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使用无人机搭载多光谱(绿色、红色和近红外)相机获取的用于樱桃番茄(品种)监测的航空照片数据集。

Dataset of aerial photographs acquired with UAV using a multispectral (green, red and near-infrared) camera for cherry tomato ( var. ) monitoring.

作者信息

Chávez-Martínez Osiris, Monjardin-Armenta Sergio Alberto, Rangel-Peraza Jesús Gabriel, Mora-Felix Zuriel Dathan, Sanhouse-García Antonio Jesus

机构信息

Universidad Autónoma de Sinaloa, Facultad de Ciencias de la Tierra y el Espacio. Circuito Interior Oriente SN, Cd Universitaria, 80040 Culiacán, Sinaloa, Mexico.

Laboratorio Nacional CONAHCYT de Tecnologías de la Información Geoespacial para los Sistemas Socioecológicos Resilientes (LaNCTIGeSSR), clave 89. Cerro de Coatepec, Ciudad Universitaria, 50110 Toluca de Lerdo, Mexico.

出版信息

Data Brief. 2024 Dec 24;58:111256. doi: 10.1016/j.dib.2024.111256. eCollection 2025 Feb.

Abstract

A dataset of aerial photographs acquired with an Unmanned Aerial Vehicle (UAV) DJI Phantom 4 Pro is presented for monitoring a cherry tomato ( var. ) crop in Navolato, Mexico. Seven photogrammetric flights were carried out to assess the plant growth using a Mapir Survey 3W multispectral camera. Multispectral images with an approximate spatial resolution of 1.83 cm/px were obtained in each photogrammetric flight. These images were acquired every 15 days starting on October 15, 2021, and ending on January 23, 2022. The dataset contains the radiometrically calibrated images of the tomato crop divided into 2 open field parcels. The dataset also includes the processed photogrammetric products (ortho-mosaics) using a binary mask to exclude the soil from the plant area. The dataset was originally acquired to assess plant growth, stress levels, and overall crop health. However, this multispectral imagery dataset can also have various uses, such as creating training datasets with accurate labels or classes which can then be used to develop, train, and/or validate machine learning algorithms for image classification, object detection tasks, or change detection analysis.

摘要

本文展示了一个使用大疆御4 Pro无人机获取的航空照片数据集,用于监测墨西哥纳沃拉托的樱桃番茄(品种)作物。使用Mapir Survey 3W多光谱相机进行了七次摄影测量飞行,以评估作物生长情况。每次摄影测量飞行都获得了空间分辨率约为1.83厘米/像素的多光谱图像。这些图像从2021年10月15日开始,每隔15天获取一次,直至2022年1月23日结束。该数据集包含辐射校准后的番茄作物图像,分为2个露天地块。数据集还包括使用二进制掩膜处理后的摄影测量产品(正射镶嵌图),以将土壤从作物区域中排除。该数据集最初用于评估作物生长、压力水平和整体作物健康状况。然而,这个多光谱图像数据集也有多种用途,比如创建带有准确标签或类别的训练数据集,然后可用于开发、训练和/或验证用于图像分类、目标检测任务或变化检测分析的机器学习算法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b23/11745797/e33d031eb662/gr1.jpg

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