geoskill-urban-population-estimation

Estimate population density from building volume, residential ratio, night-light correction and land-cover weights with total conservation.

城市人口估算 | Urban Population Estimation

Estimates the spatial distribution of population density from building volume, night lights and land-use weights, supporting population spatialization and urban research.

Core algorithm: building volume = footprint area × height; residential weight = volume × night-light correction × LULC weight (water/vegetation weights are 0); population is allocated proportionally to weights, density = weight/Σweight × total population/pixel area. Key property: Σ(density × pixel area) = total population — the population total is strictly conserved.

Dependencies / 依赖

bash

pip install 'numpy' 'rasterio'

Usage / 使用方法

Basic Usage

bash

python geoskill-urban-population-estimation.py --bbox 116.0 39.0 117.0 40.0 [other parameters]

Examples

Example 1 (Synthetic Data (Offline))

bash

python geoskill-urban-population-estimation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

Example 2 (Usage 2)

bash

python geoskill-urban-population-estimation.py --input height.tif --nightlight nl.tif --lulc lulc.tif --output-dir ./out

Example 3 (Usage 3)

bash

python geoskill-urban-population-estimation.py --bbox 121.0 31.0 122.0 32.0 --total-population 500000 --output-dir ./out --quiet

Example 4 (Usage 4)

bash

python geoskill-urban-population-estimation.py --input height.tif --total-population 200000 --pixel-size 30 --output-dir ./out

Example 5 (Usage 5)

bash

python geoskill-urban-population-estimation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --total-population 80000 --output-dir ./out --quiet

Output / 输出

File	Format	Description
population_density.tif	GeoTIFF	Population density (people per unit area)
population_stats.json	JSON	Target/estimated total population, conservation error, mean/max density
output-manifest.json	JSON	Run manifest

Data Source / 数据源 / Source

Local building height + night light + LULC GeoTIFFs; --synthetic mode simulates a comparative scenario of residential areas versus water/vegetation areas.

Privacy / 隐私声明 / Privacy

• Runs offline by default; --synthetic mode requires no network at all.
• All processing is done locally; user data is never uploaded.

License / License

MIT

---

---

name: geoskill-urban-population-estimation description: 'Estimate population density from building volume, residential ratio, night-light correction and land-cover weights with total conservation.'

城市人口估算 | Urban Population Estimation

从建筑体积、夜光与土地利用权重估算人口密度空间分布，服务于人口空间化与城市研究。

核心算法：建筑体积 = 足迹面积×高度；居住权重 = 体积×夜光校正×LULC 权重（水体/植被权重为 0）；人口按权重归一化分配，density = weight/Σweight × 总人口/像元面积。关键性质：Σ(density×像元面积) = 总人口，人口总量严格守恒。

依赖

bash

pip install 'numpy' 'rasterio'

使用方法

基本用法

bash

python geoskill-urban-population-estimation.py --bbox 116.0 39.0 117.0 40.0 [其他参数]

示例

示例 1（合成数据（离线））

bash

python geoskill-urban-population-estimation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

示例 2（用法 2）

bash

python geoskill-urban-population-estimation.py --input height.tif --nightlight nl.tif --lulc lulc.tif --output-dir ./out

示例 3（用法 3）

bash

python geoskill-urban-population-estimation.py --bbox 121.0 31.0 122.0 32.0 --total-population 500000 --output-dir ./out --quiet

示例 4（用法 4）

bash

python geoskill-urban-population-estimation.py --input height.tif --total-population 200000 --pixel-size 30 --output-dir ./out

示例 5（用法 5）

bash

python geoskill-urban-population-estimation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --total-population 80000 --output-dir ./out --quiet

输出

文件	格式	说明
population_density.tif	GeoTIFF	人口密度（人/单位面积）
population_stats.json	JSON	目标/估算总人口、守恒误差、密度均值/最大值
output-manifest.json	JSON	运行清单

数据源 / Source

本地建筑高度 + 夜光 + LULC GeoTIFF；--synthetic 模式模拟居住区与水体/植被区的对照场景。

隐私声明 / Privacy

• 默认离线运行，--synthetic 模式完全无网络。
• 所有处理在本地完成，不上传用户数据。

License

MIT