process-raster

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🇺🇸

Original

English

🇨🇳

Translation

Chinese

You are helping the user process geospatial raster data using geoai.

Input:

$@

Follow these steps in order.

你正在使用geoai帮助用户处理地理空间栅格数据。

输入：

$@

请按以下顺序执行步骤。

Step 1 -- Determine the operation

步骤1 -- 确定操作类型

Parse

$@

to identify the requested operation:

Operation	Triggers	Required inputs
`clip`	"clip", "crop", "subset", `--bbox` present	input raster + bbox
`stack`	"stack", "combine bands"	list of input rasters
`mosaic`	"mosaic", "merge"	input directory or list of rasters
`raster-to-vector`	"to vector", "vectorize", "polygonize"	input raster
`vector-to-raster`	"to raster", "rasterize", "burn"	input vector + pixel size

If the operation is unclear from the input, ask the user to specify.

解析

$@

以识别请求的操作：

操作	触发关键词	必填输入
`clip`	"clip"、"crop"、"subset"、存在 `--bbox`	输入栅格 + 边界框
`stack`	"stack"、"combine bands"	输入栅格列表
`mosaic`	"mosaic"、"merge"	输入目录或栅格列表
`raster-to-vector`	"to vector"、"vectorize"、"polygonize"	输入栅格
`vector-to-raster`	"to raster"、"rasterize"、"burn"	输入矢量 + 像素大小

如果无法从输入中明确操作类型，请询问用户指定。

Step 2 -- Resolve input file(s)

步骤2 -- 解析输入文件

For single-file operations (

clip

raster-to-vector

vector-to-raster

bash

find "$PWD" -name "INPUT_FILENAME" -not -path '*/.git/*' 2>/dev/null

For multi-file operations (

stack

mosaic

), if a directory is given:

bash

find "INPUT_DIR" -name "*.tif" -o -name "*.tiff" 2>/dev/null | sort

If the user recently inspected or downloaded a file and did not specify an input, check the state file for context:

bash

STATE_DIR=""
test -f .geoai-skills/state.json && STATE_DIR=".geoai-skills"
PROJECT_ROOT="$(git rev-parse --show-toplevel 2>/dev/null || echo "$PWD")"
PROJECT_ID="$(echo "$PROJECT_ROOT" | tr '/' '-')"
test -f "$HOME/.geoai-skills/$PROJECT_ID/state.json" && STATE_DIR="$HOME/.geoai-skills/$PROJECT_ID"

If state exists, read the last inspected or downloaded file:

bash

python3 -c "
import json
with open('STATE_DIR/state.json') as f:
    state = json.load(f)
if 'last_inspected' in state:
    print(f'Last inspected: {state[\"last_inspected\"][\"path\"]}')
if 'downloaded_files' in state:
    for f in state['downloaded_files']:
        print(f'Downloaded: {f}')
"

针对单文件操作（

clip

、

raster-to-vector

、

vector-to-raster

）：

bash

find "$PWD" -name "INPUT_FILENAME" -not -path '*/.git/*' 2>/dev/null

针对多文件操作（

stack

、

mosaic

），如果给定目录：

bash

find "INPUT_DIR" -name "*.tif" -o -name "*.tiff" 2>/dev/null | sort

如果用户最近查看或下载了文件但未指定输入，请检查状态文件获取上下文：

bash

STATE_DIR=""
test -f .geoai-skills/state.json && STATE_DIR=".geoai-skills"
PROJECT_ROOT="$(git rev-parse --show-toplevel 2>/dev/null || echo "$PWD")"
PROJECT_ID="$(echo "$PROJECT_ROOT" | tr '/' '-')"
test -f "$HOME/.geoai-skills/$PROJECT_ID/state.json" && STATE_DIR="$HOME/.geoai-skills/$PROJECT_ID"

如果状态文件存在，读取最近查看或下载的文件：

bash

python3 -c "
import json
with open('STATE_DIR/state.json') as f:
    state = json.load(f)
if 'last_inspected' in state:
    print(f'Last inspected: {state[\"last_inspected\"][\"path\"]}')
if 'downloaded_files' in state:
    for f in state['downloaded_files']:
        print(f'Downloaded: {f}')
"

Step 3 -- Execute the operation

步骤3 -- 执行操作

Clip by bounding box

按边界框裁剪

bash

python3 -c "
import geoai

result = geoai.clip_raster_by_bbox(
    input_raster='INPUT_PATH',
    output_raster='OUTPUT_PATH',
    bbox=[MINX, MINY, MAXX, MAXY],
)
print(f'Clipped raster saved to: {result}')
info = geoai.get_raster_info(result)
for k, v in info.items():
    print(f'{k}: {v}')
"

Default output:

./clipped_<original_name>.tif

bash

python3 -c "
import geoai

result = geoai.clip_raster_by_bbox(
    input_raster='INPUT_PATH',
    output_raster='OUTPUT_PATH',
    bbox=[MINX, MINY, MAXX, MAXY],
)
print(f'Clipped raster saved to: {result}')
info = geoai.get_raster_info(result)
for k, v in info.items():
    print(f'{k}: {v}')
"

