Combining hyperspectral UAV and multispectral Formosat-2 imagery for precision agriculture applications

C.M. Gevaert, J. Tang, F.J. Garcia-Haro, J. Suomalainen, L Kooistra

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

16 Citations (Scopus)


Remote sensing is a key tool for precision agriculture applications as it is capable of capturing spatial and temporal variations in crop status. However, satellites often have an inadequate spatial resolution for precision agriculture applications. High-resolution Unmanned Aerial Vehicles (UAV) imagery can be obtained at flexible dates, but operational costs may limit the collection frequency. The current study utilizes data fusion to create a dataset which benefits from the temporal resolution of Formosat-2 imagery and the spatial resolution of UAV imagery with the purpose of monitoring crop growth in a potato field. The correlation of the Weighted Difference Vegetation Index (WDVI) from fused imagery to measured crop indicators at field level and added value of the enhanced spatial and temporal resolution are discussed. The results of the STARFM method were restrained by the requirement of same-day base imagery. However, the unmixing-based method provided a high correlation to the field data and accurately captured the WDVI temporal variation at field level (r=0.969).
Original languageEnglish
Title of host publication2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing
Subtitle of host publicationWHISPERS
Place of PublicationLausanne
Number of pages4
ISBN (Electronic)978-1-4673-9012-5
Publication statusPublished - 19 Oct 2014
Externally publishedYes
Event6th Workshop On Hyperspectral Image And Signal Processing 2014: Evolution In Remote Sensing - Lausanne, Switzerland
Duration: 24 Jun 201427 Jun 2014
Conference number: 6


Conference6th Workshop On Hyperspectral Image And Signal Processing 2014
Abbreviated titleWHISPERS 2014
Internet address


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