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The increasing threat of high-severity wildfires in Mediterranean Wildland-Urban Interface (WUI) areas demands to develop effective fire risk assessment and management strategies. Simultaneously, the newfound accessibility of spaceborne hyperspectral data represents a significant potential for generating fire severity assessments, whereas National Forest Inventories (NFI) offer a vast dataset related to vegetation and fuel loads, which is essential for shaping the planning and strategies of forest services. This research work aims to advance the state-of-the-art in WUI fire risk mapping in the western Mediterranean Basin by combining PRISMA spaceborne hyperspectral data and Spanish NFI data. The proposed methodology had three main stages: (i) fire severity assessment at local scale (a wildfire) by using PRISMA hyperspectral data and Multi-Endmember Spectral Mixture Analysis (MESMA) leveraging field-based measurements of the Composite Burn Index (70 plots); (ii) development of a high fire severity probability map at regional scale from the extrapolation of a Random Forest predictive model calibrated from fire severity estimates, NFI data and topo-climatic variables at local scale (overall accuracy = 92 %; Kappa = 0.8); and (iii) identification and characterization of zones that concentrate WUIs with high probability of high fire severity if a fire event occurs (hot-spot WUIs) by crossing the information from the previous regional high fire severity probability map and a WUI cartography developed at regional scale. Study area was Castilla y León Autonomous Region (larger Spanish region, 94,226 km2), where the second-largest extreme Spanish wildfire event (28,000 ha) occurred. We identified hot-spot WUIs so that stakeholders and decision-makers could (i) prioritize resources and interventions for effective fire management and mitigation, (ii) allocate resources for prevention, and (iii) plan evacuation measures to safeguard lives and property. This study contributes to the development of next-generation fire risk assessment methods that combine remote sensing technologies with comprehensive ground-level datasets.

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Advances in remote sensing techniques for water environments have led to acquisition of abundant data on suspended sediment concentration (SSC). However, confounding factors, such as particle sizes, mineral properties, and bottom materials, have not been fully studied, despite their substantial interference with the detection of intrinsic signals of suspended sediments. Therefore, we investigated the spectral variability arising from the sediment and bottom using laboratory and field-scale experiments. In the laboratory experiment, we focused on measuring spectral characteristics of suspended sediment according to particle size and sediment type. The laboratory experiment was conducted under conditions of completely mixed sediment and non-bottom reflectance using a specially designed rotating horizontal cylinder. To investigate the effects of different channel bottoms under sediment-laden flow conditions, we performed sediment tracer tests in field-scale channels comprising sand and vegetated bottoms. Based on experimental datasets, we performed spectral analysis and multiple endmember spectral mixture analysis (MESMA) to quantify the effect of spectral variability of sediment and bottom on the relationship between hyperspectral data and SSC. The results showed that optimal spectral bands were precisely estimated under non-bottom reflectance conditions, and the effective wavelengths depended on the sediment type. The fine sediments had a higher backscattering intensity compared to the coarse sediments, and the reflectance difference according to the particle size difference increased as the SSC increased. However, in the field-scale experiment, the bottom reflectance substantially decreased the R2 in the relationship between the hyperspectral data and SSC. Nevertheless, MESMA can quantify the contribution of suspended sediment and bottom signals as fractional images. Moreover, the suspended sediment fraction had a clear exponential relationship with SSC in all cases. We conclude that MESMA-driven sediment fractions could be an important alternative for estimating SSC in shallow rivers, as it quantifies the contributions of each factor and then minimizes the bottom effect.

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Following the success of the first hyperspectral sensor, the evaluation of hyperspectral image capability became a challenge in research, which mainly focused on improving image pre-processing and processing steps to minimize their errors, whereas in this study, the focus was on the weight of hyperspectral sensor characteristics on image capability in order to distinguish this effect from errors caused by image pre-processing and processing steps and improve our knowledge of errors. For these purposes, two satellite hyperspectral sensors with similar spatial and spectral characteristics (Hyperion and PRISMA) were compared with corresponding synthetic images, and the city of Venice was selected as the study area. After creating the synthetic images, the errors in the simulation of Hyperion and PRISMA images were evaluated (1.6 and 1.1%, respectively). The same spectral unmixing procedure was performed using real and synthetic images, and their accuracies were compared. The spectral accuracies in root mean square error were equal to 0.017 and 0.016, respectively. In addition, 72.3 and 77.4% of these values were related to sensor characteristics. The spatial accuracies in the mean absolute error were equal to 3.93 and 3.68, respectively. A total of 55.6 and 59.0% of these values were related to sensor characteristics, and 22.6 and 22.3% were related to co-localization and spatial resampling errors. The difference between the radiometric precision values of the sensors was 6.81 and 5.91% regarding the spectral and spatial accuracies of Hyperion image. In conclusion, the results of this study showed that the combined use of two or more real hyperspectral images with similar characteristics and their synthetic images quantifies the weight of hyperspectral sensor characteristics on their image capability and improves our knowledge regarding processing errors, and thus image capability.

