Estimation of High-Resolution Evapotranspiration in Heterogeneous Environments Using Drone-Based Remote Sensing

Evapotranspiration (ET) is a key element of hydrological cycle analysis, irrigation demand, and for better allocation of water resources in the ecosystem. For successful water resources management activities, precise estimate of ET is necessary. Although several attempts have been made to achieve that, variation in temporal and spatial scales constitutes a major challenge, particularly in heterogeneous canopy environments such as vineyards, orchards, and natural areas. The advent of remote sensing information from different platforms, particularly the small unmanned aerial systems (sUAS) technology with lightweight sensors allows users to capture high-resolution data faster than traditional methods, described as “flexible in timing”. In this study, the Two Source Energy Balance Model (TSEB) along with high-resolution data from sUAS were used to bridge the gap in ET issues related to spatial and temporal scales. Over homogeneous vegetation surfaces, relatively low spatial resolution information derived from Landsat (e.g., 30 m) might be appropriate for ET estimate, which can capture differences between fields. However, in agricultural landscapes with presence of vegetation rows and interrows, the homogeneity is less likely to be met and the ideal conditions may be difficult to identify. For most agricultural settings, row spacing can vary within a field (vineyards and orchards), making the agricultural landscape less homogenous. This leads to a key question related to how the contextual spatial domain/model grid size could influence the estimation of surface fluxes in canopy environments such as vineyards. Furthermore, temporal upscaling of instantaneous ET at daily or longer time scales is of great practical importance in managing water resources. While remote sensing-based ET models are promising tools to estimate instantaneous ET, additional models are needed to scale up the estimated or modeled instantaneous ET to daily values. Reliable and precise daily ET (ETd) estimation is essential for growers and water resources managers to understand the diurnal and seasonal variation in ET. In response to this issue, different existing extrapolation/upscaling daily ET (ETd) models were assessed using eddy covariance (EC) and sUAS measurements. On the other hand, ET estimation over semi-arid naturally vegetated regions becomes an issue due to high heterogeneity in such environments where vegetation tends to be randomly distributed over the land surface. This reflects the conditions of natural vegetation in river corridors. While significant efforts were made to estimate ET at agricultural landscapes, accurate spatial information of ET over riparian ecosystems is still challenging due to various species associated with variable amounts of bare soil and surface water. To achieve this, the TSEB model with high-resolution remote sensing data from sUAS were used to characterize the spatial heterogeneity and calculate the ET over a natural environment that features arid climate and various vegetation types at the San Rafael River corridor

A System Approach For Defining Data Center Value Proposition

Organizations invest heavily in IT infrastructure and the data center’s share of these investments is not marginal. Organizations face the challenge of justifying capital and operational spending on these facilities and often measuring the performance of data center is ignored. Performance measurements focus on analyzing the performance of servers and software applications rather than that of the impact of the data center on the organization. Various methods that have been currently used do not convey the actual value of the data center and do not provide accurate predications of its benefit and expected performance. This report introduces a method to define the value proposition of a data center using a set of metrics that provide measures for a number of variables that define the behavior and outcomes of a data center. An analysis of the data center behavior and outcome will provide a system model from which stakeholder value can be defined

Investigating the Impact of Changing the Usage Type of Existing Structure Using BIM

Many real estate owners change the building in terms of the type of usage in response to changes in economic conditions and the requirements of the surrounding environment to get the best potential financial return. To investigate the possibilities of changing the real estate's usage, the owners of these existing structures turned to feasibility study experts for assistance in making the optimum alternatives. So, they need an integrated model between VE and BIM, especially applicable to an existing structure, to determine the optimum usage type for the existing structure. Value Engineering (VE) and Building Information Modeling (BIM) must be connected to profit from both outputs simultaneously. Previous studies only investigated the VE alternatives during the design phase; when they decided to reduce project costs by using construction materials alternatives, they ignored existing structure alternatives significantly when changing the usage type. This study attempts to provide an integrated model between VE and BIM that can be applied to the existing structure to assist in determining the best alternative in terms of the type of usage for such existing structures by conducting BIM methodology such as a feasibility study, including BIM software such as Revit and Primavera. A feasibility study that contains the bank rate of interest. As a result, the maximum financial return is obtained based on predetermined criteria and in compliance with decision-making requirements. Doi: 10.28991/CEJ-2022-08-08-06 Full Text: PD

