Milk and Cattle (in weight) Productivity Estimation

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Product Category

• Land use
• Land cover
• Natural Disaster
• Climate Change
• Coast Management 

• Marine
• Earth's Surface Motion

Financial Domains

• Investment management 
• Risk Analysis 
• Insurance management 
• Green finance

User requirements 

UN9: Understanding stock levels and monitoring supply chains.

Description

Milk and cattle (in weight) productivity have a very strong correlation with multiple factors including pasture quantity and climate data. EO can provide continuous spatial and temporal climatic data such as precipitation, temperature, wind, and evapotranspiration. Also, vegetation indices and biophysical variables derived from satellite data can be used as indicators for pasture quantity. Using machine learning algorithms, EO data can be correlated with historical milk and cattle productivity. Subsequently, these models can be used to predict and estimate productivity using EO data as predictors. 

Spatial Coverage Target

Individual farm level

Data Throughput

Rapid tasking 

Data availability

• High
• High

• Low
• Low

PRODUCT SPECIFICATIONS

Main processing steps

Climate data such as precipitation, temperature, wind speed and direction, pressure, and humidity can be derived from ERA5-land. Potential evapotranspiration can be calculated from data obtained from ERA5-land. Vegetation indices (such as NDVI, REPO, NDMI, NDCI, and PSRI), biophysical variables (such as LAI), and albedo can be derived from Sentinel-2 or Sentinel-3 based on the application. Green biomass data can be derived from LAI and phenology stages as described previously. By using feature selection algorithms, we can identify and select the most correlated features to milk and cattle productivity to be used as inputs to different machine learning models. After training and validation of different models, we can choose the models with the best performance to estimate and predict milk and cattle productivity based on input EO data.

Input data sources

Optical:  Sentinel-2&3

Radar: N.A 

Reanalysis products: ERA5-land

Supporting data:   Historical milk and cattle (in weight) productivity

Accessibility

Sentinel-2&3: freely and publicly available from ESA.

ERA5-land:  freely and publicly available from EMCWF.

Spatial resolution

Sentinel-2: 10 m

Sentinel-3: 300 m

ERA5-land: 0.1°

Frequency (Temporal resolution)

Sentinel-2: 6 days

Sentinel-3: Daily

ERA5-land: Daily

Latency

Daily

Geographical scale coverage

Globally

Delivery/ output format

Data type: Raster

File format: GeoTIFF

Accuracies

Thematic accuracy: N.A

Spatial accuracy: N.A

Constraints and limitations

• Cloud presence
• Low spatial resolution of ERA5-land
• Lack of historical milk and cattle (in weight) productivity data
• Creating universally applicable methods are challenging due to the variation of livestock and climate conditions.

User's level of knowledge and skills to extract information and perform further analysis on the EO products.

Skills: Essential

Knowledge: Essential

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