Actual Tree Research Articles

An Efficient User’s Attribute Revocation Scheme Suitable for Data Outsourcing in Cloud Storage

With the advances of cloud data centers and cloud service, many application scenarios are developed such as enterprise business, the Vehicular Ad Hoc Networks (VANET), Sensor network. Confidentiality and efficiency are two key problems. CP-ABE is one of fine-grained access control cryptographic technologies and it is widely applied in outsourced data in cloud storage to protect the user’s privacy. In addition, besides confidentiality, computational cost is an important factor which makes the application of CP-ABE possible in the situations. In this paper, we propose a novel and fast scheme based on CP-ABE algorithm from the respect of the user’s attribute revocation to make it faster. In this scheme, we construct an identical tree T2 that has the same structure as the actual access control tree T1. When the user issues to request the encrypted text preserved on CSP, CSP first tries to decrypt CT2 which is encrypted according to the access policy based on the identical tree T2 and also preserved on it, with the subset of the secret keys corresponding to the indexes of the attributes provided by the user. If CSP can successfully decrypt it, it proves that he/she has the authorization to access the cryptographic text CT1 and CSP will send CT1 to the user. Otherwise, CSP recognizes that the user has no access to CT1 and rejects to send CT1 to the user. Namely, we can decide if we authorize the right to access CT1 by judging if the secret key provided by the user can decrypt CT2. Because CT1 and CT2 have the same access control structure, they have the same secret key for decryption; that is, when some attributes are revoked, if the secret key cannot decrypt CT2, it cannot decrypt CT1. While CSP can directly decrypt CT2, but not CT1, CSP can judge if the user has access to CT1 after the attribute revocation by decryption of CT2. Moreover, we propose the construction method of CT1 and CT2. Finally, we prove that the scheme is secure and viable.

Mathematical modelling to determine the greatest height of trees

This study aimed to analyse the critical height of a column whose weight varies vertically in order to obtain a simple scaling law for a tree where the weight distribution considered. We modelled trees as cantilevers that were fixed to the ground and formulated a self-buckling problem for various weight distributions. A formula for calculating the critical height was derived in a simple form that did not include special functions. We obtained a theoretical clarification of the effect of the weight distribution of heavy columns on the buckling behaviour. A widely applicable scaling law for trees was obtained. We found that an actual tree manages to distribute the weight of its trunk and branches along its vertical extent in a manner that adequately secures its critical height. The method and findings of this study are applicable to a wide range of fields, such as the simplification of complicated buckling problems and the study of tree shape quantification.

A photogrammetry-based methodology to obtain accurate digital ground-truth of leafless fruit trees

In recent decades, a considerable number of sensors have been developed to obtain 3D point clouds that have great potential in optimizing management in agriculture through the application of precision agriculture techniques. In order to use the data provided by these sensors, it is essential to know their measurement error. In this paper, a methodology is presented for obtaining a 3D point cloud of a central axis training system defoliated fruit tree (Malus domestica Bork.) obtained from stereophotogrammetry techniques based on structure-from-motion (SfM) and multi-view stereo-photogrammetry (MVS). The point cloud was made from a set of 288 photographs of the scene including the ground truth tree which was used to generate the digital 3D model. The resulting point cloud was validated and proven to faithfully represent reality. The bias of the resulting model is −0.15 mm and 0.05 mm, for diameters and lengths, respectively. In addition, the presented methodology allows small changes in the ground truth actual tree to be detected as a consequence of the wood dehydration process. Having an actual and a digital ground-truth is the basis for validating other sensing systems for 3D vegetation characterization which can be used to obtain data to make more informed management decisions.