Myomectomy for fibroids during cesarean section: A randomized controlled trial

Background: There is a considerable debate about the management of myoma during cesarean section (CS). Recently, several studies indicated the safety and feasibility of undertaking myomectomy during CS.Objectives: To evaluate the safety, accessibility, and short-term morbidity of myomectomy for fibroids during cesarean section.Patients and Methods: This was a randomized controlled trial that included 72 patients who were admitted to the Obstetrics & Gynecology Department, Menoufia University Hospital with uterine fibroids during pregnancy; who were randomly allocated equally into a group of cesarean myomectomy (CM; n=36) and another group of CS only (n=36). The operative events and the outcome were recorded and analyzed.Results: CM group showed a longer duration of surgery and longer hospital stay, higher amount of blood loss, and higher mean pain sores, with a highly statistically significant difference (p = 0.000). No cases in both groups required blood transfusion or ICU admission. No statistically significant differences were noted between both groups as regards the fetal outcome measures (p=0.583 & 0.601).Conclusion: CM is safe and applicable in selected cases without deleterious maternal complications. Special precautions ought to be paid during the procedure, particularly in the intramural type and with large fibroids

Implications of Sensor Inconsistencies and Remote Sensing Error in the Use of Small Unmanned Aerial Systems for Generation of Information Products for Agricultural Management

Small, unmanned aerial systems (sUAS) for remote sensing represent a relatively new and growing technology to support decisions for agricultural operations. The size and power limitations of these systems present challenges for the weight, size, and capability of the sensors that can be carried, as well as the geographical coverage that is possible. These factors, together with a lack of standards for sensor technology, its deployment, and data analysis, lead to uncertainties in data quality that can be difficult to detect or characterize. These, in turn, limit comparability between data from different sources and, more importantly, imply limits on the analyses that can be accomplished with the data that are acquired with sUAS. This paper offers a simple statistical examination of the implications toward information products of an array of sensor data uncertainty issues. The analysis relies upon high-resolution data collected in 2016 over a commercial vineyard, located near Lodi, California, for the USDA Agricultural Research Service Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) Program. A Monte Carlo analysis is offered of how uncertainty in sensor spectral response and/or orthorectification accuracy can affect the estimation of information products of potential interest to growers, as illustrated in the form of common vegetation indices

Optimising the outcomes of index admission laparoscopic cholecystectomy and bile duct exploration for biliary emergencies: a service model

Aims: The rate of acute laparoscopic cholecystectomy remains low due to operational constraints. The purpose of this study is to evaluate a service model of index admission cholecystectomy with referral protocols, refined logistics and targeted job planning. Methods: A prospectively maintained dataset was evaluated to determine the processes of care and outcomes of patients undergoing emergency biliary surgery. The lead author has maintained a 28 years prospective database capturing standard demographic data, intraoperative details including the difficulty of cholecystectomy as well as postoperative outcome parameters and follow up data. Results: Over five thousand (5555) consecutive laparoscopic cholecystectomies were performed. Only patients undergoing emergency procedures (2399,43.2% of entire group) were analysed for this study. The median age was 52 years with 70% being female. The majority were admitted with biliary pain (34%), obstructive jaundice (26%) and acute cholecystitis (16%). 63% were referred by other surgeons. 80% underwent surgery within 5 days (40% within 24 h). Cholecystectomies were performed on scheduled lists (44%) or dedicated emergency lists (29%). Two thirds had suspected bile duct stones and 38.1% underwent bile duct exploration. The median operating time was 75 min, median hospital stay 7 days, conversion rate 0.8%, morbidity 8.9% and mortality rate 0.2%. Conclusion: Index admission cholecystectomy for biliary emergencies can have low rates of morbidity and mortality. Timely referral and flexible theatre lists facilitate the service, optimising clinical results, number of biliary episodes, hospital stay and presentation to resolution intervals. Cost benefits and reduced interval readmissions need to be weighed against the length of hospital stay per episode

