0000000000338254
AUTHOR
C.m. Gevaert
showing 2 related works from this author
Combining hyperspectral UAV and multispectral Formosat-2 imagery for precision agriculture applications
2014
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 …
A comparison of STARFM and an unmixing-based algorithm for Landsat and MODIS data fusion
2015
article i nfo The focus of the current study is to compare data fusion methods applied to sensors with medium- and high- spatial resolutions. Two documented methods are applied, the spatial and temporal adaptive reflectance fusion model (STARFM) and an unmixing-based method which proposes a Bayesian formulation to incorporate prior spectral information.Furthermore, thestrengths of both algorithms arecombined ina novel data fusionmethod: the Spatial and Temporal Reflectance Unmixing Model (STRUM). The potential of each method is demonstrated using simulation imagery and Landsat and MODIS imagery. The theoretical basis of the algorithms causes STARFM and STRUM to produce Landsat-like reflecta…