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During 2012-2016 California experienced the longest and most severe drought in the last centuries. This water scarcity led to an increase in non-cultivated croplands during this period. The objective of this study was to quantify agricultural trends in the Central Valley (California) at peak growth from 2013 to 2016 during the drought and in 2017-2018 post-drought. For this purpose, we analysed yearly official harvested area reported at county level for the main crops and compared them to visible-shortwave infrared (VSWIR) spectra acquired by the Airborne Visible/Infrared Imaging-Spectrometer (AVIRIS-classic) over 2334 km2 of the Central Valley each year. Multiple Endmember Spectral Mixture Analysis (MESMA) was applied to AVIRIS data to estimate green vegetation (GV), non-photosynthetic vegetation (NPV) and soil fractions in crop fields each year. MESMA and crop reports (R2 = 0.9) showed that soil (i.e.; non-cultivated areas) increased during the summers of the drought; with the smallest GV area in 2015, the second year classified with exceptional drought in this period. According to MESMA, 34 % of the cropland was covered by GV in 2015, and 69.5·104 ha according to the crop reports. MESMA also registered the highest value of soil area in 2015 (48 %). The year with most cultivated area was 2017, the wettest year in the studied period, with 54 % of the croplands covered by GV and 75.2·104 ha. This study verified that the non-cultivated areas increased in the Central Valley during the exceptional drought period and validated the use of AVIRIS imagery to monitor broad-scale cropland use changes in future climatic extreme events.

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Accidental releases of hazardous waste related to the extraction, refining, and transport of oil and gas are inevitable. Petroleum facilities and intrinsic pipelines present environmental pollution risks, threatening both human health and ecosystems. Research has been undertaken to enhance the conventional methods for monitoring hazardous waste problems and to improve time-consuming and cost-effective ways for leak detection and remediation process. In this study, both diffuse and imaging (hyperspectral) reflectance spectroscopy are used for detection and characterization of petroleum hydrocarbon (PHC) contamination in latosols. Laboratory and field measurements of PHC-contaminated and PHC-free soils were collected from an oil facility using an ASD FieldSpec-3 high-resolution portable spectrometer (2150 channels) covering visible, near infrared and shortwave infrared wavelengths (VNIR-SWIR: 350-2500 nm). The hyperspectral image dataset was acquired with the ProSpecTIR-VS airborne sensor using 357 channels in the VNIR-SWIR range at 1 m of spatial resolution. Narrow intervals of reflectance spectra were analyzed to identify the primary mineral and PHC absorption bands in soil samples and to investigate the spectral match with airborne hyperspectral data. The Multiple Endmember Spectral Mixture Analysis (MESMA) method was employed in three hierarchical levels to classify the hyperspectral imagery. The classification product yielded from MESMA model at the fourth level was 98% accurate in discriminating contaminated soils. The results demonstrated the applicability of both diffuse reflectance and imaging (hyperspectral) spectroscopy to identify bare soils contaminated by PHC leaks and spills. These technologies can also provide useful information for remediation initiatives, thereby avoiding further problems with hazardous waste.

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Since 1992, Afghanistan has gradually become the primary illicit opium producer in the entire world. To efficiently eradicate the opium poppy, it is crucial for the United Nations Office on Drugs and Crime (UNODC) and Ministry of Counter Narcotics of Afghanistan to monitor opium poppy cultivation timely. In situ detection of opium fields, however, is often expensive, time-consuming and dangerous in Afghanistan. To overcome the constraints of inaccessibility of opium fields, high-resolution (≤1 m) images, like pan-sharpened IKONOS, have been applied in previous studies. Unfortunately, these high-resolution images are expensive when monitoring a large area. In contrast, EO-1 Hyperion imagery, the only source of spaceborne hyperspectral data, has a coarse resolution (30 m), but it is free of charge. Moreover, Hyperion's large number of channels may increase the detection capability of subpixel size targets. Until now, however, little research has been found that identified opium fields from spaceborne or aerial hyperspectral images. Therefore, this study attempts to detect opium fields from a Hyperion image covering a study area in Southwest Afghanistan in a situation where training samples were not available. A proposed methodology based on unsupervised endmember-selection and multiple-endmember spectral mixture analysis can detect opium fields directly from the Hyperion image. The number of poppy pixels was overestimated by 12%.

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O objetivo do estudo foi avaliar a eficácia anti-hipertensiva e o perfil de tolerabilidade em um período médio de 12 semanas, após duas semanas de washout, da combinação fixa de anlodipino e losartana em uma mesma forma galênica, em 116 pacientes hipertensos estágio 1. As visitas clínicas foram realizadas a cada quatro semanas com avaliação da pressão arterial na posição supina e ortostática, a freqüência cardíaca, o volume das pernas e a presença de eventos adversos. A eficácia anti-hipertensiva da combinação em estudo já estava significativamente presente nas primeiras quatro semanas de tratamento e se manteve por todo o período não se observando escapes do controle pressórico. Um total de 47,16% dos pacientes atingiu a meta de controle da pressão, na menor dose diária (anlodipino 5 mg/ losartana 50 mg) da combinação fixa. Com o uso de dois comprimidos ao dia, a taxa de controle aumentou para 83,3%. Observamos um aumento no volume das pernas ao final da 12ª semana de tratamento, que foi mais expressivo no grupo que usou a maior dose da combinação anlodipino 10 mg/ losartana 100 mg dia. Houve baixa incidência de eventos adversos, sendo a cefaléia e tontura os mais relatados. Pode-se concluir que a combinação fixa de anlodipino e losartana em uma mesma forma galênica apresenta alta taxa de eficácia, determina um pequeno número de eventos adversos e se constitui em excelente opção terapêutica anti-hipertensiva, permitindo a redução da pressão arterial diastólica e sistólica atualmente preconizada pelas diretrizes de tratamento da hipertensão arterial.