UAV-derived BRDF datasets for the wheat and peach trees

Published: 13 November 2025| Version 5 | DOI: 10.17632/hgcbnmxvr8.5
Contributors:
Yuhan Guo, Xihan Mu, Xiang Lyu, Dasheng Fan, Chengzhuo Lei, Ruiqiang Wu, Donghui Xie, Guangjian Yan

Description

This dataset consists of multi-angle remote sensing data of wheat and peach trees collected in Pinggu District, Beijing, China, using a DJI Matrice 350 RTK UAV. The dataset spans key growth stages of the two crops, offering valuable insights into their canopy reflectance dynamics across different phenological periods and different remote sensing geometry. The dataset includes the following components: 1、Raw Data: Digital Number (DN) values directly exported from the onboard sensors of the UAV. These data were acquired at multiple sun-view geometry. 2、Processed Data: Multi-angle reflectance data derived through radiometric calibration of the raw DN values, along with associated geometric parameters such as view and solar angles. These processed data are suitable for further remote sensing analysis, including vegetation index computation and BRDF characterization.

Files

Steps to reproduce

This BRDF dataset was acquired using a DJI Matrice 350 RTK UAV that performed a spherical-helical flight path. Subsequently, we used ENVI 5.6 software to extract the multi-angle reflectance data of the sample plots.

Institutions

  • Beijing Normal University

Categories

Remote Sensing, Vegetation Ecology, Surface Reflectance

Funders

Licence