scholarly journals Introduction of Variable Correlation for the Improved Retrieval of Crop Traits Using Canopy Reflectance Model Inversion

2019 ◽  
Vol 11 (22) ◽  
pp. 2681
Author(s):  
Asmaa Abdelbaki ◽  
Martin Schlerf ◽  
Wout Verhoef ◽  
Thomas Udelhoven
Keyword(s):  
Test Site ◽  
Coefficient Of Determination ◽  
Canopy Reflectance ◽  
Remotely Sensed Data ◽  
Biophysical Parameters ◽  
Area Index ◽  
Model Inversion ◽  
Ill Posed ◽  
The Impact

Look-up table (LUT)-based canopy reflectance models are considered robust methods to estimate vegetation attributes from remotely sensed data. However, the LUT inversion approach is sensitive to measurements and model uncertainties, which raise the ill-posed inverse problem. Therefore, regularization options are needed to mitigate this problem and reduce the uncertainties of estimates. In this study, we introduce a new method to regularize the LUT inversion approach to improve the accuracy of biophysical parameters (leaf area index (LAI) and fractional vegetation cover (fCover)). This was achieved by incorporating known variable correlations that existed at the test site into the LUT approach to correlate the model variables of the Soil–Leaf–Canopy (SLC) model using the Cholesky decomposition algorithm. The retrievals of 27 potato plots obtained from the regularized LUT (LUTreg) were compared with the standard LUT (LUTstd), which did not consider variable correlations. Different solutions from both types of LUTs (LUTreg and LUTstd) were utilized to improve the quality of the model outputs. Results indicate that the present method improved the accuracy of LAI estimation, with the coefficient of determination R2 = 0.74 and normalized root-mean-square error NRMSE = 24.45% in LUTreg, compared with R2 = 0.71 and NRMSE = 25.57% in LUTstd. In addition, the variability of LAI decreased in LUTreg (5.10) compared with that in LUTstd (12.10). Hence, our results give new insight into the impact of adding the correlation between variables to the LUT inversion approach to improve the accuracy of estimations. In this study, only two correlated variables (LAI and fCover) were examined; in subsequent studies, the full correlation matrix based on the Cholesky algorithm should be explored.

scholarly journals Evapotranspiration simulated by CRITERIA and AquaCrop models in stony soils

2015 ◽  
Vol 10 (2) ◽  
pp. 67 ◽  
Author(s):  
Pasquale Campi ◽  
Francesca Modugno ◽  
Alejandra Navarro ◽  
Fausto Tomei ◽  
Giulia Villani ◽  
...  
Keyword(s):  
Statistical Tests ◽  
Efficiency Index ◽  
Balance Model ◽  
Coefficient Of Determination ◽  
Wheat Crop ◽  
Area Index ◽  
Aquacrop Model ◽  
Daily Evapotranspiration ◽  
Daily Scale ◽  
The Impact

The performance of a water balance model is also based on the ability to correctly perform simulations in heterogeneous soils. The objective of this paper is to test CRITERIA and AquaCrop models in order to evaluate their suitability in estimating evapotranspiration at the field scale in two types of soil in the Mediterranean region: non-stony and stony soil. The first step of the work was to calibrate both models under the non-stony conditions. The models were calibrated by using observations on wheat crop (leaf area index or canopy cover, and phenological stages as a function of degree days) and pedo-climatic measurements. The second step consisted in the analysing the impact of the soil type on the models performances by comparing simulated and measured values. The outputs retained in the analysis were soil water content (at the daily scale) and crop evapotranspiration (at two time scales: daily and crop season). The model performances were evaluated through four statistical tests: normalised difference (D%) at the seasonal time scale; and relative root mean square error (RRMSE), efficiency index (EF), coefficient of determination (r<sup>2</sup>) at the daily scale. At the seasonal scale, values of D% were less than 15% in stony and on-stony soils, indicating a good performance attained by both models. At the daily scale, the RRMSE values (2) indicate the inadequacy of AquaCrop to simulate correctly daily evapotranspiration. The higher performance of CRITERIA model to simulate daily evapotranspiration in stony soils, is due to the soil submodel, which requires the percentage skeleton as an input, while AquaCrop model takes into account the presence of skeleton by reducing the soil volume.

