Application of Multi-Source Remote Sensing Data and Lidar Data Fusion Technology in Agricultural Monitoring

Abstract

The fusion technology of multiple and LiDAR data has important value in agricultural monitoring process, which can contribute to the accuracy of crop identification, real-time monitoring of crop growth status, and evaluation of advanced land resource characteristics. Due to the large-scale coverage and complex spectral features of remote sensing images, they have the potential to identify vegetation and soil characteristics; And LiDAR images have precise spatial structural characteristics, such as tree crown height, ground morphology, etc., which can complement the latter in structural and informational spaces, filling the limitations of single source data acquisition in representation. Of course, having great technological potential does not necessarily mean that it can be fully realized. In fact, it also faces some challenges, such as mismatched temporal spatial resolution, cumbersome data acquisition and processing processes, high development costs for hardware facilities and algorithm software, etc., all of which hinder the effectiveness and depth of the development of this technology. This article mainly starts from the agricultural and forestry scenarios, explores suitable integration development paths and strategies based on their existing problems, in order to enhance the practical value and intelligence level of agricultural remote sensing data integration, promote the intelligent and refined development of agriculture, and provide technical support for its development.