Description: Background To assess management patterns and outcome in patients with glioblastoma multiforme (GBM) treated during 2008–2010 in Spain. Methods Retrospective analysis of clinical, therapeutic, and survival data collected through filled questionnaires from patients with histologically confirmed GBM diagnosed in 19 Spanish hospitals. Results We identified 834 patients (23% aged 〉70 years). Surgical resection was achieved in 66% of patients, although the extent of surgery was confirmed by postoperative MRI in only 41%. There were major postoperative complications in 14% of patients, and age was the only independent predictor (Odds ratio [OR], 1.03; 95% confidence interval [CI],1.01–1.05; P = .006). After surgery, 57% received radiotherapy (RT) with concomitant and adjuvant temozolomide, 21% received other regimens, and 22% were not further treated. In patients treated with surgical resection, RT, and chemotherapy ( n = 396), initiation of RT ≤42 days was associated with longer progression-free survival (hazard ratio [HR], 0.8; 95% CI, 0.64–0.99; P = .042) but not with overall survival (HR, 0.79; 95% CI, 0.62–1.00; P = .055). Only 32% of patients older than 70 years received RT with concomitant and adjuvant temozolomide. The median survival in this group was 10.8 months (95% CI, 6.8–14.9 months), compared with 17.0 months (95% CI, 15.5–18.4 months; P = .034) among younger patients with GBM treated with the same regimen. Conclusions In a community setting, 57% of all patients with GBM and only 32% of older patients received RT with concomitant and adjuvant temozolomide. In patients with surgical resection who were eligible for chemoradiation, initiation of RT ≤42 days was associated with better progression-free survival.

Description: The dataset is composed of AisaEAGLE airborne hyperspectral imagery data acquired during the AIRMETH2016 campaign on August 27th, 2016 within the Toolik Lake Natural Research Area on the Alaskan North Slope. The Toolik Lake Research Natural Area is representative of the North Slope physiographic province of the Southern Arctic Foothills (Walker et al., 1989). Dominant vegetation types are dictated by soil moisture and geology and include moist tussock tundra, wet sedge meadows, and dry upland heaths. The dataset includes three flight lines with 130 spectral bands ranging from VIS to NIR (451.7 – 897 nm) wavelength regions. The dataset also includes Level 2A EnMAP simulated imagery using the end-to-end Simulation tool (EeteS) with 78 bands from VIS to NIR (423 – 903 mn). The overall goal of the campaign was to acquire airborne imagery over the Toolik Vegetation grid encompassing 94 permanent 1 x 1 m vegetation plots where corresponding, comprehensive multi-seasonal spectral reflectance, photosynthetic pigment, and detailed species composition data exists. The remote sensing data are highly novel and can be used for vegetation mapping of species composition, plant biomass, and photosynthetic activity.

Description: We describe EnMAP-like imaging spectroscopy data files to be used for mineral mapping with the EnMAPBOX software. It is simulated EnMAP satellite data, which is based on hyperspectral flight cam-paign data with the AVIRIS-NG and HyMap sensors. In preparation of the EnMAP satellite mission, an EnMAPBOX software package provides tools for visualization and scientific analysis of the data. Among many applications, the EnMAPBOX contains geological mapping tools (EnGeoMAP). Here we apply these tools to several representative test cases (Boesche, 2015; Boesche et al., 2016; Mielke et al., 2016). The test data comprise two study sites. The first scene covers the Mountain Pass open pit mine - a carbonatite deposit in California, USA. It contains calcitic rock units and rare earth element (REE) bearing minerals of the bastnaesite group, also called fluorocarbonates (Olson et al., 1954). The REE concentrations at mountain pass are 9.2% on average, among the highest in the world (Brüning and Böhmer, 2011). The high concentration and the open pit activities make Mountain Pass an ideal test site to investigate the rare earth element distribution in the surface layer. The airborne image data were collected in 2014 by Jet Propulsion Laboratory (JPL), USA, with the AVIRIS-NG sensor and form the basis for EnMAP simulations (Segl et al., 2012; Thompson et al., 2015). The second HyMap spectral image data covers part of the Miocene Cabo de Gata-Nίjar volcanic field, in southeast Spain. It comprises a subset of (Chabrillat et al., 2016) covering the Rodalquilar and Lomilla Calderas, which host the economically relevant gold-silver, lead-zinc-silver-gold and alunite deposits. It is a hydrothermal alteration complex, representing the silicic alteration, the advanced argillic alter-ation zone, which grades into the argillic and propylitic zone (Arribas et al., 1995, 1989). The image data are part of the Cabo de Gata-Nίjar HyMap imagery which was collected during the DLR HyEurope airborne campaign 2005 in the frame of the GFZ land degradation program (Chabrillat et al., 2016, 2005). We use these datasets to simulate EnMAP-like images for classification and mapping using spectro-scopic remote sensing techniques in the EnGeoMAP tools. The EnMAP end-to-end Simulation (EeteS) tool produced simulated EnMAP like data with a spatial sampling distance of 30 x 30 m and 242 spectral bands (Guanter et al., 2015; Segl et al., 2012).

