VIsToLAI: A modular open-source platform for estimating the leaf area index from remote sensing-derived vegetation indices
Year: 2026
Type: software-paper
Abstract: VIsToLAI, a unique open-source software framework developed in Python, stands out for its ability to estimate the leaf area index (LAI) using time series data derived from a variety of remote sensing vegetation indices (VIs). Its support for multiple VIs and integration of both empirical regression and machine learning modules provides a flexible and scalable data assimilation workflow. The software's versatility is demonstrated through case studies on four staple crops, showcasing its extendibility for the geospatial projection of LAI simulations. VIsToLAI’s modular architecture allows for the easy incorporation of new indices and algorithms and for seamless integration into existing remote sensing workflows.
Source: SoftwareX
Authors: Jonghan Ko, Chi Tim Ng
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,200
Award: G4299427030
OpenAlex ID: W7118673108