香蕉枯萎病无人机多光谱影像数据集

Fusarium wilt of banana, also known as "banana cancer", currently threatens banana production areas worldwide. Timely and accurate identification of Fusarium wilt disease is crucial for effective disease control and optimizing agricultural planting structure. To explore the use of unmanned aerial vehicle (UAV) remote sensing for identifying banana wilt disease, this study obtained comprehensive experimental data on wilted banana plants in a banana plantation in Long'an County, Guangxi. The data set includes UAV multispectral reflectance data and ground survey data on the incidence of banana wilt disease. The UAV multispectral imaging data have high spatial resolution, while the ground survey data is accurate, making them suitable for research on UAV remote sensing identification and monitoring of banana wilt disease. This data set is of great significance for promoting research and application of remote sensing monitoring of crop diseases.

香蕉枯萎病（Fusarium wilt of banana）又称“香蕉癌症”，目前已对全球所有香蕉产区构成威胁。及时、精准地识别香蕉枯萎病，对于开展高效病害防控、优化农业种植结构具有关键意义。为探究利用无人机（unmanned aerial vehicle, UAV）遥感技术识别香蕉枯萎病的可行路径，本研究于广西隆安县某香蕉种植园采集了染病香蕉植株的成套实验数据。本数据集涵盖无人机多光谱反射率数据与香蕉枯萎病发病率地面调查数据两类：无人机多光谱成像数据拥有较高空间分辨率，地面调查数据则具备可靠精度，二者均适配无人机遥感识别与监测香蕉枯萎病的相关研究。该数据集对于推动作物病害遥感监测领域的研究与应用具有重要价值。

搜集汇总

背景与挑战

背景概述

该数据集包含广西隆安县香蕉种植园的无人机多光谱影像和地面调查数据，用于研究香蕉枯萎病的遥感识别和监测。数据集具有高空间分辨率和准确的地面调查数据，适用于作物病害遥感监测的研究和应用。