Canopy structural attributes derived from AVIRIS imaging spectroscopy data in a mixed broadleaf/conifer forest

There is a well-established need within the remote sensing community for improved estimation and understanding of canopy structure and its influence on the retrieval of leaf biochemical properties. The main goal of this research was to assess the potential of optical spectral information from NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) to discriminate different canopy structural types. In the first phase, we assessed the relationships between optical metrics and canopy structural parameters obtained from LiDAR in terms of different canopy structural attributes (biomass (i.e., area under Vegetation Vertical Profile, VVPint), canopy height and vegetation complexity). Secondly, we identified and classified different âcanopy structural typesâ by integrating several structural traits using Random Forests (RF). The study area is a heterogeneous forest in Sierra National Forest in California (USA). AVIRIS optical properties were analyzed by means of several sets of variables, including single narrow band reflectance and 1st derivative, sub-pixel cover fractions, narrow-band indices, spectral absorption features, optimized normalized difference indices and Principal Component Analysis (PCA) components. Our results demonstrate that optical data contain structural information that can be retrieved. The first principal component, used as a proxy for albedo, was the most strongly correlated optical metric with vegetation complexity, and it also correlated well with biomass (VVPint) and height. In conifer forests, the shade fraction was especially correlated to vegetation complexity, while water-sensitive optical metrics had high correlations with biomass (VVPint). Single spectral band analysis results showed that correlations differ in magnitude and in direction, across the spectrum and by vegetation type and structural variable. This research illustrates the potential of AVIRIS to analyze canopy structure and to distinguish several structural types in a heterogeneous forest. Furthermore, RF using optical metrics derived from AVIRIS proved to be a powerful technique to generate maps of structural attributes. The results emphasize the importance of using the whole optical spectrum, since all spectral regions contributed to canopy structure assessment

Canopy structural attributes derived from AVIRIS imaging spectroscopy data in a mixed broadleaf/conifer forest

There is a well-established need within the remote sensing community for improved estimation and understanding of canopy structure and its influence on the retrieval of leaf biochemical properties. The main goal of this research was to assess the potential of optical spectral information from NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) to discriminate different canopy structural types. In the first phase, we assessed the relationships between optical metrics and canopy structural parameters obtained from LiDAR in terms of different canopy structural attributes (biomass (i.e., area under Vegetation Vertical Profile, VVPint), canopy height and vegetation complexity). Secondly, we identified and classified different âcanopy structural typesâ by integrating several structural traits using Random Forests (RF). The study area is a heterogeneous forest in Sierra National Forest in California (USA). AVIRIS optical properties were analyzed by means of several sets of variables, including single narrow band reflectance and 1st derivative, sub-pixel cover fractions, narrow-band indices, spectral absorption features, optimized normalized difference indices and Principal Component Analysis (PCA) components. Our results demonstrate that optical data contain structural information that can be retrieved. The first principal component, used as a proxy for albedo, was the most strongly correlated optical metric with vegetation complexity, and it also correlated well with biomass (VVPint) and height. In conifer forests, the shade fraction was especially correlated to vegetation complexity, while water-sensitive optical metrics had high correlations with biomass (VVPint). Single spectral band analysis results showed that correlations differ in magnitude and in direction, across the spectrum and by vegetation type and structural variable. This research illustrates the potential of AVIRIS to analyze canopy structure and to distinguish several structural types in a heterogeneous forest. Furthermore, RF using optical metrics derived from AVIRIS proved to be a powerful technique to generate maps of structural attributes. The results emphasize the importance of using the whole optical spectrum, since all spectral regions contributed to canopy structure assessment

Mortalidad en lista de espera de trasplante renal en la era COVID: ¿pausar actividad de trasplante?

Introducción: El trasplante renal es el tratamiento de elección de la enfermedad renal en etapa terminal (ERT). Desde marzo de 2020, la actividad de trasplantes en México se ha visto afectada debido a la pandemia de COVID-19. Objetivo: Determinar el impacto en la mortalidad de pacientes en lista de espera (LE) para trasplante renal de donante cadavérico en un hospital de referencia en Yucatán, por suspensión de actividades debido a la pandemia. Material y métodos: Pacientes > 18 años en LE para trasplante renal en este hospital. En caso de muerte de un paciente, se investigó la causa, especialmente si estaba asociada a COVID-19. Un valor de p de dos colas ≤ 0.05 se consideró significativo en todos los análisis. Resultados: La razón de probabilidad de muerte por COVID-19 en un paciente con ERT en la LE en 2020 fue OR = 5.04 (IC 95%: 1.65-7.14, p = 0.023). La razón de probabilidad de morir con ERT en la LE con retraso en las consultas de seguimiento fue de OR = 6.59 (IC 95%: 2.7-16.28, p = 0.008). Conclusión: La probabilidad de muerte de un paciente con ERT en la LE con retraso en las consultas de seguimiento y retención del trasplante es estadísticamente más alta que la probabilidad de muerte por COVID-19

