imagery of 10x10 and 20x20 meters for the agricultural industry, survey assessments of natural resources and various forms of data analysis to support business decision-making.
- Continuous data for 30 days and can be traced back up to 5 years.
- Cloud-free data processing
- High resolution satellite imagery of 10x10 meters and 20x20 meters
- Monthly data for all regions in the country.
- Display data in pixel ready to be used with Geographic Information System (GIS) conveniently.
Varuna's VLMP platform monitors health and predicts sugarcane yields. It helps improve the cultivation efficiency of the Thai agricultural sector and it is a technology that meets the world's growing food demand. Therefore, this platform will indeed promote food security in the future.