Transpiration and Water Use of an Irrigated Traditional Olive Grove with Sap-Flow Observations and the FAO56 Dual Crop Coefficient Approach

The SIMDualKc model was applied to evaluate the crop water use and the crop coefficient (Kc) of an irrigated olive grove (Olea europaea L.) located in Sicily, Italy, using experimental data collected from two crop seasons. The model applies the FAO56 dual Kc approach to compute the actual crop evapotranspiration (ETc act) and its components, i.e., the actual tree transpiration (Tc act), obtained through the basal crop coefficient (Kcb), and soil evaporation according to an evaporation coefficient (Ke). Model calibration was performed by minimizing the difference between the predicted Tc act and the observed daily tree transpiration measured with sap flow instrumentation (TSF field) acquired in 2009. The validation was performed using the independent data set of sap flow measurements from 2011. The calibrated Kcb was equal to 0.30 for the initial and non-growing season stages, 0.42 for the mid-season, and 0.37 for the end season. For both seasons, the goodness-of-fit indicators relative to comparing TSF field with the simulated Tc act resulted in root mean square errors (RMSE) lower than 0.27 mm d−1 and a slope of the linear regression close to 1.0 (0.94 ≤ b0 ≤ 1.00). The olive grove water balance simulated with SIMDualKc produced a ratio between soil evaporation (Es) and ETc act that averaged 39%. The ratio between actual (ETc act) and potential crop evapotranspiration (ETc) varied from 84% to about 99% in the mid-season, indicating that the values of ETc act are close to ETc, i.e., the adopted deficit irrigation led to limited water stress. The results confirm the suitability of the SIMDualKc model to apply the FAO56 dual Kc approach to tree crops, thus assessing the water use of olives and supporting the development of appropriate irrigation management tools that are usable by farmers. A different way to estimate Kcb is based on the approach suggested in 2009 by Allen and Pereira (A&P), which involves the measured fraction of ground covered (shaded) by the crop and the height of the trees. Its application to the studied grove produced the mid-season Kcb values ranging from 0.40–0.45 and end-season Kcb values ranging from 0.35–0.40. The comparison between the A&P-computed Tc act A&P and TSF field shows RMSE values ranging from 0.27 to 0.43 mm d−1, which demonstrates the adequacy of the latter approach for parameterizing water balance models and for irrigation scheduling decision making.

Geoecological parameters indicate discrepancies between potential and actual forest area in the forest-steppe of Central Mongolia

BackgroundForest distribution in the forest-steppe of Mongolia depends on relief, permafrost, and climate, and is highly sensitive to climate change and anthropogenic disturbance. Forest fires and logging decreased the forest area in the forest-steppe of Mongolia. The intention of this study was to identify the geoecological parameters that control forest distribution and living-tree biomass in this semi-arid environment. Based on these parameters, we aimed to delineate the area that forest might potentially occupy and to analyse the spatial patterns of actual and potential tree biomass.MethodsWe used a combination of various geographic methods in conjunction with statistical analyses to identify the key parameters controlling forest distribution. In several field campaigns, we mapped tree biomass and ecological parameters in a study area within the Tarvagatai Nuruu National Park (central Mongolia). Forest areas, topographic parameters and vegetation indices were obtained from remote sensing data. Significant correlations between forest distribution and living-tree biomass on one hand, and topographic parameters, climate data, and environmental conditions on the other hand, were used to delineate the area of potential forest distribution and to estimate total living-tree biomass for this area.ResultsPresence of forest on slopes was controlled by the factors elevation, aspect, slope, mean annual precipitation, and mean growing-season temperature. Combining these factors allowed for estimation of potential forest area but was less suitable for tree-biomass delineation. No significant differences in mean living-tree biomass existed between sites exposed to different local conditions with respect to forest fire, exploitation, and soil properties. Tree biomass was reduced at forest edges (defined as 30 m wide belt), in small fragmented and in large forest stands. Tree biomass in the study area was 20 × 109 g (1,086 km2 forest area), whereas the potential tree biomass would reach up to 65 × 109 g (> 3168 km2).ConclusionsThe obtained projection suggests that the potential forest area and tree biomass under the present climatic and geoecological conditions is three times that of the present forest area and biomass. Forest fires, which mostly affected large forest stands in the upper mountains, destroyed 43% of the forest area and 45% of the living-tree biomass in the study area over the period 1986–2017.