scholarly journals The Influence of Hospital Image and Service Quality on Discharge Against Medical Advice through Patient Satisfaction

2021 ◽  
Author(s):  
Yusriadi Yusriadi
Keyword(s):  
Quality Of Service ◽  
Patient Satisfaction ◽  
Service Quality ◽  
District Hospital ◽  
Medical Advice ◽  
Coefficient Of Determination ◽  
Against Medical Advice ◽  
Discharge Against Medical Advice ◽  
The Impact

The purpose of this study is to examine the impact of hospital image and quality of service on Discharge Against Medical Advice (DAMA) via patient satisfaction at Majene District Hospital. This research was performed in the hospital room of the Majene District Hospital from July to August 2020. The type of analysis used is quantitative research to explain the dependent variable's effect on the independent variable and the mediating variable. This study population was all 102 patients with DAMA at Majene Hospital, as the population was deemed limited and the whole population was sampled. The test results of the coefficient of determination of the path analysis of substructure 1 resulted in a modified R square value of 0.235. In this case, it is argued that patient satisfaction is affected by the hospital picture and quality of service by 23.5 percent. In comparison, the remaining 76.5 percent is influenced by other variables not analysed in this review. The outcome of the measurement of standardized beta coefficients, the effect of the hospital picture (X1) on patient satisfaction (Y1) is 0.228, and the service quality (X2) on patient satisfaction (Y1) is 0.325.

scholarly journals The Effect of Product Quality to Purchase Decision at Safary Milk D’Kandang Amazing Farm Depok

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Maidar Simanihuruk
Keyword(s):  
Product Quality ◽  
Quantitative Methods ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Positive Influence ◽  
Coefficient Of Determination ◽  
Purchase Decision ◽  
The Impact

<p><em>To achieve the desired product quality, a quality standardization of the product is needed. This method is intended to ensure that the products produced meet the predetermined standards so that consumers will not lose confidence in the product concerned. Consumers will make a purchase decision if the product is considered to have high quality. </em><em>The quality of the product will be felt after the item is consumed or used so that consumers will feel satisfied with the product purchased</em><em>. </em><em>The purpose of this study is to determine the impact of product quality on purchas</em><em>e</em><em> decision</em><em> </em><em> at the </em><em>Safary Milk D’Kandang Amazing Farm Depok. The Method of research used is quantitative methods in order to obtain more comprehensive, valid, reliable, and objective data. The sample consists of 100 visitors who visited the Safary Milk D’Kandang Amazing Farm Depok, selected based on the Probability Sampling with Simple Random Sampling technique. The factor and simple linear regression analysis were used for the data analysis with SPSS 22.0.</em><em></em></p><p><em>                </em><em>The results of the study showed that product quality has a positive influence significantly contributed</em><em> </em><em> to the purchas</em><em>e</em><em> decision </em><em> </em><em>at the </em><em>Safary Milk D’Kandang Amazing Farm Depok (</em><em>t = 11.955 &gt; t <sub>table</sub> with a significance of 0.000 (ρ &lt; 0.05) and that is proved by the score of R = 0.770.</em><em> From the coefficient of determination, it can be concluded that the Purchas</em><em>e</em><em> Decision is influenced by the Product Quality variable by 59.3% and the remaining 40.7% which is influenced by other variables.</em><em></em></p><p><em>Keywords: Product Quality, Purchase Decision</em><em></em></p>

scholarly journals PERAN MOTIVASI DAN KINERJA PENYULUH PERTANIAN DALAM MENGUBAH PERILAKU PETANI JAGUNG

2018 ◽  
Vol 14 (3) ◽  
pp. 225
Author(s):  
Mohamad Ikbalbahua
Keyword(s):  
Agricultural Extension ◽  
Coefficient Of Determination ◽  
Influence Coefficient ◽  
Performance Impact ◽  
Ex Post ◽  
Ex Post Facto ◽  
Farmer Behavior ◽  
And Performance ◽  
The Impact

