Species Distribution Grid Aggregation for Uneven Observation Data
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Solution Overview
Problem
The distribution of species data across various locations is inconsistent and uneven, leading to poor display effects due to insufficient data quantity and variation in species prevalence, which existing databases fail to adequately address.
Innovation Solution
A method involving obtaining original species distribution data, determining a map grid scale, and enhancing data within each grid using species distribution data from surrounding grids, with adjustments for elevation differences and species commonness, and applying weight values based on attenuation coefficients to aggregate data effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If species distribution data is collected from various locations, then data coverage is improved, but data distribution remains uneven and display效果 is poor
Solution Approach 1:
The patent merges data from multiple grids surrounding a central grid to perform data enhancement. By combining data from neighboring grids within a set range, the system aggregates scattered observations into meaningful patterns, transforming uneven distributed data into enhanced display quality through spatial consolidation.
Solution Approach 2:
The patent introduces a spatial dimension by organizing data into grid-based clusters and performing enhancements in the spatial domain. Instead of treating data points independently, the system considers spatial relationships between grids, using surrounding grid data to enhance the central grid, thereby converting one-dimensional data points into two-dimensional spatial patterns.
2Reliability
If data enhancement is performed using surrounding grid data, then data consistency is improved, but computational complexity increases
Solution Approach 1:
The patent segments the spatial domain into discrete grids, allowing data enhancement to be performed independently for each grid. This segmentation enables parallel processing and reduces computational complexity by breaking down the global enhancement problem into localized grid-level operations, where each grid only needs to process data from its immediate surroundings.
Solution Approach 2:
The patent applies local quality enhancement by using only data from surrounding grids within a set range for each central grid, rather than processing global data. This localized approach improves data consistency through spatially-aware enhancement while reducing computational complexity by limiting the data scope to relevant local regions.
3Measurement precision
If elevation differences are considered in data aggregation, then data accuracy is improved, but processing requirements increase
Solution Approach 1:
The patent performs preliminary action by pre-processing and storing elevation data for each grid before the data aggregation process. This allows elevation differences to be quickly referenced during enhancement without performing complex real-time calculations, thereby improving data accuracy while minimizing additional processing energy requirements during the main aggregation operation.
Data Source
AI summary
The present invention provides a species distribution data aggregation method and system, and a storage medium. The method comprises: obtaining original species distribution data; determining a map grid scale displaying the species distribution, and acquiring the original species distribution data within a range of each grid; and taking each grid as a central grid, and performing data enhancement on the central grid by using original species distribution data of multiple other grids within a set range around each grid, thereby obtaining a species distribution data aggregation result of each grid. The species distribution data aggregation method provided by the invention can enhance the display of the species distribution data, thereby improving the data display effects.