Individual Tree Crown Detection Using UAV Orthomosaic

Unmanned Aerial Vehicles (UAVs) are increasingly used in forestry as they are economical and flexible. This study aims to present the advantages of the drone photogrammetry method in collecting individual tree crowns, as individual tree crown detection could deliver essential ecological and economic information. The referred accuracy for individual tree crown extraction is 79.2%. Only crowns that were clearly visible were selected and manually delineated on the image because the distribution of the true crown size is significantly different from the segmented crowns. The aim of this study is to investigate UAVs orthomosaics in individual tree crown detection. The objectives of this study are to produce the orthomosaic of tree crown extraction mapping using the Pix4D software and analyze the tree crowns using tree crown delineation and the OBIA algorithm. Data processing involves the processing of aerial images using Pix4Dmapper. Automatic tree crown detection involves a tree crown delineation algorithm and OBIA operations to process the tree crown extraction. The crown delineation algorithm and OBIA algorithm operation will be compared to the actual tree crown measurement in terms of diameter and area. The tree crown delineation method obtained a 0.347m mean diameter difference from the actual tree crown diameter, while the OBIA approach obtained 4.98m. The tree crown delineation method obtained 97.26% of the actual tree crown area, while OBIA obtained 91.74%.

A method for measuring the forces acting on a tree trunk using strain gauges.

The wind force acted on a tree constantly changes in magnitude, direction, and distribution. We developed a method to measure simultaneously the amount of force (F), centroid of the distributed force (C), and direction of force (D) on a tree trunk using four strain gauges. F and C were estimated from the difference in the bending moments at two different positions along the long axis of the stem. D was estimated using the difference in the sensor outputs at two different radial positions at the same height. In principle, the two strain gauges should be oriented precisely 90° apart; however, this is unrealistic on an actual tree trunk. To calculate D, we developed a new method to detect the radial position and modulus of elasticity of each strain gauge after attaching it. We conducted three types of experiment. First, we loaded a wood pole with weights arranged in 11 patterns to test the accuracies of F and C for a distributed load. Next, we applied tensile forces to the wood pole and an evergreen conifer sapling from eight directions to test the accuracy of D, F, and C. On average, estimation errors were < 2% for both the distributed load and circumferential tensile load. Our method can estimate F, C, and D precisely, even if the wood is uneven and the strain gauges are not aligned. This is a great advantage for field wind force measurements.

EXAMINATION OF MANGROVE MODELING IN NUMERICAL CALCULATION

A number of studies which handle wave height attenuation effect due to coastal vegetation such as mangroves and coastal forests have been performed. In recent years, for considering effect of the mangrove roots, actual trees have been used for laboratory test. Chang (2019) proposed a formula for calculating C_D and C_M from Re and KC through experiments using a mangrove 3D model printed using actual tree. The C_D and C_M have been estimated experimentally under the condition that the water depth is relatively large and the waves don't break. However, the relationship between the Re number and the KC number and the C_D and C_M have not been investigated. Therefore, we conducted experiments focusing on the arrangement and density of the forest zone and trunk thickness. Then we demonstrated the validity of our analysis based on the comparison of our result and results of previous studies. The aim of this study is to establish a modeling method for coastal vegetation in order to enable calculation of the wave attenuation effect due to mangroves using numerical calculation.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/bcNlvRSvJQk

Estimation of Tree Height by Combining Low Density Airborne LiDAR Data and Images Using the 3D Tree Model: A Case Study in a Subtropical Forest in China

In general, low density airborne LiDAR (Light Detection and Ranging) data are typically used to obtain the average height of forest trees. If the data could be used to obtain the tree height at the single tree level, it would greatly extend the usage of the data. Since the tree top position is often missed by the low density LiDAR pulse point, the estimated forest tree height at the single tree level is generally lower than the actual tree height when low density LiDAR data are used for the estimation. To resolve this problem, in this paper, a modified approach based on three-dimensional (3D) parameter tree model was adopted to reconstruct the tree height at the single tree level by combining the characteristics of high resolution remote sensing images and low density airborne LiDAR data. The approach was applied to two coniferous forest plots in the subtropical forest region, Fujian Province, China. The following conclusions were reached after analyzing the results: The marker-controlled watershed segmentation method is able to effectively extract the crown profile from sub meter-level resolution images without the aid of the height information of LiDAR data. The adaptive local maximum method satisfies the need for detecting the vertex of a single tree crown. The improved following-valley approach is available for estimating the tree crown diameter. The 3D parameter tree model, which can take advantage of low-density airborne LiDAR data and high resolution images, is feasible for improving the estimation accuracy of the tree height. Compared to the tree height results from only using the low density LiDAR data, this approach can achieve higher estimation accuracy. The accuracy of the tree height estimation at the single tree level for two test areas was more than 80%, and the average estimation error of the tree height was 0.7 m. The modified approach based on the three-dimensional parameter tree model can effectively increase the estimation accuracy of individual tree height by combining the characteristics of high resolution remote sensing images and low density airborne LiDAR data.

