Retrieval of Seasonal Leaf Area Index from Simulated EnMAP Data through Optimized LUT-Based Inversion of the PROSAIL Model

The upcoming satellite mission EnMAP offers the opportunity to retrieve information on the seasonal development of vegetation parameters on a regional scale based on hyperspectral data. This study aims to investigate whether an analysis method for the retrieval of leaf area index (LAI),developed and validated on the 4 m resolution scale of six airborne datasets covering the 2012 growing period, is transferable to the spaceborne 30 m resolution scale of the future EnMAP mission. The widely used PROSAIL model is applied to generate look-up-table (LUT) libraries, by which the model is inverted to derive LAI information. With the goal of defining the impact of different selection criteria in the inversion process, different techniques for the LUT based inversion are tested, such as several cost functions, type and amount of artificial noise, number of considered solutions and type of averaging method. The optimal inversion procedure (Laplace, median, 4% inverse multiplicative noise, 350 out of 100, 000 averages) is identified by validating the results against corresponding in-situ measurements (n = 330) of LAI. Finally, the best performing LUT inversion (R-2 = 0.65, RMSE = 0.64) is adapted to simulated EnMAP data, generated from the airborne acquisitions. The comparison of the retrieval results to upscaled maps of LAI, previously validated on the 4 m scale, shows that the optimized retrieval method can successfully be transferred to spaceborne EnMAP data

Retrieval of Seasonal Leaf Area Index from Simulated EnMAP Data through Optimized LUT-Based Inversion of the PROSAIL Model

The upcoming satellite mission EnMAP offers the opportunity to retrieve information on the seasonal development of vegetation parameters on a regional scale based on hyperspectral data. This study aims to investigate whether an analysis method for the retrieval of leaf area index (LAI),developed and validated on the 4 m resolution scale of six airborne datasets covering the 2012 growing period, is transferable to the spaceborne 30 m resolution scale of the future EnMAP mission. The widely used PROSAIL model is applied to generate look-up-table (LUT) libraries, by which the model is inverted to derive LAI information. With the goal of defining the impact of different selection criteria in the inversion process, different techniques for the LUT based inversion are tested, such as several cost functions, type and amount of artificial noise, number of considered solutions and type of averaging method. The optimal inversion procedure (Laplace, median, 4% inverse multiplicative noise, 350 out of 100, 000 averages) is identified by validating the results against corresponding in-situ measurements (n = 330) of LAI. Finally, the best performing LUT inversion (R-2 = 0.65, RMSE = 0.64) is adapted to simulated EnMAP data, generated from the airborne acquisitions. The comparison of the retrieval results to upscaled maps of LAI, previously validated on the 4 m scale, shows that the optimized retrieval method can successfully be transferred to spaceborne EnMAP data

Формирование ударного импульса в зависимости от исполнения промежуточной полости пневмогидравлического ударного узла

С использованием математического моделирования изучено влияние параметров среды промежуточной полости формирователя пневмогидравлического ударного узла на форму и длительность ударного импульса. Показано как, изменяя параметры и конструктивное исполнение формирователя и промежуточной полости, можно увеличивать эффективность удара

Postoperative CD4 counts predict anastomotic leaks in patients with penetrating abdominal trauma

