A One Year Landsat 8 Conterminous United States Study of Cirrus and Non-Cirrus Clouds

The first year of available Landsat 8 data over the conterminous United States (CONUS), composed of 11,296 acquisitions sensed over more than 11 thousand million 30 m pixel locations, was analyzed comparing the spatial and temporal incidence of 30 m cloud and cirrus states available in the standard Landsat 8 Level 1 product suite. This comprehensive data analysis revealed that on average over a year of CONUS observations (i) 35.9% were detected with high confidence cloud, with spatio-temporal patterns similar to those observed by previous Landsat 5 and 7 cloud analyses; (ii) 28.2% were high confidence cirrus; (iii) 20.1% were both high confidence cloud and high confidence cirrus; and (iv) 6.9% were detected as high confidence cirrus but low confidence cloud. The results illustrate the potential of the 30 m cloud and cirrus states available in the standard Landsat 8 Level 1 product suite but imply that the historical CONUS Landsat archive has about 7% of undetected cirrus contaminated pixels. Systematic cloud detection commission errors over a minority of highly reflective exposed soil/sand surfaces were found and it is recommended that caution be taken when using the currently available Landsat 8 cloud data over similar surfaces

The Global Availability of Landsat 5 TM and Landsat 7 ETM+ Land Surface Observations and Implications for Global 30m Landsat Data Product Generation

With the advent of the free U.S. Landsat data policy it is now feasible to consider the generation of global coverage 30 m Landsat data sets with temporal reporting frequency similar to that provided by the monthly Web Enabled Landsat (WELD) products. A statistical Landsat metadata analysis is reported considering more than 800,000 Landsat 5 TM and Landsat 7 ETM + acquisitions obtained from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center archive. The global monthly probabilities of acquiring a cloud-free land surface observation for December 1998 to November 2001 (2000 epoch) and from December 2008 to November 2011 (2010 epoch) are reported to assess the availability of the Landsat data in the USGS Landsat archive for global multi-temporal land remote sensing applications. The global probabilities of acquiring a cloud-free land surface observation in each of three different seasons with the highest seasonal probabilities of cloud-free land surface observation are reported, considering one, two and three years of Landsat data, to assess the availability of Landsat data for global land cover mapping. The probabilities are derived considering Landsat 5 TM only, Landsat 7 ETM + only, and both sensors combined, to examine the relative benefits of using one or both Landsat sensors. The results demonstrate the utility of combing both Landsat 5 TM and Landsat 7 ETM + data streams to take advantage of their different acquisition patterns and to mitigate the deleterious impact of the Landsat 7 ETM + 2003 scan line failure. Sensor combination provided a greater global acquisition coverage with a 1.7% to 14.4% higher percentage of land locations acquired monthly compared to considering Landsat 7 ETM + data alone. The mean global monthly probability of a cloud-free land surface observation for the combined sensors was up to nearly 1.4 and 6.7 times greater than for ETM + and TM alone respectively. The probability of acquiring a cloud-free Landsat land surface observation in different seasons was greater when more years of data were considered and when both Landsat sensor data were combined. Considering combined sensors and 36 months of data, 86.4% and 84.2% of the global land locations had probabilities ≥ 0.95 for the 2000 and 2010 epochs respectively, with a global mean probability of 0.92 (σ 0.24) for the 2000 epoch and 0.90 (σ 0.28) for the 2010 epoch. These results indicate that 36 months of combined Landsat sensor data will provide sufficient land surface observations for 30 m global land cover mapping using a multi-temporal supervised classification scheme

Alternative Methods to Predict Actual Evapotranspiration Illustrate the Importance of Accounting for Phenology: The Event Driven Phenology Model Part II

Evapotranspiration (ET) flux constitutes a major component of both the water and energy balances at the land surface. Among the many factors that control evapotranspiration, phenology poses a major source of uncertainty in attempts to predict ET. Contemporary approaches to ET modeling and monitoring frequently summarize the complexity of the seasonal development of vegetation cover into static phenological trajectories (or climatologies) that lack sensitivity to changing environmental conditions. The Event Driven Phenology Model (EDPM) offers an alternative, interactive approach to representing phenology. This study presents the results of an experiment designed to illustrate the differences in ET arising from various techniques used to mimic phenology in models of land surface processes. The experiment compares and contrasts two realizations of static phenologies derived from long-term satellite observations of the Normalized Difference Vegetation Index (NDVI) against canopy trajectories produced by the interactive EDPM trained on flux tower observations. The assessment was carried out through validation of predicted ET against records collected by flux tower instruments. The VegET model (Senay, 2008) was used as a framework to estimate daily actual evapotranspiration and supplied with seasonal canopy trajectories produced by the EDPM and traditional techniques. The interactive approach presented the following advantages over phenology modeled with static climatologies: (a) lower prediction bias in crops; (b) smaller root mean square error in daily ET – 0.5 mm per day on average; (c) stable level of errors throughout the season similar among different land cover types and locations; and (d) better estimation of season duration and total seasonal ET