When a definition makes the difference: operative issues about tree height measures from RPAS-derived CHMs

Tree height (H) survey is a fundamental step in forest mensuration. The error affecting tree height measure, necessarily influences the correspondent tree estimates. The remotely survey of vegetation using PHODAR (PHOtogrammetric Detection And Ranging) or LiDAR (Light Detection And Ranging) techniques generates very high-density point clouds, that result into Canopy Height Models (CHMs) having GSD (Ground Sampling Distance) of few centimetres. This GSD value potentially allows to survey single crown apexes, which, from a forestry point of view, do not represent the actual tree height. Apex height value, in fact, does not represent the prevailing dendrometric height (PDH) but the maximum tree value. In this study we propose a new approach aimed at measuring dendrometric height by PHODAR derived CHM, taking care about this issue. The proposed method defines a correcting factor (found equal to 95% percentile of CHM values distribution within a given crown) for the tree height extraction from CHM based on the PDH concept. The method could be implemented to single crown approach in forest parameters extraction algorithms permitting more reliable results, especially in terms of tree volume and related estimations (e.g., carbon stock quantification, allometric models).

Effects of salinity and sodicity on the seasonal dynamics of actual evapotranspiration and surface energy balance components in mature micro-irrigated pistachio orchards

This article presents findings from a field research study conducted in the San Joaquin Valley of California in 2016–2018 to appraise the effects of soil salinity and sodicity on evapotranspiration and energy balance components of micro-irrigated pistachio orchards. Actual evapotranspiration (ETa) and tree physiologic parameters were measured during consecutive growing seasons in mature orchards grown on non-saline and saline/sodic soils. Salinity and sodicity decreased pistachio water use by about 30%, with ETa reductions varying along the growing season. Accurate information on the dynamics of ETa and energy balance components along the growing season can improve water management for nut orchards exposed to long-term saline-sodic conditions. Results show that the main driver of ETa was the net radiation (Rn), which supplied most of the energy to vaporize water, irrespective of the growth period and level of salinity/sodicity. Field observations revealed that Rn was lower for salt-affected trees due to smaller canopies, which intercepted less light than non-saline trees. Secondarily, the exchange of sensible heat (H) between the ambient air and tree canopies was affected by the interaction between salinity–sodicity and seasonality. Early in the season, salinity and sodicity affected ETa mainly through the reduced canopy growth, which decreased the available energy (Rn–G) for ETa and reduced the water uptake as a result of the lower soil water potential. Late in the season, an increase in H and a decrease in the contribution of the aerodynamic component (β coefficient) to the latent heat flux (LE) occurred, which determined a further reduction of ETa due to a physiological response. The decrease in the β coefficient during the late season was associated with a direct impact of ion accumulation on leaf functionality. Collecting data on the contribution of the aerodynamic component to LE offers a low-cost method to detect and quantify physiological stress, while providing useful information for managing irrigation in salt-affected orchards. The results presented in this article provide insights to improve irrigation management of salt-affected pistachio through integration of weather measurements, energy balance components, and plant-based parameters.

