Delineation of Crop Field Areas and Boundaries from UAS Imagery Using PBIA and GEOBIA with Random Forest Classification

Remote Sensing

Greg Patterson¹  Ataollah Haddadi¹  Jinfei Wang²  Armand LaRocque³  Odysseas Vlachopoulos³  Brigitte Leblon³ 

[1] A&L Canada Laboratories, 2136 Jetstream Rd., London, ON N5V 3P5, Canada;Department of Geography, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5C2, Canada;Faculty of Forestry and Environmental Management, University of New Brunswick, 2 Bailey Dr, Fredericton, NB E3B5A3, Canada;

关键词: UAS;    UAV;    random forests;    PBIA;    GEOBIA;    multispectral;   

DOI  :  10.3390/rs12162640

来源: DOAJ

【 摘 要 】

Unmanned aircraft systems (UAS) have been proven cost- and time-effective remote-sensing platforms for precision agriculture applications. This study presents a method for automatic delineation of field areas and boundaries that uses UAS multispectral orthomosaics acquired over 7 vegetated fields having a variety of crops in Prince Edward Island (PEI). This information is needed by crop insurance agencies and growers for an accurate determination of crop insurance premiums. The field areas and boundaries were delineated by applying both a pixel-based and an object-based supervised random forest (RF) classifier applied to reflectance and vegetation index images, followed by a vectorization pipeline. Both methodologies performed exceptionally well, resulting in a mean area goodness of fit (AGoF) for the field areas greater than 98% and a mean boundary mean positional error (BMPE) lower than 0.8 m for the seven surveyed fields.

【 授权许可】

Unknown