Preface: the environmental mapping and analysis program (EnMAP) mission: preparing for its scientific exploitation

Open access; distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) licenseThe imaging spectroscopy mission EnMAP aims to assess the state and evolution of terrestrialandaquaticecosystems,examinethemultifacetedimpactsofhumanactivities,andsupport a sustainable use of natural resources. Once in operation (scheduled to launch in 2019), EnMAP will provide high-quality observations in the visible to near-infrared and shortwave-infrared spectral range. The scientific preparation of the mission comprises an extensive science program. This special issue presents a collection of research articles, demonstrating the potential of EnMAP for various applications along with overview articles on the mission and software tools developed within its scientific preparation.Ye

Restoration of Simulated EnMAP Data through Sparse Spectral Unmixing

This paper proposes the use of spectral unmixing and sparse reconstruction methods to restore a simulated dataset for the Environmental Mapping and Analysis Program (EnMAP), the forthcoming German spaceborne hyperspectral mission. The described method independently decomposes each image element into a set of representative spectra, which come directly from the image and have previously undergone a low-pass filtering in noisy bands. The residual vector from the unmixing process is considered as mostly composed of noise and ignored in the reconstruction process. The first assessment of the results is encouraging, as the original bands taken into account are reconstructed with a high signal-to-noise ratio and low overall distortions. Furthermore, the same method could be applied for the inpainting of dead pixels, which could affect EnMAP data, especially at the end of the satellite’s life cycle

Restoration of Simulated EnMAP Data through Sparse Spectral Unmixing

This paper proposes the use of spectral unmixing and sparse reconstruction methods to restore a simulated dataset for the Environmental Mapping and Analysis Program (EnMAP), the forthcoming German spaceborne hyperspectral mission. The described method independently decomposes each image element into a set of representative spectra, which come directly from the image and have previously undergone a low-pass filtering in noisy bands. The residual vector from the unmixing process is considered as mostly composed of noise and ignored in the reconstruction process. The first assessment of the results is encouraging, as the original bands taken into account are reconstructed with a high signal-to-noise ratio and low overall distortions. Furthermore, the same method could be applied for the inpainting of dead pixels, which could affect EnMAP data, especially at the end of the satellite’s life cycle