Optimal arrangement-based dump vegetation intelligent monitoring method

By using an optimal set of monitoring points and multi-angle image acquisition technology, combined with a dual-flow feature fusion network and growth trend prediction, the problems of insufficient automation and lack of predictive basis in existing vegetation monitoring methods have been solved, achieving high-precision and fully automated vegetation coverage monitoring.

CN122313259APending Publication Date: 2026-06-30CCTEG SHENYANG ENG CO
View PDF 0 Cites 0 Cited by

Patent Information

Application Number
CN202610322140.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-17
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

Existing vegetation cover monitoring methods rely on quadrats, which are labor-intensive, inefficient, and have limited applicability. Remote sensing monitoring lacks precision, while existing photogrammetric monitoring methods are inflexible, costly, and lack scientific prediction capabilities, resulting in insufficient data representativeness, accuracy, and automation.

Method used

An intelligent vegetation monitoring method based on optimal layout of spoil heaps is adopted. The monitoring point set is constructed by spatial variogram and simulated annealing algorithm. Combined with adjustable support and industrial-grade digital camera, multi-angle image acquisition and video stream analysis are carried out. Vegetation area segmentation is performed by using dual-stream feature fusion network. Coverage, plant height and tiller number are automatically calculated by combining environmental factors such as light and wind direction. The logistic growth model is also incorporated to predict growth trend.

Benefits of technology

It has achieved fully automated multi-angle monitoring without quadrats, improved the representativeness of monitoring coverage and terrain adaptability, reduced monitoring errors, significantly improved the monitoring accuracy and automation in complex terrain, and has the ability to predict vegetation growth scientifically.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN122313259A_ABST
    Figure CN122313259A_ABST
Patent Text Reader

Abstract

This invention discloses an intelligent monitoring method for vegetation in spoil heaps based on optimal layout, belonging to the field of open-pit mine ecological restoration monitoring technology. This invention employs spatial variogram and simulated annealing algorithms to achieve optimal monitoring point layout; it automatically acquires multi-angle images and videos using adjustable supports, and performs keyframe extraction, multi-angle registration, and adaptive denoising preprocessing; the images are input into a lightweight dual-stream feature fusion network, and vegetation areas are accurately segmented through RGB and NDVI dual-stream attention fusion and combined loss function optimization; based on the segmentation results and environmental factors, vegetation coverage, plant height, and tiller number are automatically calculated; the time series is decomposed using STL, and the logistic growth model is integrated into the LSTM network as a physical constraint to output a growth trend prediction that conforms to biological laws. This invention achieves fully automated monitoring from layout to prediction, significantly improving the accuracy and efficiency of monitoring reclaimed grassland in spoil heaps.
Need to check novelty before this filing date? Find Prior Art