Viability of temperate fruit tree varieties in Spain under climate change according to chilling accumulation

Fruit trees stop their growth over the coldest period of the year to avoid damage. To resume their growth and for successful fruit production, they need to accumulate winter chill. It is expected that global warming will diminish winter chill availability with potentially negative impacts on the viability and yield of these crops. The objective of this study was to assess the viability of seven tree crops among the most relevant in peninsular Spain and the Balearic Islands. For this purpose, chilling requirements were gathered from the literature to define a requirement range for each tree crop encompassing most of the varieties used in Spain. Then the bias-adjusted outputs of an ensemble of 10 regional climate models under the two representative concentration pathways (RCPs), 4.5 and 8.5, were used to feed a chilling model for calculating chill accumulation. The ensemble's outcome agreement index was applied to each combination of chill requirement and climate ensemble to assess crop viability. This was done by testing the hypothesis that the winter chill accumulation will be greater than the safe winter chill for the 2021–2050 (near future) and 2071–2100 (far future) periods and for both RCPs. A future reduction in the safe winter chill areas is projected with high agreement in climate projections across peninsular Spain and the Balearic Islands independently of the RCP or future period. The crops studied would be viable in the near future period as long as varieties with low chilling requirements are used. These varieties, however, would not be adequate in the far future in some currently highly productive regions, where the situation would become more severe, especially under the RCP8.5 scenario. In these cases, adaptation would be possible by shifting the crop to adjacent areas together with careful variety selection in terms of chilling requirements. The results indicate that the RCP8.5 scenario in the far future has an especially negative impact on the crops analysed, calling for resolute mitigation measures to guarantee tree crop production and food security. Recommendations for adaptation, with low uncertainty regarding climate projections, were included here, using actual tree varieties, thereby facilitating interpretation and on-field application for farmers and agricultural technicians.

Cropland trees need to be included for accurate model simulations of land-atmosphere heat fluxes, temperature, boundary layer height, and ozone

Trees significantly impact land-atmosphere feedbacks through evapotranspiration, photosynthesis and isoprene emissions. These processes influence the local microclimate, air quality and can mitigate temperature extremes and sequester carbon dioxide. Despite such importance, currently only 5 out of 15 atmospheric chemistry climate models even partially account for the presence of cropland trees. We first show that the tree cover over intensely farmed regions in Asia, Australia and South America is significantly underestimated (e.g. only 1–3% tree cover over north-India) in the Model of Emissions of Gases and Aerosol from Nature (MEGAN) and absent in Noah land-surface module of the Weather Research and Forecasting (WRF-Chem) Model. By including the actual tree cover (~10%) over the north-west Indo Gangetic Plain in the Noah land-surface module of the WRF-Chem and the MEGAN module, during the rice growing monsoon season in August, we find that the latent heat flux alone increases by 100%–300% while sensible heat flux reduces by 50%–100%, leading to a reduction in daytime boundary layer height by 200–400 m. This greatly improves agreement between the modelled and measured temperature, boundary layer height and surface ozone, which were earlier overestimated and isoprene and its oxidation products which were earlier underestimated. Mitigating peak daytime temperatures and ozone improves rice production by 10 to 20%. Our findings from north west Indo-Gangetic Plain establish that such plantations mitigate heat stress, and have beneficial effects on crop yields while also sequestering carbon. Expanding agroforestry practices to 50% of the cropland area could result in up to 40% yield gain regionally. Implementing such strategies globally could increase crop production and sequester 0.3–30 GtC per year, and therefore future climate mitigation and food security efforts should consider stakeholder participation for increased cropland agroforestry in view of its beneficial effects.

DETECTING AND COUNTING ORCHARD TREES ON UNMANNED AERIAL VEHICLE (UAV)-BASED IMAGES USING ENTROPY AND NDVI FEATURES

Abstract. Multispectral images were acquired by a camera on board an Unmanned Aerial Vehicle (UAV) over two apple orchards in Prince Edward Island in summer 2016. A method was developed to automatically detect rows of planted trees and trees in each row using the normalized difference vegetation index (NDVI) image and its related entropy and variance images. The image-based tree position was then compared to the actual tree location measured in the field. We achieved an accuracy of 93% between the estimated and measured number of trees in both orchards.