A New Concept for Simulation of Vegetated Land Surface Dynamics: The Event Driven Phenology Model Part I

Phenologies of the vegetated land surface are being used increasingly for diagnosis and prognosis of climate change consequences. Current prospective and retrospective phenological models stand far apart in their approaches to the subject. We report on an exploratory attempt to implement a phenological model based on a new event driven concept which has both diagnostic and prognostic capabilities in the same modeling framework. This Event Driven Phenological Model (EDPM) is shown to simulate land surface phenologies and phenophase transition dates in agricultural landscapes based on assimilation of weather data and land surface observations from spaceborne sensors. The model enables growing season phenologies to develop in response to changing environmental conditions and disturbance events. It also has the ability to ingest remotely sensed data to adjust its output to improve representation of the modeled variable. We describe the model and report results of initial testing of the EDPM using Level 2 flux tower records from the Ameri- flux sites at Mead, Nebraska, USA, and at Bondville, Illinois, USA. Simulating the dynamics of normalized difference vegetation index based on flux tower data, the predictions by the EDPM show good agreement (RMSE0.8) for maize and soybean during several growing seasons at different locations. This study presents the EDPM used in the companion paper (Kovalskyy and Henebry, 2011) in a coupling scheme to estimate daily actual evapotranspiration over multiple growing seasons

Change and Persistence in Land Surface Phenologies of the Don and Dnieper River Basins

The formal collapse of the Soviet Union at the end of 1991 produced major socio-economic and institutional dislocations across the agricultural sector. The picture of broad scale patterns produced by these transformations continues to be discovered. We examine here the patterns of land surface phenology (LSP) within two key river basins—Don and Dnieper—using AVHRR (Advanced Very High Resolution Radiometer) data from 1982 to 2000 and MODIS (Moderate Resolution Imaging Spectroradiometer) data from 2001 to 2007. We report on the temporal persistence and change of LSPs as summarized by seasonal integration of NDVI (normalized difference vegetation index) time series using accumulated growing degree-days (GDDI NDVI). Three land cover super-classes—forest lands, agricultural lands, and shrub lands—constitute 96% of the land area within the basins. All three in both basins exhibit unidirectional increases in AVHRR GDDI NDVI between the Soviet and post-Soviet epochs. During the MODIS era (2001–2007), different socio-economic trajectories in Ukraine and Russia appear to have led to divergences in the LSPs of the agricultural lands in the two basins. Interannual variation in the shrub lands of the Don river basin has increased since 2000. This is due in part to the better signal-to-noise ratio of the MODIS sensor, but may also be due to a regional drought affecting the Don basin more than the Dnieper basin

Alternative methods to predict actual evapotranspiration illustrate the importance of accounting for phenology – Part 2: The event driven phenology model

Evapotranspiration (ET) flux constitutes a major component of both the water and energy balances at the land surface. Among the many factors that control evapotranspiration, phenology poses a major source of uncertainty in attempts to predict ET. Contemporary approaches to ET modeling and monitoring frequently summarize the complexity of the seasonal development of vegetation cover into static phenological trajectories (or climatologies) that lack sensitivity to changing environmental conditions. The Event Driven Phenology Model (EDPM) offers an alternative, interactive approach to representing phenology. This study presents the results of an experiment designed to illustrate the differences in ET arising from various techniques used to mimic phenology in models of land surface processes. The experiment compares and contrasts two realizations of static phenologies derived from long-term satellite observations of the Normalized Difference Vegetation Index (NDVI) against canopy trajectories produced by the interactive EDPM trained on flux tower observations. The assessment was carried out through validation of predicted ET against records collected by flux tower instruments. The VegET model (Senay, 2008) was used as a framework to estimate daily actual evapotranspiration and supplied with seasonal canopy trajectories produced by the EDPM and traditional techniques. The interactive approach presented the following advantages over phenology modeled with static climatologies: (a) lower prediction bias in crops; (b) smaller root mean square error in daily ET – 0.5 mm per day on average; (c) stable level of errors throughout the season similar among different land cover types and locations; and (d) better estimation of season duration and total seasonal ET

Geometric filters for protein–ligand complexes based on phenomenological molecular models