INTRODUCTION : The influence of trauma- and surgical stress-induced decrease of CD4 count on anastomotic leaks after penetrating abdominal trauma has to date not been investigated. A prospective study was performed to explore the effect of CD4 count 24 h after surgery on the anastomotic leak rate and to identify risk factors for anastomotic leaks. METHODS : This was a prospective study including 98 patients with small or large bowel resection and subsequent anastomosis due to penetrating abdominal trauma. Univariate analysis identified risk factors for the development of anastomotic leak and also investigated the predictive value of the CD4 count for this complication. RESULTS : Of the 98 patients 23 patients (23%) were HIV-infected. The overall leak rate was 13%. Univariate analysis including all potential risk factors with p-values6units and delayed anastomosis after damage control surgery. Survival rates were analysed with the χ2 test and did not show a significantly higher mortality rate in patients with low CD4 count. The negative impact of trauma and subsequent surgery on the cell mediated immunity was demonstrated by the fact that 55 (73%) of the HIV-negative patients had a CD4 count less than 500 cells/μl 24 h postoperatively. HIV-infection had no significant influence on the leak rate, however all HIV infected patients that developed an anastomotic leak died. CONCLUSION : A low post-operative CD4 count is a predictor for anastomotic leaks irrespective of HIV-serostatus. Low postoperative serum albumin, high injury severity, gunshot wound as mechanism of injury, blood transfusion requirement >6 units and delayed anastomosis were further risk factors for anastomotic complications. Postoperative CD4 count and serum albumin should be considered in the decision making process of performing an anastomosis or diverting stoma for patients after “clip and drop” of the bowel as part of damage control surgery.http://www.elsevier.com/ /locate/injury2019-11-16hj2018Surger

Transdisciplinary global change research: the co-creation of knowledge for sustainability

The challenges formulated within the Future Earth framework set the orientation for research programmes in sustainability science for the next ten years. Scientific disciplines from natural and social science will collaborate both among each other and with relevant societal groups in order to define the important integrated research questions, and to explore together successful pathways towards global sustainability. Such collaboration will be based on transdisciplinarity and integrated research concepts. This paper analyses the relationship between scientific integration and transdisciplinarity, discusses the dimensions of integration of different knowledge and proposes a platform and a paradigm for research towards global sustainability that will be both designed and conducted in partnership between science and society. We argue that integration is an iterative process that involves reflection among all stakeholders. It consists of three stages: co-design, co-production and co-dissemination

Physically-Based Retrieval of Canopy Equivalent Water Thickness Using Hyperspectral Data

Quantitative equivalent water thickness on canopy level (EWTcanopy) is an important land surface variable and retrieving EWTcanopy from remote sensing has been targeted by many studies. However, the effect of radiative penetration into the canopy has not been fully understood. Therefore, in this study the Beer-Lambert law is applied to inversely determine water content information in the 930 to 1060 nm range of canopy reflectance from measured winter wheat and corn spectra collected in 2015, 2017, and 2018. The spectral model was calibrated using a look-up-table (LUT) of 50,000 PROSPECT spectra. Internal model validation was performed using two leaf optical properties datasets (LOPEX93 and ANGERS). Destructive in-situ measurements of water content were collected separately for leaves, stalks, and fruits. Correlation between measured and modelled water content was most promising for leaves and ears in case of wheat, reaching coefficients of determination (R-2) up to 0.72 and relative RMSE (rRMSE) of 26% and in case of corn for the leaf fraction only (R-2 = 0.86, rRMSE = 23%). These findings indicate that, depending on the crop type and its structure, different parts of the canopy are observed by optical sensors. The results from the Munich-North-Isar test sites indicated that plant compartment specific EWTcanopy allows us to deduce more information about the physical meaning of model results than from equivalent water thickness on leaf level (EWT) which is upscaled to canopy water content (CWC) by multiplication of the leaf area index (LAI). Therefore, it is suggested to collect EWTcanopy data and corresponding reflectance for different crop types over the entire growing cycle. Nevertheless, the calibrated model proved to be transferable in time and space and thus can be applied for fast and effective retrieval of EWTcanopy in the scope of future hyperspectral satellite missions

