高分辨率无人机影像数据集，覆盖印度水稻全生长周期。
A UAV-Based Multispectral and RGB Dataset for Multi-Stage Paddy Crop Monitoring in Indian Agricultural Fields
- 无人机搭载多光谱与高清相机，按标准流程采集
- 含4.2万张图像，1厘米/像素分辨率，覆盖5英亩农田
- 适合精准农业、病害检测与产量预测研究
本文介绍了一个大规模无人飞行器（UAV）采集的RGB与多光谱图像数据集，覆盖印度安得拉邦维贾亚瓦达地区水稻从育苗到收获的全生长阶段。采用2000万像素RGB相机和500万像素四波段多光谱相机（红、绿、红边、近红外），通过标准化操作流程确保数据可重复性。数据集包含42,430张原始图像（共415 GB），在5英亩田地上以1厘米/像素地面采样距离获取，附带GPS坐标、飞行高度及环境条件等元数据。图像经Pix4D Fields处理生成正射影像图和植被指数图，如归一化差异植被指数（NDVI）和归一化差异红边指数（NDRE）。该数据集是少数提供高分辨率图像与丰富元数据、覆盖印度水稻全生长阶段的数据集之一，可通过IEEE DataPort获取DOI。可用于靶向喷洒、病害分析和产量估算研究。
原文摘要 · Abstract (English)
We present a large-scale unmanned aerial vehicle (UAV)-based RGB and multispectral image dataset collected over paddy fields in the Vijayawada region, Andhra Pradesh, India, covering nursery to harvesting stages. We used a 20-megapixel RGB camera and a 5-megapixel four-band multispectral camera capturing red, green, red-edge, and near-infrared bands. Standardised operating procedure (SOP) and checklists were developed to ensure repeatable data acquisition. Our dataset comprises of 42,430 raw images (415 GB) captured over 5 acres with 1 cm/pixel ground sampling distance (GSD) with associated metadata such as GPS coordinates, flight altitude, and environmental conditions. Captured images were validated using Pix4D Fields to generate orthomosaic maps and vegetation index maps, such as normalised difference vegetation index (NDVI) and normalised difference red-edge (NDRE) index. Our dataset is one of the few datasets that provide high-resolution images with rich metadata that cover all growth stages of Indian paddy crops. The dataset is available on IEEE DataPort with DOI, . It can support studies on targeted spraying, disease analysis, and yield estimation.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。