# 多光谱/高光谱遥感在热带农业中的应用：文献与技术进展综述

> 检索时间：2026年6月25日 | 数据来源：Crossref, Semantic Scholar
> 检索范围：2024-2026年发表文献 | 聚焦热带作物：椰子、油棕、香蕉、芒果、咖啡、可可等

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## 一、检索策略与关键词

| 语言 | 关键词组合 |
|------|-----------|
| 英文 | `hyperspectral tropical crops remote sensing`, `multispectral UAV tropical agriculture`, `PROSAIL tropical crops`, `smart agriculture remote sensing tropical fruit`, `deep learning hyperspectral tropical crops`, `UAV remote sensing oil palm coconut banana mango coffee` |
| 中文 | `高光谱 热带作物 遥感`, `无人机多光谱 智慧农业 热带水果`, `高光谱遥感 椰子 油棕 香蕉 芒果`, `多光谱遥感 热带农业 作物监测`, `热带果树 遥感 高光谱 监测` |

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## 二、热带作物专题研究论文（2024-2026）

### 2.1 油棕（Oil Palm）

| # | 论文标题 | 年份 | 期刊 | DOI |
|---|---------|------|------|-----|
| 1 | **Object-Based Image Analysis (OBIA) on Hyperspectral Imagery from Drone for Ganoderma Basal Stem Rot Disease Detection in Oil Palm** | 2024 | Journal of Oil Palm Research | 10.21894/jopr.2024.0025 |
| 2 | **Ganoderma Detection in Oil Palm Plantations Using UAV Hyperspectral Imaging and AI** | 2025 | TENCON 2025 IEEE | 10.1109/tencon66050.2025.11374927 |
| 3 | **RCNN Algorithm for Oil Palm Tree Imagery Counting Using Unmanned Aerial Vehicle (UAV) Data** | 2025 | IGARSS 2025 | 10.1109/igarss55030.2025.11243092 |
| 4 | **Deep Learning Based Census and Mapping of Oil Palm Plantations from VHR Satellite Images** | 2024 | IGARSS 2024 | 10.1109/igarss53475.2024.10642932 |
| 5 | **Quantification of Adulteration of Palm Kernel Oil in Virgin Coconut Oil Using NIR Hyperspectral Imaging** | 2024 | J. Integrative Agriculture | 10.1016/j.jia.2023.08.002 |
| 6 | **Smartphone Application for Detecting and Visualizing Basal Stem Rot Disease Stages in Oil Palm** | 2025 | Frontiers in Remote Sensing | 10.3389/frsen.2025.1553844 |

**技术重点**：无人机高光谱成像用于灵芝病（Ganoderma）基茎腐病检测，基于对象的图像分析（OBIA），深度学习分类与计数。

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### 2.2 椰子（Coconut）

| # | 论文标题 | 年份 | 期刊 | DOI |
|---|---------|------|------|-----|
| 1 | **A Multi-Source Remote Sensing Identification Framework for Coconut Palm Mapping** | 2025 | Remote Sensing | 10.3390/rs18010102 |
| 2 | **An EfficientNet Based Model for Classification of Oil Palm, Coconut and Banana Trees in Drone Images** | 2024 | SSRN | 10.2139/ssrn.4994651 |

**技术重点**：多源遥感数据融合的椰子识别框架，深度学习无人机影像分类（油棕/椰子/香蕉三分类）。

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### 2.3 香蕉（Banana）

| # | 论文标题 | 年份 | 期刊 | DOI |
|---|---------|------|------|-----|
| 1 | **Banana Plantation Identification Using Remote Sensing Data in Tropical and Subtropical Regions** | 2025 | EGU General Assembly | 10.5194/egusphere-egu25-2709 |
| 2 | **An EfficientNet Based Model for Classification of Oil Palm, Coconut and Banana Trees in Drone Images** | 2024 | SSRN | 10.2139/ssrn.4994651 |

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### 2.4 芒果（Mango）

| # | 论文标题 | 年份 | 期刊 | DOI |
|---|---------|------|------|-----|
| 1 | **Mango Quality Assessment Using Near-Infrared Spectroscopy and Hyperspectral Imaging: A Systematic Review** | 2025 | Agronomy | 10.3390/agronomy15102271 |
| 2 | **Rapid Assessment of Lychee and Mango Fruit Quality Using Hyperspectral Imaging** | 2025 | LWT | 10.1016/j.lwt.2025.117833 |
| 3 | **High-Precision Mango Orchard Mapping Using a Deep Learning Pipeline** | 2024 | Remote Sensing | 10.3390/rs16173207 |
| 4 | **MangiSpectra: UAV+LSTM for Tree Health and Yield Estimation in Mango Orchards** | 2025 | Remote Sensing | 10.3390/rs17040703 |