Estimation of Surface Thermal Emissivity in a Vineyard for UAV Microbolometer Thermal Cameras Using NASA HyTES Hyperspectral Thermal, and Landsat and AggieAir Optical Data

Microbolometer thermal cameras in UAVs and manned aircraft allow for the acquisition of highresolution temperature data, which, along with optical reflectance, contributes to monitoring and modeling of agricultural and natural environments. Furthermore, these temperature measurements have facilitated the development of advanced models of crop water stress and evapotranspiration in precision agriculture and heat fluxes exchanges in small river streams and corridors. Microbolometer cameras capture thermal information at blackbody or radiometric settings (narrowband emissivity equates to unity). While it is customary that the modeler uses assumed emissivity values (e.g. 0.99– 0.96 for agricultural and environmental settings); some applications (e.g. Vegetation Health Index), and complex models such as energy balance-based models (e.g. evapotranspiration) could benefit from spatial estimates of surface emissivity for true or kinetic temperature mapping. In that regard, this work presents an analysis of the spectral characteristics of a microbolometer camera with regard to emissivity, along with a methodology to infer thermal emissivity spatially based on the spectral characteristics of the microbolometer camera. For this work, the MODIS UCBS Emissivity Library, NASA HyTES hyperspectral emissivity, Landsat, and Utah State University AggieAir UAV surface reflectance products are employed. The methodology is applied to a commercial vineyard agricultural setting located in Lodi, California, where HyTES, Landsat, and AggieAir UAV spatial data were collected in the 2014 growing season. Assessment of the microbolometer spectral response with regards to emissivity and emissivity modeling performance for the area of study are presented and discussed

To What Extent Does the Eddy Covariance Footprint Cutoff Influence the Estimation of Surface Energy Fluxes Using Two Source Energy Balance Model and High-Resolution Imagery in Commercial Vineyards?

Validation of surface energy fluxes from remote sensing sources is performed using instantaneous field measurements obtained from eddy covariance (EC) instrumentation. An eddy covariance measurement is characterized by a footprint function / weighted area function that describes the mathematical relationship between the spatial distribution of surface flux sources and their corresponding magnitude. The orientation and size of each flux footprint / source area depends on the micro-meteorological conditions at the site as measured by the EC towers, including turbulence fluxes, friction velocity (ustar), and wind speed, all of which influence the dimensions and orientation of the footprint. The total statistical weight of the footprint is equal to unity. However, due to the large size of the source area / footprint, a statistical weight cutoff of less than one is considered, ranging between 0.85 and 0.95, to ensure that the footprint model is located inside the study area. This results in a degree of uncertainty when comparing the modeled fluxes from remote sensing energy models (i.e., TSEB2T) against the EC field measurements. In this research effort, the sensitivity of instantaneous and daily surface energy flux estimates to footprint weight cutoffs are evaluated using energy balance fluxes estimated with multispectral imagery acquired by AggieAir sUAS (small Unmanned Aerial Vehicle) over commercial vineyards near Lodi, California, as part of the ARS-USDA Agricultural Research Service’s Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) project. The instantaneous fluxes from the eddy covariance tower will be compared against instantaneous fluxes obtained from different TSEB2T aggregated footprint weights (cutoffs). The results indicate that the size, shape, and weight of pixels inside the footprint source area are strongly influenced by the cutoff values. Small cutoff values, such as 0.3 and 0.35, yielded high weights for pixels located within the footprint domain, while large cutoffs, such as 0.9 and 0.95, result in low weights. The results also indicate that the distribution of modelled LE values within the footprint source area are influenced by the cutoff values. A wide variation in LE was observed at high cutoffs, such as 0.90 and 0.95, while a low variation was observed at small cutoff values, such as 0.3. This happens due to the large number of pixel units involved inside the footprint domain when using high cutoff values, whereas a limited number of pixels are obtained at lower cutoff values