Homogeneous tree height derivation from tree crown delineation using Seeded Region Growing (SRG) segmentation

ABSTRACT The demand for tree height derivation is increasing year by year, especially for large plantation and forest area. The conventional method needs a long time to complete tree measurement for large forest area, especially when using a pole, measuring tape, rangefinder, clinometer, and tree climbing. This study aims to evaluate the height of oil palm tree based on crown diameter by using a multi-rotor Unmanned Aerial Vehicle (UAV). Digital Elevation Model (DEM) and orthophoto were generated by using Agisoft software, while oil palm tree crown diameter was delineated by using seed generation with Quantum Geographic Information System (QGIS) and Seeded Region Growing (SRG) segmentation methods in the System for Automated Geoscientific Analysis (SAGA). The study validates the results between the actual tree height and tree height estimated from UAV. The results showed that the orthophoto was successfully generated with a Ground Sampling Distance (GSD) of 2.95 cm and 129 tree crowns were successfully analyzed. The accuracy of the tree height as compared to the actual measurement was 57.7 cm. In conclusion, UAV images are capable of determining the tree height after going through the correct procedure to help foresters in their daily task.

Locating the propagation source in complex networks with a direction-induced search based Gaussian estimator

Locating the propagation source is crucial for developing strategies to control the spreading process taking on complex networks. Gaussian estimator (GE) is one of the most effective methods for propagation source locating in networks with limited observers. However, on general graphs, due to GE makes an approximation that the actual diffusion tree in spreading process is assumed to be a breadth-first search (BFS) tree, and thus ignores the effect of direction information recorded in observers. Therefore, the accuracy of GE is affected. In this paper, by utilizing the direction information in observers, we define, for the first time, a novel direction-induced search (DIS). Further, a direction-induced search based Gaussian estimator (DISGE) is proposed by combining DIS and the original GE. Experimental results on a series of synthetic and real networks show that the DISGE is feasible and effective in locating the propagation source with limited observers.

Estimating and Mapping Mangrove Biomass Dynamic Change Using WorldView-2 Images and Digital Surface Models

Mapping and quantification of biomass changes is critical to understanding mangrove carbon sequestration, conservation, and restoration. Few previous studies have focused on mangrove biomass changes based on high spatial resolution images, particularly for disturbed and recovering areas. This study developed an effective model to estimate and map mangrove aboveground biomass dynamic change between 2010 and 2016 on Qi'ao Island in South China. The study area includes native Kandelia candel ( K. candel ) and planted Sonneratia apetala ( S. apetala ) mangrove species within the largest planted area in China. Models were developed using WorldView-2 images, digital surface models (DSMs), and the random forest algorithm. Accuracies of the model were assessed using multiyear field samples. DSMs were identified as the most important variable for model accuracy, reducing relative error by up to 3.14%. Three models were developed: a model for 2010, another model for 2016, and a combined model for 2010 and 2016. Compared with the 2010 (RMSE = 41.03 t/ha, RMSEr = 24.31%) and 2016 (RMSE = 39.92 t/ha, RMSEr = 23.40%) models, the combined model (RMSE = 50.99 t/ha, RMSEr = 30.48%) only increased the relative error by 6.17% and 7.08%, respectively. Mangrove biomass maps generated from the most accurate models showed total biomass increased from 23270.43 to 39819.03 tons by up to 71.11% over the study period. K. candel total biomass decreased by 36.5% due to Derris trifoliata challenge. S. apetala total biomass increased by 74.79% due to reforestation programs, achieving aboveground biomass accumulation of 4.17 t/ha for stands that existed in 2010. This study provides insights into biomass dynamic change in disturbed and recovering mangrove areas. Future studies should consider using LiDAR techniques to obtain actual tree height applied for biomass estimation instead of DSM.

Detecting tree mortality with Landsat-derived spectral indices: Improving ecological accuracy by examining uncertainty

