UAV Visible-Light Imagery of Peanut Seedlings from Shandong, China (2022–2023)

This dataset contains high-resolution UAV visible-light imagery of peanut seedlings collected from two locations in Shandong Province, China: Laixi (Qingdao) and Ningyang (Tai’an). A total of three field plots (Plot1, Plot2, Plot3,Plot4) were established across these two sites. All images were acquired during the early growth stages of peanut seedlings using consumer-grade UAV platforms. The dataset includes imagery captured at three flight altitudes: 15 m, 25 m, and 40 m across multiple field plots. Each image file name provides detailed metadata, including the location, flight height, acquisition date , and plot ID (Plot1, Plot2, Plot3,Plot4). The acquisition period spans 2022–2023, enabling multi-temporal analysis of crop growth dynamics. These visible-light orthophotos can support a wide range of research and applications, including: peanut seedling detection and emergence monitoring vegetation monitoring under different flight altitudes agricultural remote sensing data processing and algorithm development UAV-based field phenotyping studies All images are provided in TIFF format without calculated checksums. This dataset offers high-resolution visible-light imagery that is valuable for agricultural machine learning, crop monitoring, and precision agriculture remote sensing research.This dataset contains high-resolution UAV visible-light imagery of peanut seedlings collected from two locations in Shandong Province, China: Laixi (Qingdao) and Ningyang (Tai’an). A total of three field plots (Plot1, Plot2, Plot3) were established across these two sites. All images were acquired during the early growth stages of peanut seedlings using consumer-grade UAV platforms. The dataset includes imagery captured at three flight altitudes: 15 m, 25 m, and 40 m across multiple field plots. Each image file name provides detailed metadata, including the location, flight height, acquisition date and plot ID (Plot1, Plot2, Plot3,Plot4). The acquisition period spans 2022–2023, enabling multi-temporal analysis of crop growth dynamics. These visible-light orthophotos can support a wide range of research and applications, including: peanut seedling detection and emergence monitoring vegetation monitoring under different flight altitudes agricultural remote sensing data processing and algorithm development UAV-based field phenotyping studies All images are provided in TIFF format without calculated checksums. This dataset offers high-resolution visible-light imagery that is valuable for agricultural machine learning, crop monitoring, and precision agriculture remote sensing research.