Map-Element Population Estimation Below Cell-Level Resolution
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Solution Overview
Problem
Existing information processing systems are unable to estimate population in ranges smaller than a cell, limiting the ability to provide detailed population information.
Innovation Solution
A population output device and estimation model that utilize a neural network to estimate population information for each type of map element within an area, using area information and population data to output detailed population data for each map element.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If population estimation is performed using existing information processing systems based on cell data, then population information can be obtained at the cell level, but population information in ranges smaller than the cell cannot be estimated
Solution Approach 1:
The invention segments the cell area into multiple smaller regions using map elements (buildings, roads, parks, water bodies) as boundaries. By dividing the estimation target into finer spatial units corresponding to specific map elements, the system can provide population information at a granular level below the cell level, thus resolving the contradiction between obtaining cell-level population data and losing detailed spatial distribution information
Solution Approach 2:
The invention applies local quality by estimating population separately for each type of map element (e.g., residential buildings, commercial buildings, parks) within the cell area. Instead of providing a single aggregated population figure for the entire cell, the system generates differentiated population estimates for different spatial zones based on their land use characteristics, thereby preserving detailed population distribution information while maintaining overall estimation accuracy
2Loss of information
If population information is estimated for each type of map element, then detailed population distribution information can be output, but the complexity of the estimation model increases
Solution Approach 1:
The invention employs a universal estimation model that handles multiple types of map elements (buildings, roads, parks, water bodies) using a single integrated framework. The model accepts diverse map element data as input and generates population estimates for all element types through unified processing logic, avoiding the need for separate specialized models for each land use category and thus controlling system complexity while delivering detailed population information
Solution Approach 2:
The invention introduces map element data as an intermediary layer between cell-level geographic information and population estimation. By using map elements (buildings, roads, parks) as intermediate spatial units with defined attributes and boundaries, the system bridges the gap between coarse cell data and fine-grained population distribution, enabling detailed estimates without directly complicating the core estimation algorithm
Data Source
AI summary
A population output device 1 includes a storage unit 11 that stores an estimation model that receives an input of area information related to an area and including information related to a population of the area and information related to a summation value, for each type of a map element, related to one or more map elements constituting map data of the area, and outputs population information related to a population estimated for each type of the map element of the area, an acquisition unit 10 that acquires the area information related to a target area that is an area to be targeted, and an output unit 13 that outputs the population information related to the target area, the population information being output by inputting the acquired area information related to the target area to the stored estimation model.