SAR 海冰制图 | SAR Sea Ice Mapping

Maps sea ice type and concentration from single-temporal SAR σ⁰ (linear power). Physical basis:

• Open water: specular reflection, very low σ⁰ (~−24 dB) and uniform texture.
• Young ice: newly formed ice surface, moderate σ⁰ and fairly uniform texture.
• Multi-year ice: repeatedly frozen and thawed, rough surface, high σ⁰ and strong texture.

Processing workflow:

1. Three-class Otsu on a dB scale: 3-class Otsu on 10·log10(σ⁰) separates open water / young ice / multi-year ice (log scale + three thresholds prevent young ice from being merged into open water; bimodal scenes automatically fall back to 2 classes).
2. GLCM texture refinement: multi-year ice = high σ⁰ and high GLCM contrast; the remaining ice is classified as young ice. --season summer raises the texture threshold (summer melt weakens texture, so multi-year ice is judged more conservatively).
3. Concentration: fraction of ice pixels within the --window sliding window (ice concentration ∈ [0,1]).

Dependencies / 依赖

pip install numpy rasterio scipy

Usage / 使用方法

Basic usage (bbox only, synthetic data auto-generated)

python geoskill-sar-sea-ice-mapping.py --bbox 120.0 75.0 122.0 77.0 --output-dir ./out

Example 1: synthetic data (offline, winter)

python geoskill-sar-sea-ice-mapping.py --bbox 120 75 122 77 --synthetic --season winter --output-dir ./syn

Example 2: real SAR σ⁰ imagery

python geoskill-sar-sea-ice-mapping.py --input sigma0_linear.tif --output-dir ./real

Example 3: summer scenario

python geoskill-sar-sea-ice-mapping.py --bbox 120 75 122 77 --season summer --output-dir ./summer --quiet

Example 4: custom concentration window

python geoskill-sar-sea-ice-mapping.py --bbox 120 75 122 77 --window 15 --output-dir ./w15 --quiet

Output / 输出

Data Source / 数据源 / Source

• Real mode: local SAR σ⁰ GeoTIFF (linear power).
• Synthetic mode: locally generated sea-surface background + young / multi-year ice areas (with different σ⁰ and texture).

Privacy / 隐私声明 / Privacy

• Fully offline by default; --synthetic mode makes no network calls.
• All processing is done locally; no user data is uploaded.

License / License

MIT

name: geoskill-sar-sea-ice-mapping description: '从SAR σ⁰制图海冰类型与密集度：dB刻度三类Otsu分水面/新冰/多年冰，GLCM纹理精炼多年冰，滑窗计算冰密集度，输出海冰类型GeoTIFF、密集度GeoTIFF与面积统计JSON。SAR sea ice type and concentration mapping via multi-Otsu backscatter thresholds and GLCM texture.'

SAR 海冰制图 | SAR Sea Ice Mapping

从单时相 SAR σ⁰（线性功率）制图海冰类型与密集度。物理依据：

• 开放水面：镜面反射，σ⁰ 极低（~−24 dB）、纹理均匀。
• 新冰（young ice）：初生冰面，σ⁰ 中等、纹理较均匀。
• 多年冰（multi-year ice）：反复冻融、表面粗糙，σ⁰ 高且纹理强。

方法流程：

1. dB 刻度三类 Otsu：在 10·log10(σ⁰) 上用 3 类 Otsu 分水面 / 新冰 / 多年冰（对数刻度 + 三阈值避免新冰被并入水面；双峰场景自动回退 2 类）。
2. GLCM 纹理精炼：多年冰 = 高 σ⁰ 且高 GLCM 对比度，其余冰判为新冰。 --season summer 会提高纹理门限（夏季融冰减弱纹理，更保守判多年冰）。
3. 密集度：--window 滑窗内冰像元占比（ice concentration ∈ [0,1]）。

依赖

pip install numpy rasterio scipy

使用方法

基本用法（仅给 bbox，自动合成）

python geoskill-sar-sea-ice-mapping.py --bbox 120.0 75.0 122.0 77.0 --output-dir ./out

示例 1：合成数据（离线，冬季）

python geoskill-sar-sea-ice-mapping.py --bbox 120 75 122 77 --synthetic --season winter --output-dir ./syn

示例 2：真实 SAR σ⁰ 影像

python geoskill-sar-sea-ice-mapping.py --input sigma0_linear.tif --output-dir ./real

示例 3：夏季场景

python geoskill-sar-sea-ice-mapping.py --bbox 120 75 122 77 --season summer --output-dir ./summer --quiet

示例 4：自定义密集度窗口

python geoskill-sar-sea-ice-mapping.py --bbox 120 75 122 77 --window 15 --output-dir ./w15 --quiet

输出

数据源 / Source

• 真实模式：本地 SAR σ⁰ GeoTIFF（线性功率）。
• 合成模式：本地生成海面背景 + 新冰 / 多年冰区（不同 σ⁰ 与纹理）。

隐私声明 / Privacy

• 默认完全离线运行，--synthetic 无任何网络。
• 所有处理本地完成，不上传用户数据。

License

MIT