Yuxiang Wang , Gert Kootstra , Zengling Yang , Haris Ahmad Khan
{"title":"无人机多光谱农业遥感:不同光照条件下辐射校正方法的比较研究","authors":"Yuxiang Wang , Gert Kootstra , Zengling Yang , Haris Ahmad Khan","doi":"10.1016/j.biosystemseng.2024.11.005","DOIUrl":null,"url":null,"abstract":"<div><div>Unmanned aerial vehicles (UAVs) equipped with multispectral cameras have been widely used in precision agriculture. However, a notable challenge is the variation in ambient illumination, which affects the accuracy and reliability of UAV-based spectral-data acquisition. In this study, the aim is to evaluate and enhance the performance of existing radiometric correction techniques under varying illumination conditions, primarily concerning radiometric accuracy and homogeneity. Seven methods including three conventional methods and four new methods were employed for correcting the MicaSense Altum multispectral system which equips with a downwelling light sensor (DLS). Two specific strategies were adopted: (1) capturing reference panels at UAV flying altitudes, and (2) strategically placing multiple sets of reference panels throughout the study area. The result shows that calibrating images one time, for instance, the empirical line method (ELM), is seriously affected by the variable illumination. The commercial solution that using the DLS helps improve the uniformity of orthomosaics but lower its radiometric accuracy. Optimising the use of the DLS by capturing panels at the UAV's flight altitude can greatly improve accuracy. Additionally, when the DLS is unavailable, strategically placing multiple reference panels across the field and correcting calibration parameters for each image can effectively help mitigate the impact of varying illumination on generated reflectance orthomosaics. In conclusion, selecting suitable radiometric correction methods is crucial for UAV multi-spectral data collection when facing variable illumination conditions.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"248 ","pages":"Pages 240-254"},"PeriodicalIF":4.4000,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"UAV multispectral remote sensing for agriculture: A comparative study of radiometric correction methods under varying illumination conditions\",\"authors\":\"Yuxiang Wang , Gert Kootstra , Zengling Yang , Haris Ahmad Khan\",\"doi\":\"10.1016/j.biosystemseng.2024.11.005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Unmanned aerial vehicles (UAVs) equipped with multispectral cameras have been widely used in precision agriculture. However, a notable challenge is the variation in ambient illumination, which affects the accuracy and reliability of UAV-based spectral-data acquisition. In this study, the aim is to evaluate and enhance the performance of existing radiometric correction techniques under varying illumination conditions, primarily concerning radiometric accuracy and homogeneity. Seven methods including three conventional methods and four new methods were employed for correcting the MicaSense Altum multispectral system which equips with a downwelling light sensor (DLS). Two specific strategies were adopted: (1) capturing reference panels at UAV flying altitudes, and (2) strategically placing multiple sets of reference panels throughout the study area. The result shows that calibrating images one time, for instance, the empirical line method (ELM), is seriously affected by the variable illumination. The commercial solution that using the DLS helps improve the uniformity of orthomosaics but lower its radiometric accuracy. Optimising the use of the DLS by capturing panels at the UAV's flight altitude can greatly improve accuracy. Additionally, when the DLS is unavailable, strategically placing multiple reference panels across the field and correcting calibration parameters for each image can effectively help mitigate the impact of varying illumination on generated reflectance orthomosaics. In conclusion, selecting suitable radiometric correction methods is crucial for UAV multi-spectral data collection when facing variable illumination conditions.</div></div>\",\"PeriodicalId\":9173,\"journal\":{\"name\":\"Biosystems Engineering\",\"volume\":\"248 \",\"pages\":\"Pages 240-254\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2024-11-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biosystems Engineering\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S153751102400240X\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURAL ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosystems Engineering","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S153751102400240X","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
UAV multispectral remote sensing for agriculture: A comparative study of radiometric correction methods under varying illumination conditions
Unmanned aerial vehicles (UAVs) equipped with multispectral cameras have been widely used in precision agriculture. However, a notable challenge is the variation in ambient illumination, which affects the accuracy and reliability of UAV-based spectral-data acquisition. In this study, the aim is to evaluate and enhance the performance of existing radiometric correction techniques under varying illumination conditions, primarily concerning radiometric accuracy and homogeneity. Seven methods including three conventional methods and four new methods were employed for correcting the MicaSense Altum multispectral system which equips with a downwelling light sensor (DLS). Two specific strategies were adopted: (1) capturing reference panels at UAV flying altitudes, and (2) strategically placing multiple sets of reference panels throughout the study area. The result shows that calibrating images one time, for instance, the empirical line method (ELM), is seriously affected by the variable illumination. The commercial solution that using the DLS helps improve the uniformity of orthomosaics but lower its radiometric accuracy. Optimising the use of the DLS by capturing panels at the UAV's flight altitude can greatly improve accuracy. Additionally, when the DLS is unavailable, strategically placing multiple reference panels across the field and correcting calibration parameters for each image can effectively help mitigate the impact of varying illumination on generated reflectance orthomosaics. In conclusion, selecting suitable radiometric correction methods is crucial for UAV multi-spectral data collection when facing variable illumination conditions.
期刊介绍:
Biosystems Engineering publishes research in engineering and the physical sciences that represent advances in understanding or modelling of the performance of biological systems for sustainable developments in land use and the environment, agriculture and amenity, bioproduction processes and the food chain. The subject matter of the journal reflects the wide range and interdisciplinary nature of research in engineering for biological systems.