Retrieval of Biophysical Crop Variables from Multi-Angular Canopy Spectroscopy

The future German Environmental Mapping and Analysis Program (EnMAP) mission, due to launch in late 2019, will deliver high resolution hyperspectral data from space and will thus contribute to a better monitoring of the dynamic surface of the earth. Exploiting the satellite's +/- 30 degrees across-track pointing capabilities will allow for the collection of hyperspectral time-series of homogeneous quality. Various studies have shown the possibility to retrieve geo-biophysical plant variables, like leaf area index (LAI) or leaf chlorophyll content (LCC), from narrowband observations with fixed viewing geometry by inversion of radiative transfer models (RTM). In this study we assess the capability of the well-known PROSPECT 5B + 4SAIL (Scattering by Arbitrarily Inclined Leaves) RTM to estimate these variables from off-nadir observations obtained during a field campaign with respect to EnMAP-like sun-target-sensor-geometries. A novel approach for multiple inquiries of a large look-up-table (LUT) in hierarchical steps is introduced that accounts for the varying instances of all variables of interest. Results show that anisotropic effects are strongest for early growth stages of the winter wheat canopy which influences also the retrieval of the variables. RTM inversions from off-nadir spectra lead to a decreased accuracy for the retrieval of LAI with a relative root mean squared error (rRMSE) of 18% at nadir vs. 25% (backscatter) and 24% (forward scatter) at off-nadir. For LCC estimations, however, off-nadir observations yield improvements, i.e., rRMSE (nadir) = 24% vs. rRMSE (forward scatter) = 20%. It follows that for a variable retrieval through RTM inversion, the final user will benefit from EnMAP time-series for biophysical studies regardless of the acquisition angle and will thus be able to exploit the maximum revisit capability of the mission

Unconditional well-posedness and IMEX improvement of a family of predictor-corrector methods in micromagnetics

Recently, Kim & Wilkening (Convergence of a mass-lumped finite element method for the Landau-Lifshitz equation, Quart. Appl. Math., 76, 383-405, 2018) proposed two novel predictor-corrector methods for the Landau-Lifshitz-Gilbert equation (LLG) in micromagnetics, which models the dynamics of the magnetization in ferromagnetic materials. Both integrators are based on the so-called Landau-Lifshitz form of LLG, use mass-lumped variational formulations discretized by first-order finite elements, and only require the solution of linear systems, despite the nonlinearity of LLG. The first(-order in time) method combines a linear update with an explicit projection of an intermediate approximation onto the unit sphere in order to fulfill the LLG-inherent unit-length constraint at the discrete level. In the second(-order in time) integrator, the projection step is replaced by a linear constraint-preserving variational formulation. In this paper, we extend the analysis of the integrators by proving unconditional well-posedness and by establishing a close connection of the methods with other approaches available in the literature. Moreover, the new analysis also provides a well-posed integrator for the Schrödinger map equation (which is the limit case of LLG for vanishing damping). Finally, we design an implicit-explicit strategy for the treatment of the lower-order field contributions, which significantly reduces the computational cost of the schemes, while preserving their theoretical properties

Model-Based Optimization of Spectral Sampling for the Retrieval of Crop Variables with the PROSAIL Model

Satellite hyperspectral Earth observation missions have strong potential to support sustainable agriculture by providing accurate spatial and temporal information of important vegetation biophysical and biochemical variables. To meet this goal, possible error sources in the modelling approaches should be minimized. Thus, first of all, the capability of a model to reproduce the measured spectral signals has to be tested before applying any retrieval algorithm. For an exemplary demonstration, the coupled PROSPECT-D and SAIL radiative transfer models (PROSAIL) were employed to emulate the setup of future hyperspectral sensors in the visible and near-infrared (VNIR) spectral regions with a 6.5 nm spectral sampling distance. Model uncertainties were determined to subsequently exclude those wavelengths with the highest mean absolute error (MAE) between model simulation and spectral measurement. The largest mismatch could be found in the green visible and red edge regions, which can be explained by complex interactions of several biochemical and structural variables in these spectral domains. For leaf area index (LAI, m(2)m(-2)) retrieval, results indicated only a small improvement when using optimized spectral samplings. However, a significant increase in accuracy for leaf chlorophyll content (LCC, mu gcm(-2)) estimations could be obtained, with the relative root mean square error (RMSE) decreasing from 26% (full VNIR range) to 15% (optimized VNIR) for maize and from 77% to 29% for soybean, respectively. We therefore recommend applying a specific model-error threshold (MAE of similar to 0.01) to stabilize the retrieval of crop biochemical variables