Satellite-derived fire severity metrics are a foundational tool used to estimate fire effects at the landscape scale. Changes in surface characteristics permit reasonably accurate delineation between burned and unburned areas, but variability in severity within burned areas is much more challenging to detect. Previous studies have relied primarily on categorical data to calibrate severity indices in terms of classification accuracy, but this approach does not readily translate into an expected amount of error in terms of actual tree mortality. We addressed this issue by examining a dataset of 40,370 geolocated trees that burned in the 2013 California Rim Fire using 36 Landsat-derived burn severity indices.The differenced Normalized Burn Ratio (dNBR) performed reliably well, but the differenced SWIR:NIR ratio most accurately predicted percent basal area mortality and the differenced normalized vegetation index (dNDVI) most accurately predicted percent mortality of stems ≥10 cm diameter at breast height. Relativized versions of dNBR did not consistently improve accuracy; the relativized burn ratio (RBR) was generally equivalent to dNBR while RdNBR had consistently lower accuracy.There was a high degree of variability in observed tree mortality, especially at intermediate spectral index values. This translated into a considerable amount of uncertainty at the landscape scale, with an expected range in estimated percent basal area mortality greater than 37% for half of the area burned (>50,000 ha). In other words, a 37% range in predicted mortality rate was insufficient to capture the observed mortality rate for half of the area burned. Uncertainty was even greater for percent stem mortality, with half of the area burned exceeding a 46% range in predicted mortality rate. The high degree of uncertainty in tree mortality that we observed challenges the confidence with which Landsat-derived spectral indices have been used to measure fire effects, and this has broad implications for research and management related to post-fire landscape complexity, distribution of seed sources, or persistence of fire refugia. We suggest ways to account for uncertainty that will facilitate a more nuanced and ecologically-accurate interpretation of fire effects.This study makes three key contributions to the field of remote sensing of fire effects: 1) we conducted the most comprehensive comparison to date of all previously published severity indices using the largest contiguous set of georeferenced tree mortality field data and revealed that the accuracy of both absolute and relative spectral indices depends on the tree mortality metric of interest;2) we conducted this study in a single, large fire that enabled us to isolate variability due to intrinsic, within-landscape factors without the additional variance due to extrinsic factors associated with different biogeographies or climatic conditions; and 3) we identified the range in tree mortality that may be indistinguishable based on spectral indices derived from Landsat satellites, and we demonstrated how this variability translates into a considerable amount of uncertainty in fire effects at the landscape scale.

A conceptual framework and optimization for a task-based modular harvesting manipulator

This paper provides a new concept of a modular, task-based agricultural robot whose construction can be changed using different combinations of basic parts. This way, the robot structure can be optimized to different tasks. This kind of robot combines the advantages of economical task-based robots with the ability to multitask, typically provided by costly universal robots. The modular approach can increase the profitability of agriculture robot manipulators and opens the door for robotic harvesters into agriculture. We present the entire flow of designing this type of modular agricultural manipulator. We first measure and model real trees and then calculate the time it takes the robot to reach every fruit according to the robot structure and location. Lastly, we use our optimization approach to find a robot optimal for pre-defined tasks, such as maximizing the number of fruit harvested or minimizing the picking time. Simulation results, based on actual three-dimensional tree models, show that modular robots can collect 30–40 percent more fruit than a robot with a fixed structure of the same complexity. Furthermore, a modular robot can be adapted to every season for different types of fruit; consequently, it provides much better results both in harvesting time and in amount of harvested fruit. Thus, a modular robot has the potential to increase the utilization compared with a fixed structure robot and helps overcome low-utilization barrier of entrance of robots into agriculture.

Reliability of the latest echographic recommendations for estimating left ventricular filling pressures: A comparative study with left cardiac catheterization

The current recommendations regarding the estimation of left ventricular filling pressures are based on expert consensus. We tried to evaluate the reliability of the actual algorithm in comparison with the left cardiac catheterization and with the algorithms published in 2009. We enrolled 100 adult patients scheduled for coronary angiography between December 2017 and May 2018. An estimation of filling pressures by transthoracic echocardiography and cardiac catheterization on the same day was performed. The mean age of our patients was 62.79 years ± 10.35 with a male predominance (sex ratio at 3.34). The majority had coronary artery disease (66%). The mean ejection fraction was 53% ± 13. The 2016 algorithm was superior to those published in 2009 compared to the invasive estimate. In fact, its sensitivity and specificity were 70.14% and 86.66% with an accuracy of 75.25% versus 62.21%, 86.66% and 69.79% respectively for the 2009 algorithms. Analysis, in case of preserved systolic function, showed a great decrease in the results of the 2009 algorithms while the 2016 algorithm remained valid. Regarding echographic parameters, the E/e’ ratio had the highest coefficient value ( r = 0.47) whereas no correlation was found for the tricuspid regurgitation jet velocity. In addition to its simplicity, the actual decision tree for estimating left ventricular filling pressures seems reliable and more efficient than the previous ones.