**技术重点**：NIR光谱和高光谱成像的芒果品质检测综述，无人机+LSTM框架的芒果物候分析与产量估测。

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### 2.5 咖啡（Coffee）

| # | 论文标题 | 年份 | 期刊 | DOI |
|---|---------|------|------|-----|
| 1 | **AI-Driven Segmentation of UAV GNDVI Imagery in Shade-Grown Coffee** | 2025 | IEEE CONCAPAN XLIII | 10.1109/concapan66820.2025.11512412 |

**技术重点**：无人机GNDVI影像分割用于荫蔽咖啡林检测。

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### 2.6 其他热带作物

| 作物 | 论文标题 | 年份 | 期刊 | DOI |
|------|---------|------|------|-----|
| **橡胶** | Crop Water Requirement Estimation for Rubber Plantation Using Hyperspectral RS | 2024 | IEEE InGARSS | 10.1109/ingarss61818.2024.10984283 |
| **橡胶** | Novel Hyperspectral Index (RPMI) for Rubber Tree Powdery Mildew Severity | 2026 | SPIE RSTSM | 10.1117/12.3115588 |
| **荔枝** | Enhanced Litchi Fruit Detection Integrating Hyperspectral Reconstruction and YOLOv8 | 2025 | Comp. Elec. Agri. | 10.1016/j.compag.2025.110659 |
| **荔枝** | Rapid Assessment of Lychee and Mango Fruit Quality Using HSI | 2025 | LWT | 10.1016/j.lwt.2025.117833 |
| **水稻(热带)** | Rice Crop Parameters Predicted Using UAV Multispectral Imagery | 2025 | Tropical Agri. Res. | 10.4038/tar.v36i1.8885 |

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## 三、核心技术方法论论文

### 3.1 PROSAIL辐射传输模型

| # | 论文标题 | 年份 | 期刊 | DOI |
|---|---------|------|------|-----|
| 1 | Carotenoids Increase as Early Stress Indicator: PROSAIL with Hyperspectral Drone Data | 2025 | IGARSS 2025 | 10.1109/igarss55030.2025.11242690 |
| 2 | Improved PROSAIL + Hybrid Deep Learning for Biophysiological Traits | 2025 | SSRN | 10.2139/ssrn.5109462 |
| 3 | Retrieval of Crop Canopy Chlorophyll: Machine Learning vs. PROSAIL | 2024 | Remote Sensing | 10.3390/rs16122058 |
| 4 | Winter Wheat LAI Inversion Using PSO-NN-PROSAIL Model | 2024 | Int. J. Remote Sensing | 10.1080/01431161.2024.2339200 |

### 3.2 无人机多光谱/高光谱平台

| # | 论文标题 | 年份 | 期刊 | DOI |
|---|---------|------|------|-----|
| 1 | Systematic Review of Multispectral UAV Image Datasets for Precision Agriculture | 2026 | Remote Sensing | 10.3390/rs18040659 |
| 2 | UC-HSI: UAV-Based Crop Hyperspectral Imaging Datasets and ML Benchmark | 2024 | IEEE GRSL | 10.1109/lgrs.2024.3431644 |
| 3 | Evaluating Spectral Resolution Effects: UAV Multi vs Hyperspectral | 2026 | EGU | 10.5194/egusphere-egu26-743 |
| 4 | ML for Crop Water Stress in Smallholder Farms Using UAV Multispectral | 2025 | SSRN | 10.2139/ssrn.5280483 |

### 3.3 深度学习与AI方法

| # | 论文标题 | 年份 | 期刊 | DOI |
|---|---------|------|------|-----|
| 1 | Deep Learning for Satellite, UAV, and Hyperspectral Crop Monitoring | 2026 | Farming 5.0 | 10.1201/9781003715726-4 |
| 2 | A2Former: Airborne Hyperspectral Crop Classification with Attention | 2026 | Remote Sensing | 10.3390/rs18020220 |
| 3 | Hybrid Ensemble Framework for Hyperspectral Crop Classification | 2026 | J. Indian Soc. RS | 10.1007/s12524-025-02369-8 |
| 4 | Hierarchical Spectral-Spatial Transformer for HSI+MSI Fusion | 2024 | Remote Sensing | 10.3390/rs16224127 |

### 3.4 Computers and Electronics in Agriculture 相关

| # | 论文标题 | 年份 | DOI |
|---|---------|------|-----|
| 1 | Enhanced Litchi Detection with Hyperspectral Reconstruction + YOLOv8 | 2025 | 10.1016/j.compag.2025.110659 |
| 2 | Multi-Scale Semantic Feature Fusion for RS Crop Classification | 2024 | 10.1016/j.compag.2024.109185 |
| 3 | 3D Crop Reconstruction: Review of HSI and MSI Approaches | 2026 | 10.1016/j.compag.2025.111282 |
| 4 | ML Models for Pre-harvest Tomato Fruit Quality Using HSI | 2025 | 10.1016/j.compag.2024.109788 |
| 5 | WOFOST+SCOPE Model Coupling for RS-Based Crop Growth | 2024 | 10.1016/j.compag.2024.109238 |