Burden and centralised treatment in Europe of rare tumours: results of RARECAREnet - a population-based study

Background Rare cancers pose challenges for diagnosis, treatments, and clinical decision making. Information about rare cancers is scant. The RARECARE project defined rare cancers as those with an annual incidence of less than six per 100 000 people in European Union (EU). We updated the estimates of the burden of rare cancers in Europe, their time trends in incidence and survival, and provide information about centralisation of treatments in seven European countries. Methods We analysed data from 94 cancer registries for more than 2 million rare cancer diagnoses, to estimate European incidence and survival in 2000–07 and the corresponding time trends during 1995–2007. Incidence was calculated as the number of new cases divided by the corresponding total person-years in the population. 5-year relative survival was calculated by the Ederer-2 method. Seven registries (Belgium, Bulgaria, Finland, Ireland, the Netherlands, Slovenia, and the Navarra region in Spain) provided additional data for hospitals treating about 220 000 cases diagnosed in 2000–07. We also calculated hospital volume admission as the number of treatments provided by each hospital rare cancer group sharing the same referral pattern. Findings Rare cancers accounted for 24% of all cancers diagnosed in the EU during 2000–07. The overall incidence rose annually by 0.5% (99·8% CI 0·3–0·8). 5-year relative survival for all rare cancers was 48·5% (95% CI 48·4 to 48·6), compared with 63·4% (95% CI 63·3 to 63·4) for all common cancers. 5-year relative survival increased (overall 2·9%, 95% CI 2·7 to 3·2), from 1999–2001 to 2007–09, and for most rare cancers, with the largest increases for haematological tumours and sarcomas. The amount of centralisation of rare cancer treatment varied widely between cancers and between countries. The Netherlands and Slovenia had the highest treatment volumes. Interpretation Our study benefits from the largest pool of population-based registries to estimate incidence and survival of about 200 rare cancers. Incidence trends can be explained by changes in known risk factors, improved diagnosis, and registration problems. Survival could be improved by early diagnosis, new treatments, and improved case management. The centralisation of treatment could be improved in the seven European countries we studied. Funding The European Commission (Chafea)

The EUROCARE-5 study on cancer survival in Europe 1999-2007: Database, quality checks and statistical analysis methods

Background Since 25 years the EUROCARE study monitors the survival of cancer patients in Europe through centralised collection, quality check and statistical analysis of population-based cancer registries (CRs) data. The European population covered by the study increased remarkably in the latest round. The study design and statistical methods were also changed to improve timeliness and comparability of survival estimates. To interpret the EUROCARE-5 results on adult cancer patients better here we assess the impact of these changes on data quality and on survival comparisons. Methods In EUROCARE-5 the survival differences by area were studied applying the complete cohort approach to data on nearly nine million cancer patients diagnosed in 2000-2007 and followed up to 2008. Survival time trends were analysed applying the period approach to data on about 10 million cancer cases diagnosed from 1995 to 2007 and followed up to 2008. Differently from EUROCARE-4, multiple primary cancers were included and relative survival was estimated with the Ederer II method. Results EUROCARE-5 covered a population of 232 million resident persons, corresponding to 50% of the 29 participating countries. The population coverage increased particularly in Eastern Europe. Cases identified from death certificate only (DCO) were on average 2.9%, range 0-12%. Microscopically confirmed cases amounted to over 85% in most CRs. Compared to previous methods, including multiple cancers and using the Ederer II estimator reduced survival estimates by 0.4 and 0.3 absolute percentage points, on average. Conclusions The increased population size and registration coverage of the EUROCARE-5 study ensures more robust and comparable estimates across European countries. This enlargement did not impact on data quality, which was generally satisfactory. Estimates may be slightly inflated in countries with high or null DCO proportions, especially for poor prognosis cancers. The updated methods improved the comparability of survival estimates between recently and long-term established registries and reduced biases due to informative censoring