计算机科学
模块化设计
工作流程
叶面积指数
遥感
软件
可扩展性
数据挖掘
精准农业
植被(病理学)
索引(排版)
桥接(联网)
遥感应用
数据采集
机器学习
经验模型
随机森林
回归
软件体系结构
植被指数
数据处理
建筑
环境科学
出处
期刊:SoftwareX
[Elsevier BV]
日期:2026-01-06
卷期号:33: 102504-102504
被引量:2
标识
DOI:10.1016/j.softx.2025.102504
摘要
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.
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