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## 四、高价值综述论文

| # | 论文标题 | 年份 | 期刊 | DOI |
|---|---------|------|------|-----|
| 1 | **Tree Crop Yield Estimation and Prediction Using RS and ML: A Systematic Review** | 2024 | Smart Agri. Tech. | 10.1016/j.atech.2024.100556 |
| 2 | Mango Quality Assessment Using NIR Spectroscopy and HSI: Systematic Review | 2025 | Agronomy | 10.3390/agronomy15102271 |
| 3 | Systematic Review of Multispectral UAV Image Datasets for Precision Agri. | 2026 | Remote Sensing | 10.3390/rs18040659 |
| 4 | AI+RS for Crop Growth Estimation and Yield Prediction: Sys. Review | 2025 | EGU | 10.5194/egusphere-egu25-8207 |
| 5 | Assessing Model Trade-Offs in Agricultural RS: ML and DL Review | 2025 | Remote Sensing | 10.3390/rs17152670 |

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## 五、中文文献

| # | 论文标题 | 年份 | 期刊 |
|---|---------|------|------|
| 1 | 无人机遥感技术在农作物病虫害监测中的应用与优化 | 2025 | 农业科技与发展 |
| 2 | 深度学习结合多传感器数据融合的农田环境智能管控分析 | 2026 | 农业科学 |
| 3 | 高分高光谱遥感图像计算成像：从融合到光谱超分 | 2025 | 遥感学报 |
| 4 | SSViM：用于高光谱图像分类的空间光谱Vision Mamba网络 | 2026 | 激光与光电子学进展 |

> ⚠️ **注意**：CNKI（知网）无公开API，中文核心期刊论文检索受限。建议通过 CNKI (https://www.cnki.net) 检索《农业工程学报》《遥感学报》《光谱学与光谱分析》《热带作物学报》《中国农业科学》等期刊。

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## 六、技术趋势总结

### 主要技术路径

| 技术方向 | 成熟度 | 热带作物应用热点 |
|---------|--------|----------------|
| 无人机多光谱遥感 | 成熟 | 长势监测、营养诊断、病虫害检测 |
| 无人机高光谱成像 | 较成熟 | 病害早期检测（油棕Ganoderma）、品质评估 |
| PROSAIL辐射传输模型 | 较成熟 | LAI、叶绿素含量反演 |
| 深度学习+高光谱 | 较成熟 | 作物分类、树种识别、病害检测 |
| 高光谱-多光谱融合 | 发展中 | 提升时空分辨率 |
| 时序遥感分析 | 发展中 | 物候监测、产量预测 |
| IoT+高光谱集成 | 初步 | 智慧灌溉、精准施肥 |

### 热带作物遥感的主要挑战

1. **云覆盖严重** → SAR+光学融合、无人机低空飞行
2. **冠层结构复杂** → LiDAR+光谱融合、3D重建
3. **地面真值获取困难** → 无人机辅助采样、弱监督学习
4. **品种特异性** → 品种级光谱库建设

### 数据源库建设建议

**高优先级数据源**：
- UC-HSI dataset (UAV-based Crop Hyperspectral Imaging)
- Sentinel-2 MSI（10m分辨率，免费）
- PRISMA hyperspectral satellite
- 国产高分系列（GF-5高光谱、GF-6多光谱）

**关键模型与算法**：
- PROSAIL RTM → 冠层参数反演
- A2Former / Vision Transformer → 高光谱分类
- YOLOv8 → 无人机影像检测
- LSTM → 物候时序建模

**热带作物专题光谱库**：
- 油棕：健康 vs Ganoderma病害光谱
- 椰子：不同品种/树龄光谱
- 芒果：不同成熟度/品质光谱
- 咖啡：荫蔽 vs 全光照光谱
- 香蕉：不同生长阶段光谱

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## 七、Top 10 必读论文推荐

1. **Trentin et al. (2024)** - Tree crop yield estimation using RS+ML review
2. **Izzuddin (2024)** - OBIA+HSI for Ganoderma in oil palm
3. **Wen et al. (2025)** - Multi-source RS for coconut mapping
4. **Chaudhary et al. (2025)** - Mango quality NIR/HSI review
5. **Afsar et al. (2024)** - Deep learning mango orchard mapping
6. **Afsar et al. (2025)** - MangiSpectra: UAV+LSTM for mango yield
7. **Kanwal et al. (2025)** - Lychee/mango HSI quality assessment
8. **Xie et al. (2025)** - Litchi detection + HSI reconstruction + YOLOv8
9. **Kwang et al. (2025)** - Ganoderma detection UAV HSI+AI
10. **Martinez et al. (2025)** - Coffee GNDVI UAV AI segmentation

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## 八、检索局限与建议

1. **CNKI受限**：知网无公开API，中文论文需手动检索
2. **全文获取**：通过DOI在Sci-Hub或机构订阅获取
3. **持续跟踪期刊**：Remote Sensing, Comp. Elec. Agri., ISPRS JPRS, Precision Agriculture
4. **预印本**：SSRN和arXiv有最新未出版论文