Molecular docking is a widely used method of computer-aided drug design capable of accurate prediction of protein-ligand complex conformations. However, scoring functions used to estimate free energy of binding still lack accuracy. Aim. Development of computationally simple and rapid algorithms for ranking ligands based on docking results. Methods. Computational filters utilizing geometry of protein-ligand complex were designed. Efficiency of the filters was verified in a cross-docking study with QXP/Flo software using crystal structures of human serine proteases thrombin (F2) and factor Xa (F10) and two corresponding sets of known selective inhibitors. Results. Evaluation of filtering results in terms of ROC curves with varying filter threshold value has shown their efficiency. However, none of the filters outperformed QXP/Flo built-in scoring function Pi . Nevertheless, usage of the filters with optimized set of thresholds in combination with Pi achieved significant improvement in performance of ligand selection when compared to usage of Pi alone. Conclusions. The proposed geometric filters can be used as a complementary to traditional scoring functions in order to optimize ligand search performance and decrease usage of computational and human resources.Молекулярний докінг є широко застосовуваним обчислювальним методом пошуку лігандів біомолекул, здатним до достатньо точного передбачення конформацій комплексів білок–ліганд. У той же час скоринговим функціям, що використовують для оцінки сили зв’язування, бракує точності. Мета. Розробка обчислювально простих та швидких алгоритмів для вибору потенційних лігандів з комплексів, отриманих у результаті докінгу. Методи. Створено обчислювальні фільтри, засновані на геометричних співвідношеннях у комплексі білок–ліганд, ефективність яких перевірено крос-докінговим дослідженням із застосуванням кристалічних структур людських серинових протеаз тромбіна (F2) і фактора 10а (F10), а також двох відповідних наборів відомих селективних інгібіторів за допомогою програмного забезпечення QXP/Flo. Результати. Оцінено результати застосування фільтрів у термінах ROC-кривих із змінними пороговими значеннями та показано їхню ефективність. Проте жоден з фільтрів не перевершив за ефективністю вбудовану скорингову функцію Pi програми QXP/ Flo. Тим не менш, використання фільтрів з оптимізованими пороговими значеннями у комбінації з Pi дозволило значно збільшити ефективність порівняно із застосуванням лише Pi. Висновки. Розроблені геометричні фільтри можуть слугувати доповненням до традиційних скорингових функцій для оптимізації пошуку лігандів і зменшення залучення обчислювальних та люд- ських ресурсів.Молекулярный докинг – широко используемый вычислительный метод поиска лигандов биомолекул, способный довольно точно предсказывать конформацию комплекса белок–лиганд. В то же время скоринговые функции, используемые для оценки силы связывания, недостаточно точны. Цель. Разработка вычислительно простых и быстрых алгоритмов для выбора потенциальных лигандов из комплексов, полученных в результате докинга. Методы. Созданы вычислительные фильтры на основе геометрических соотношений в комплексе белок–лиганд, эффективность которых проверена кросс-докинговым исследованием c применением кристаллических структур человеческих сериновых протеаз тромбина (F2) и фактора 10а (F10), а также двух соответствующих наборов известных селективных ингибиторов с помощью программного обеспечения QXP/Flo. Результаты. Оценены результаты применения фильтров в терминах ROC-кривых с переменными пороговыми значениями и показана их эффективность. Однако ни один из фильтров не превзошел по эффективности встроенную скоринговую функцию Pi программы QXP/Flo. Тем не менее, использование фильтров с оптимизированными пороговыми значениями в комбинации с Pi позволило существенно увеличить эффективность в сравнении с применением только Pi. Выводы. Разработанные геометрические фильтры могут служить дополнением к традиционным скоринговым функциям для оптимизации поиска лигандов и уменьшения привлечения вычислительных и человеческих ресурсов

Evaluation of the Event Driven Phenology Model Coupled with the VegET Evapotranspiration Model Through Comparisons with Reference Datasets in a Spatially Explicit Manner

A new model coupling scheme with remote sensing data assimilation was developed for estimation of daily actual evapotranspiration (ET). The scheme represents a mix of the VegET, a physically based model to estimate ET from a water balance, and an event driven phenology model (EDPM), where the EDPM is an empirically derived crop specific model capable of producing seasonal trajectories of canopy attributes. In this experiment, the scheme was deployed in a spatially explicit manner within the croplands of the Northern Great Plains. The evaluation was carried out using 2007-2009 land surface forcing data from the North American Land Data Assimilation System (NLDAS) and crop maps derived from remotely sensed data of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compared the canopy parameters produced by the phenology model with normalized difference vegetation index (NDVI) data derived from the MODIS nadir bi-directional reflectance distribution function (BRDF) adjusted reflectance (NBAR) product. The expectations of the EDPM performance in prognostic mode were met, producing determination coefficient (r2) of 0.8 +/-.0.15. Model estimates of NDVI yielded root mean square error (RMSE) of 0.1 +/-.0.035 for the entire study area. Retrospective correction of canopy dynamics with MODIS NDVI brought the errors down to just below 10% of observed data range. The ET estimates produced by the coupled scheme were compared with ones from the MODIS land product suite. The expected r2=0.7 +/-.15 and RMSE = 11.2 +/-.4 mm per 8 days were met and even exceeded by the coupling scheme0 functioning in both prognostic and retrospective modes. Minor setbacks of the EDPM and VegET performance (r2 about 0.5 and additional 30 % of RMSR) were found on the peripheries of the study area and attributed to the insufficient EDPM training and to spatially varying accuracy of crop maps. Overall the experiment provided sufficient evidence of soundness and robustness of the EDPM and VegET coupling scheme, assuring its potential for spatially explicit applications

