# satellite-analysis-system

**Repository Path**: lyxstart/satellite-analysis-system

## Basic Information

- **Project Name**: satellite-analysis-system
- **Description**: 测试node版本地物分类
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-12-23
- **Last Updated**: 2026-01-14

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

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  <p align="center">A progressive <a href="http://nodejs.org" target="_blank">Node.js</a> framework for building efficient and scalable server-side applications.</p>
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## Description

[Nest](https://github.com/nestjs/nest) framework TypeScript starter repository.

## 已选择的图像处理和机器学习依赖包

本项目经过评估后选择了以下不依赖 C++ 和 Python 的图像处理和机器学习库：

### [gdal-async](https://github.com/mmomtchev/node-gdal-async)
- **描述**: GDAL (Geospatial Data Abstraction Library) 的 Node.js 异步绑定，用于处理地理空间数据
- **选用理由**: 相比于 gdal-next，gdal-async 提供了更好的异步支持和性能，并且避免了复杂的 C++ 编译依赖

### [@tensorflow/tfjs](https://github.com/tensorflow/tfjs)
- **描述**: TensorFlow 的 JavaScript 实现，可在浏览器和 Node.js 环境中运行机器学习模型
- **选用理由**: 相比于 @tensorflow/tfjs-node，纯 JavaScript 版本避免了原生插件的编译问题和 Python 依赖

### [opencv-wasm](https://github.com/echamudi/opencv-wasm)
- **描述**: OpenCV 的 WebAssembly 版本，提供了计算机视觉功能的完整实现
- **选用理由**: 相比于 opencv4nodejs，opencv-wasm 不需要本地编译 OpenCV 库，避免了 C++ 依赖和复杂的构建过程

## 项目架构与核心功能模块

本项目是一个基于 NestJS 的卫星图像植被分析系统，包含以下核心功能模块：

### 模块一：影像解析引擎 (Data Engine)
- 使用 GDAL 分块读取大型卫星 TIFF 文件
- 提取特定波段（如 B4 红光和 B8 近红外）
- 避免一次性加载整个图像到内存

### 模块二：光谱分析算法 (Spectral Logic)
- 利用 TensorFlow.js 计算 NDVI 指数
- 根据阈值生成植被二值矩阵

### 模块三：空间形态优化 (OpenCV Engine)
- 使用 OpenCV 进行形态学处理消除噪点
- 提取并过滤植被区域轮廓

### 模块四：瓦片渲染与展示 (Tile Server)
- 将分析结果渲染为 PNG 图像
- 生成符合 XYZ 标准的瓦片用于前端展示

### 异步任务处理
- 使用 BullMQ 队列处理耗时的图像分析任务
- 避免阻塞主线程，提高系统响应性

## Project setup

```bash
$ npm install
```

## Compile and run the project

```bash
# development
$ npm run start

# watch mode
$ npm run start:dev

# production mode
$ npm run start:prod
```

## Run tests

```bash
# unit tests
$ npm run test

# e2e tests
$ npm run test:e2e

# test coverage
$ npm run test:cov
```

## API Endpoints

### 上传并分析植被图像
```
POST /vegetation/analyze
Content-Type: multipart/form-data

Form fields:
- image: 卫星图像文件 (TIFF/JPEG2000格式)
- threshold: NDVI阈值 (可选，默认0.4)
- nirBand: 近红外波段编号 (可选，默认8，适用于Sentinel-2)
- redBand: 红光波段编号 (可选，默认4，适用于Sentinel-2)
- kernelSize: 形态学处理核大小 (可选，默认3)
- minArea: 最小轮廓面积 (可选，默认100)
- zoomLevel: 瓦片缩放级别 (可选，默认10)
```

### 获取分析任务状态
```
GET /vegetation/status/:jobId
```

### 获取分析结果瓦片
```
GET /vegetation/tiles/:z/:x/:y
```

## Deployment

When you're ready to deploy your NestJS application to production, there are some key steps you can take to ensure it runs as efficiently as possible. Check out the [deployment documentation](https://docs.nestjs.com/deployment) for more information.

If you are looking for a cloud-based platform to deploy your NestJS application, check out [Mau](https://mau.nestjs.com), our official platform for deploying NestJS applications on AWS. Mau makes deployment straightforward and fast, requiring just a few simple steps:

```bash
$ npm install -g @nestjs/mau
$ mau deploy
```

With Mau, you can deploy your application in just a few clicks, allowing you to focus on building features rather than managing infrastructure.

## Resources

Check out a few resources that may come in handy when working with NestJS:

- Visit the [NestJS Documentation](https://docs.nestjs.com) to learn more about the framework.
- For questions and support, please visit our [Discord channel](https://discord.gg/G7Qnnhy).
- To dive deeper and get more hands-on experience, check out our official video [courses](https://courses.nestjs.com/).
- Deploy your application to AWS with the help of [NestJS Mau](https://mau.nestjs.com) in just a few clicks.
- Visualize your application graph and interact with the NestJS application in real-time using [NestJS Devtools](https://devtools.nestjs.com).
- Need help with your project (part-time to full-time)? Check out our official [enterprise support](https://enterprise.nestjs.com).
- To stay in the loop and get updates, follow us on [X](https://x.com/nestframework) and [LinkedIn](https://linkedin.com/company/nestjs).
- Looking for a job, or have a job to offer? Check out our official [Jobs board](https://jobs.nestjs.com).

## Support

Nest is an MIT-licensed open source project. It can grow thanks to the sponsors and support by the amazing backers. If you'd like to join them, please [read more here](https://docs.nestjs.com/support).

## Stay in touch

- Author - [Kamil Myśliwiec](https://twitter.com/kammysliwiec)
- Website - [https://nestjs.com](https://nestjs.com/)
- Twitter - [@nestframework](https://twitter.com/nestframework)

## License

Nest is [MIT licensed](https://github.com/nestjs/nest/blob/master/LICENSE).