默认输出路径：

./clipped_<original_name>.tif

Stack bands

堆叠波段

bash

python3 -c "
import geoai

result = geoai.stack_bands(
    input_files=['FILE1', 'FILE2', 'FILE3'],
    output_file='OUTPUT_PATH',
)
print(f'Stacked raster saved to: {result}')
info = geoai.get_raster_info(result)
for k, v in info.items():
    print(f'{k}: {v}')
"

bash

python3 -c "
import geoai

result = geoai.stack_bands(
    input_files=['FILE1', 'FILE2', 'FILE3'],
    output_file='OUTPUT_PATH',
)
print(f'Stacked raster saved to: {result}')
info = geoai.get_raster_info(result)
for k, v in info.items():
    print(f'{k}: {v}')
"

Mosaic GeoTIFFs

拼接GeoTIFF

bash

python3 -c "
import geoai

result = geoai.mosaic_geotiffs(
    input_dir='INPUT_DIR',
    output_file='OUTPUT_PATH',
)
print(f'Mosaic saved to: {result}')
info = geoai.get_raster_info(result)
for k, v in info.items():
    print(f'{k}: {v}')
"

bash

python3 -c "
import geoai

result = geoai.mosaic_geotiffs(
    input_dir='INPUT_DIR',
    output_file='OUTPUT_PATH',
)
print(f'Mosaic saved to: {result}')
info = geoai.get_raster_info(result)
for k, v in info.items():
    print(f'{k}: {v}')
"

Raster to vector

栅格转矢量

bash

python3 -c "
import geoai

gdf = geoai.raster_to_vector(
    raster_path='INPUT_PATH',
    output_path='OUTPUT_PATH',
)
print(f'Vectorized: {len(gdf)} features')
print(f'Saved to: OUTPUT_PATH')
print(f'Columns: {list(gdf.columns)}')
"

Default output:

./<original_name>.gpkg

bash

python3 -c "
import geoai

gdf = geoai.raster_to_vector(
    raster_path='INPUT_PATH',
    output_path='OUTPUT_PATH',
)
print(f'Vectorized: {len(gdf)} features')
print(f'Saved to: OUTPUT_PATH')
print(f'Columns: {list(gdf.columns)}')
"

默认输出路径：

./<original_name>.gpkg

Vector to raster

矢量转栅格

bash

python3 -c "
import geoai

result = geoai.vector_to_raster(
    vector_path='INPUT_PATH',
    output_path='OUTPUT_PATH',
    pixel_size=PIXEL_SIZE,
)
print(f'Rasterized: {result}')
info = geoai.get_raster_info(result)
for k, v in info.items():
    print(f'{k}: {v}')
"

Default pixel size: 1.0 (or infer from context). Default output:

./<original_name>.tif

Replace all placeholder values with actual paths and parameters before running.

bash

python3 -c "
import geoai

result = geoai.vector_to_raster(
    vector_path='INPUT_PATH',
    output_path='OUTPUT_PATH',
    pixel_size=PIXEL_SIZE,
)
print(f'Rasterized: {result}')
info = geoai.get_raster_info(result)
for k, v in info.items():
    print(f'{k}: {v}')
"

默认像素大小：1.0（或从上下文推断）。默认输出路径：

./<original_name>.tif

运行前请将所有占位符替换为实际路径和参数。

Step 4 -- Update state

步骤4 -- 更新状态

If a state directory exists, update it with the output file path using the same state resolution pattern as Step 2.

如果状态目录存在，使用步骤2中的状态解析规则，将输出文件路径更新到状态文件中。

Step 5 -- Report and suggest

步骤5 -- 报告与建议

Report:

Operation performed
Input and output file paths
Key properties of the output (dimensions, CRS, band count, feature count)

Then suggest: "Use
/geoai-skills:inspect-geo
to examine the result in detail."

报告内容：

执行的操作
输入和输出文件路径
输出文件的关键属性（尺寸、CRS、波段数、要素数）

然后建议："使用
/geoai-skills:inspect-geo
详细查看处理结果。"

Error handling

错误处理

import geoai
fails -> delegate to
```
/geoai-skills:install-geoai
```
.
File not found -> use
```
find
```
to locate, suggest corrected path.
CRS mismatch (for stack/mosaic) -> report the issue and suggest reprojecting first.
Insufficient disk space -> report the error.
Memory error (very large rasters) -> suggest processing in tiles or using a smaller extent.

import geoai
失败 -> 调用
```
/geoai-skills:install-geoai
```
处理。
文件未找到 -> 使用
```
find
```
命令定位，建议修正路径。
CRS不匹配（针对堆叠/拼接操作）-> 报告问题并建议先进行投影转换。
磁盘空间不足 -> 报告错误。
内存错误（处理超大栅格时）-> 建议分块处理或使用更小的范围。