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Forest monitoring requires more automated systems to analyse the large amount of remote sensing data. A new method of change detection is proposed for identifying forest land cover change using high spatial resolution satellite images. Combining the advantages of image segmentation, image differencing and stochastic analysis of the multispectral signal,(More)
—Currently, most optical Earth observation satellites carry both a panchromatic sensor and a set of lower spatial resolution multispectral sensors. In order to benefit from both sources of information, several pansharpening methods have been developed to produce a multispectral image at the spatial resolution of the panchromatic band. The aim of this paper(More)
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The objective of this paper is to show that the structure of the spatiotemporal continuum has important implications in practical stochastic hydrology (e.g., geostatistical analysis of hydrologic sites) and is not merely an abstract mathematical concept. We propose that the concept of physical geometry as a spatiotemporal continuum with properties that are(More)
Full-waveform inversions were applied to retrieve surface , two-layered and continuous soil moisture profiles from ground penetrating radar (GPR) data acquired in an 11-ha agricultural field situated in the loess belt area in central Belgium. The radar system consisted of a vector network analyzer combined with an off-ground horn antenna operating in the(More)
Confusion matrix and derived global indices (kappa, overall accuracy, producer accuracy) are widely accepted as a standard method for the accuracy assessment of land use/land cover maps. In order to build the confusion matrix, the ground truth labels of samples are crossed with the map labels. Most of the time, the sampling strategies are simply based on(More)