Continuous Forest Stock Monitoring via Dynamic Sample Plot Updates
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Solution Overview
Problem
Current methods for monitoring forest stock are inefficient due to long survey periods, low precision, high costs, and limited comparability, making it difficult to achieve real-time and continuous monitoring of forest resources.
Innovation Solution
A continuous monitoring method and system that involves sampling design, intelligent sample plot layout, automatic data collection, dynamic updating of forest resource maps, precision testing, and correction, allowing for real-time output and continuous comparability of forest stock data using remote sensing and on-site surveys.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If second class survey is carried out every 10 years, then comprehensive forest stock data can be obtained, but the monitoring period is long and productivity is low
Solution Approach 1:
The patent divides the forest monitoring area into multiple fixed sample plots that are segmented across different regions. By segmenting the monitoring task into discrete plot-level measurements, the system enables continuous data collection at each plot while aggregating results to represent the entire forest area, thus increasing monitoring frequency without sacrificing comprehensive coverage
Solution Approach 2:
The patent implements periodic re-measurement at fixed sample plots at intervals of 1 year or more but less than 10 years. This periodic action allows for continuous monitoring capability while reducing the overall time investment compared to decade-long surveys, achieving a balance between monitoring frequency and resource allocation
2Quantity of substance
If growth model update is used, then monitoring cost is reduced, but measurement precision decreases due to static plot data
Solution Approach 1:
The patent employs feedback mechanisms where measurement results from fixed sample plots are used to dynamically update growth models. The measured data from recent surveys feeds back into the model to adjust parameters and improve accuracy, ensuring the model reflects current forest conditions rather than relying on static historical data
Solution Approach 2:
The patent changes the temporal parameter of data collection by implementing frequent re-measurement at fixed plots. This parameter change transforms the static nature of traditional survey data into dynamic, time-series data that captures forest growth patterns, thereby improving model precision without proportionally increasing costs
3Measurement precision
If laser radar tree measurement is used, then measurement precision is improved, but cost increases and device complexity increases
Solution Approach 1:
The patent extracts the essential measurement function from expensive laser radar systems and implements it using simpler, lower-cost measurement devices at fixed sample plots. By taking out only the critical measurement capability needed for forest stock assessment and implementing it through affordable means, the system achieves acceptable precision without the high costs associated with laser radar
Solution Approach 2:
The patent employs inexpensive measurement devices at multiple fixed sample plots rather than expensive reusable laser radar systems. The use of multiple low-cost measurement points distributed across the forest area achieves comprehensive monitoring coverage and acceptable precision at a fraction of the cost of laser radar technology
4Measurement precision
If second class survey is conducted, then accurate forest stock data is obtained, but the workload is large and operation becomes complex
Solution Approach 1:
The patent segments the complex forest survey task into standardized measurements at fixed sample plots. Each plot follows a uniform measurement protocol, dividing the overall survey into manageable, repeatable units that reduce operational complexity while maintaining data accuracy through consistent methodology across all locations
Data Source
AI summary
The invention concerns a continuous monitoring method and system for forest stock and its execution method, including: 1, sample plots sampling design; 2, intelligent sample plots layout; 3, automatic sample plot data collection; 4, dynamic update of stock: detecting plot type change subclasses through remote sensing, and updating graphic and attribute forest resource change maps information; building a dynamic forest stand update model through intelligent sample plot data for plot type unchanged subclasses, and then updating attribute information of forest subclasses; 5, precision test and correction; 6, monitoring output: outputting current period stock monitoring data; 7, determining whether a monitoring period arrives. The invention shortens the survey and monitoring period, provides accurate and comparable monitoring results, significantly reduces costs, the workload and risks of work organization, quality inspection, and production safety, particularly suitable for forest resource stock survey and monitoring in counties and forest farms, with significant comprehensive benefits.