Identification of novel small molecule inhibitors of adenovirus gene transfer using a high throughput screening approach

Due to many favourable attributes adenoviruses (Ads) are the most extensively used vectors for clinical gene therapy applications. However, following intravascular administration, the safety and efficacy of Ad vectors are hampered by the strong hepatic tropism and induction of a potent immune response. Such effects are determined by a range of complex interactions including those with neutralising antibodies, blood cells and factors, as well as binding to native cellular receptors (coxsackie adenovirus receptor (CAR), integrins). Once in the bloodstream, coagulation factor X (FX) has a pivotal role in determining Ad liver transduction and viral immune recognition. Due to difficulties in generating a vector devoid of multiple receptor binding motifs, we hypothesised that a small molecule inhibitor would be of value. Here, a pharmacological approach was implemented to block adenovirus transduction pathways. We developed a high throughput screening (HTS) platform to identify the small molecule inhibitors of FX-mediated Ad5 gene transfer. Using an in vitro fluorescence and cell-based HTS, we evaluated 10,240 small molecules. Following sequential rounds of screening, three compounds, T5424837, T5550585 and T5660138 were identified that ablated FX-mediated Ad5 transduction with low micromolar potency. The candidate molecules possessed common structural features and formed part of the one pharmacophore model. Focused, mini-libraries were generated with structurally related molecules and in vitro screening revealed novel hits with similar or improved efficacy. The compounds did not interfere with Ad5:FX engagement but acted at a subsequent step by blocking efficient intracellular transport of the virus. In vivo, T5660138 and its closely related analogue T5660136 significantly reduced Ad5 liver transgene expression at 48 h post-intravenous administration of a high viral dose (1 × 10<sup>11</sup> vp/mouse). Therefore, this study identifies novel and potent small molecule inhibitors of the Ad5 transduction which may have applications in the Ad gene therapy setting

Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)

Forest cover loss and bare ground gain from 2006 to 2010 for the conterminous United States (CONUS) were quantified at a 30 m spatial resolution using Web-Enabled Landsat Data available from the USGS Center for Earth Resources Observation and Science (EROS) (http://landsat.usgs.gov/WELD.php). The approach related multi-temporal WELD metrics and expert-derived training data for forest cover loss and bare ground gain through a decision tree classification algorithm. Forest cover loss was reported at state and ecoregional scales, and the identification of core forests\u27 absent of change was made and verified using LiDAR data from the GLAS (Geoscience Laser Altimetry System) instrument. Bare ground gain correlated with population change for large metropolitan statistical areas (MSAs) outside of desert or semi-desert environments. Google Earth™ time series images were used to validate the products. Mapped forest cover loss totaled 53,084 km2 and was found to be depicted conservatively, with a user\u27s accuracy of 78% and a producer\u27s accuracy of 68%. Excluding errors of adjacency, user\u27s and producer\u27s accuracies rose to 93% and 89%, respectively. Mapped bare ground gain equaled 5974 km2 and nearly matched the estimated area from the reference (Google Earth™) classification; however, user\u27s (42%) and producer\u27s (49%) accuracies were much less than those of the forest cover loss product. Excluding errors of adjacency, user\u27s and producer\u27s accuracies rose to 62% and 75%, respectively. Compared to recent 2001–2006 USGS National Land Cover Database validation data for forest loss (82% and 30% for respective user\u27s and producer\u27s accuracies) and urban gain (72% and 18% for respective user\u27s and producer\u27s accuracies), results using a single CONUS-scale model with WELD data are promising and point to the potential for national scale operational mapping of key land cover transitions. However, validation results highlighted limitations, some of which can be addressed by improving training data, creating a more robust image feature space, adding contemporaneous Landsat 5 data to the inputs, and modifying definition sets to account for differences in temporal and spatial observational scales. The presented land cover extent and change data are available via the official WELD website (ftp://weldftp.cr.usgs.gov/CONUS_5Y_LandCover/ftp://weldftp.cr.usgs. gov/CONUS_5Y_LandCover/)