Publications

Investigations into the spatial dynamics of soil aggregate stability (AS) are urgently needed to better target areas that have undergone soil degradation. However, due to the lack of efficient alternatives to the conventional labor-intensive methods to quantify AS, detailed information on its spatial structure across scales are scarce. The objective of this study was to explore the possibility of using hyperspectral remote sensing imagery to ...

Hyperspectral (HS) super-resolution reconstruction is an ill-posed inversion problem, for which the solution from reconstruction constraint is not unique. To address this, an HS image
super-resolution method is proposed to first utilize the joint regulation of spatial and spectral nonlocal similarities. We then fused the HS and panchromatic images with sparse regulation. With these two regulation terms, edge sharpness and spectrum ...

The value of characteristic reflectance features for mapping urban materials has been demonstrated in many experiments
with airborne imaging spectrometry. Analysis of larger areas requires satellite-based multispectral imagery, which
typically lacks the spatial and spectral detail of airborne data. Consequently the need arises to develop mapping methods
that exploit the complementary strengths of both data sources. In this paper a ...

Natura 2000 habitats are priority habitats for nature conservation in Europe and need to be monitored closely. In this study, angular hyperspectral CHRIS/Proba imagery was tested for mapping a Natura 2000 heathland site in the north of Belgium. Two ensemble classifiers, Random Forest (RF) and
Adaboost, were used and their results compared with Support Vector Machines (SVM). Two classification scenarios were examined: (1) only the nadir ...

Due to the fragmented compositional structure of urban scenes, many pixels are mixtures of multiple materials even in high spatial resolution airborne hyperspectral data. In the past ten years, sparse regression based spectral unmixing methods have achieved some noticeable results. Recently, Chen et al. proposed a jointly sparse spectral mixture analysis model for urban mapping. Their model has a high computational load, however, and wrongly ...

Detailed land use/land cover classification at ecotope level is important for environmental evaluation. In this study, we investigate the possibility of using airborne hyperspectral imagery for the classification of ecotopes. In particular, we assess two tree-based ensemble classification algorithms: Adaboost and Random Forest, based on standard classification accuracy, training time and classification stability. Our results show that Adaboost ...

Hyperspectral remote sensing is based on measuring the scattered and reflected electromagnetic signals from the Earths surface emitted by the Sun. The received radiance at the sensor is usually degraded by atmospheric effects and instrumental (sensor) noises which include thermal (Johnson) noise, quantization noise, and shot (photon) noise. Noise reduction is often considered as a preprocessing step for hyperspectral imagery. In the past decade, ...

This paper presents the results of estimation of leaf chlorophyll concentration through model inversion, from hyperspectral imagery of artificially treated orchard crops. The objectives were to examine model inversion robustness under changing viewing conditions, and the potential of multi-angle hyperspectral data to improve accuracy of chlorophyll estimation. The results were compared with leaf chlorophyll measurements from laboratory analysis ...