Published November 6, 2023
| Version v1
Conference paper
Open
Leaf Area Index Time Series Imputation for Early Yield Prediction
Authors/Creators
- 1. VISTA Remote Sensing in Geosciences GmbH, Germany
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2.
Eindhoven University of Technology
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3.
Athena Research and Innovation Center In Information Communication & Knowledge Technologies
Description
Leaf Area Index (LAI) is a key parameter in crop growth models, and its accurate estimation is crucial for yield prediction. However, LAI data values are often missing or incomplete due to various reasons, such as sensor failures or cloud cover. In this paper, we propose a set of time series data imputation methods for LAI values derived from satellite images by radiative transfer model (RTM) inversion. The methods perform temporal interpolation either at the level of individual pixels or on spatial aggregates. Our experimental evaluation demonstrates that our approach can be applied to various crop types and has the potential to improve the accuracy and timeliness of yield prediction.
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