Description: Soil degradation is a major threat for European soils and therefore, the European Commission recommends intensifying research on soil monitoring to capture changes over time and space. Imaging spectroscopy is a promising technique to create spatially accurate topsoil maps based on hyperspectral remote sensing data. We tested the application of a local partial least squares regression (PLSR) to airborne HySpex and simulated satellite EnMAP (Environmental Mapping and Analysis Program) data acquired in north-eastern Germany to quantify the soil organic carbon (SOC) content. The approach consists of two steps: (i) the local PLSR uses the European LUCAS (land use/cover area frame statistical survey) Soil database to quantify the SOC content for soil samples from the study site in order to avoid the need for wet chemistry analyses, and subsequently (ii) a remote sensing model is calibrated based on the local PLSR SOC results and the corresponding image spectra. This two-step approach is compared to a traditional PLSR approach using measured SOC contents from local samples. The prediction accuracy is high for the laboratory model in the first step with R2 = 0.86 and RPD = 2.77. The HySpex airborne prediction accuracy of the traditional approach is high and slightly superior to the two-step approach (traditional: R2 = 0.78, RPD = 2.19; two-step: R2 = 0.67, RPD = 1.79). Applying the two-step approach to simulated EnMAP imagery leads to a lower but still reasonable prediction accuracy (traditional: R2 = 0.77, RPD = 2.15; two-step: R2 = 0.48, RPD = 1.41). The two-step models of both sensors were applied to all bare soils of the respective images to produce SOC maps. This local PLSR approach, based on large scale soil spectral libraries, demonstrates an alternative to SOC measurements from wet chemistry of local soil samples. It could allow for repeated inexpensive SOC mapping based on satellite remote sensing data as long as spectral measurements of a few local samples are available for model calibration.

Description: The scope of the Science Plan is to describe the scientific background, applications, and activities related to the Environmental Mapping and Analysis Program (EnMAP) mission. Primarily, the document addresses scientists and funding institutions, but it may also be of interest for environmental stakeholders and governmental bodies. It is conceived to be a living document that will be updated throughout the entire mission. Chapter 1 provides a brief overview of the principles and current state of imaging spectroscopy. This is followed by an introduction to the EnMAP mission, including its objectives and potential impact on international programs as well as major environmental and societal challenges to their understanding and management EnMAP can contribute. Chapter 2 describes the EnMAP system together with data products and access, calibration/validation issues, and synergies with other missions. Chapter 3 gives an overview of the relevance, current lines of research, and potential contributions of EnMAP for major fields of application, such as vegetation, geology and soils, coastal and inland waters, cryosphere, urban areas, atmosphere and hazards to address the environmental and societal challenges presented in Chapter 1. Finally, Chapter 4 outlines the scientific exploitation strategy, which includes the strategy for community building and training, preparatory flight campaigns and software developments. A list of abbreviations is provided in the annex to this document, while an extended glossary of terms and abbreviations is available at the EnMAP website.