The purpose of this study are: (1) identify the influence of competence that can improve the performance of agricultural extension in the development of maize farming, (2) examine the influence of competence and performance of agricultural extension on the behavior of corn farmers, and (3) analysis the impact of extension performance agriculture corn farmers on changing behaviors. Research conducted in Gorontalo Province in Maret until Juni 2018. The study was "ex post facto," The smallest unit of observation is the agricultural extension numbering 118 persons. Data collected through interviews using a questionnaire. Data were analyzed using LISREL 8.30 SEM program. Results showed the influence of competence on the performance of agricultural extension is influenced by the dimensions of Capacity building and needs affiliated. Variable motivation of extension agents indirect influence on corn farmers' behavior changes, while the performance of agricultural extension through the dimensions of quality of appreciation of cultural diversity and quality of management information direct impact on farmer behavior with the influence coefficient of 0.83 unit. Impact of agricultural extension agent performance impact on changing behaviors through a dimension of competence corn farmers and farmers with farmer participation coefficient of determination (R2) equal to 69 percent.

scholarly journals Inversion of Rice Biophysical Parameters Using Simulated Compact Polarimetric SAR C-Band Data

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2271 ◽  
Author(s):  
Xianyu Guo ◽  
Kun Li ◽  
Yun Shao ◽  
Zhiyong Wang ◽  
Hongyu Li ◽  
...  
Keyword(s):  
Water Content ◽  
Cloud Model ◽  
Volumetric Water Content ◽  
Coefficient Of Determination ◽  
Accurate Estimation ◽  
Biophysical Parameters ◽  
Area Index ◽  
Water Cloud ◽  
Sar Data ◽  
New Generation

Timely and accurate estimation of rice parameters plays a significant role in rice monitoring and yield forecasting for ensuring food security. Compact-polarimetric (CP) synthetic aperture radar (SAR), a good compromise between the dual- and quad-polarized SARs, is an important part of the new generation of Earth observation systems. In this paper, the ability of CP SAR data to retrieve rice biophysical parameters was explored using a modified water cloud model. The results showed that S1 was superior to other CP variables in rice height inversion with a coefficient of determination (R2) of 0.92 and a root-mean-square error (RMSE) of 5.81 cm. RL was the most suitable for inverting the volumetric water content of the rice canopy, with an R2 of 0.95 and a RMSE of 0.31 kg/m3. The m-χ decomposition produced the highest accuracies for the ear biomass: R2 was 0.89 and RMSE was 0.17 kg/m2. The highest accuracy of leaf area index (LAI) retrieval was obtained for RH (right circular transmit and horizontal linear receive) with an R2 of 0.79 and a RMSE of 0.33. This study illustrated the capability of CP SAR data with respect to retrieval of rice biophysical parameters, especially for height, volumetric water content of the rice canopy, and ear biomass, and this mode may offer the best option for rice-monitoring applications because of swath coverage.

scholarly journals Automated leveling systems for development and cleaning of reclamation channels in the agro-industrial complex

2021 ◽  
Vol 845 (1) ◽  
pp. 012154
Author(s):  
A V Mironov ◽  
A S Apatenko ◽  
N S Sevryugina ◽  
O A Stupin
Keyword(s):  
Human Factor ◽  
Field Tests ◽  
Test Site ◽  
Satellite Monitoring ◽  
Industrial Complex ◽  
Agricultural Work ◽  
Technological Improvement ◽  
The Impact ◽  
Speed And Accuracy

Abstract Reclamation complexes, the key element of which are bypass canals, are actively used for effective agricultural work. For the development of reclamation canals. as a rule, excavator equipment is used, which subsequently ensures their effective functioning. The analysis of the impact of the efficiency of the functioning of amelioration systems on the agro-industrial complex (AIC) sectors revealed a significant dependence on obtaining high-quality crops or pastures. Factors were identified that reduce the quality of reclamation work. Among them, the indicator of positioning accuracy of the profile of the soil during clearing or arrangement of channels is highlighted as the main one. It was proved that the installation of automated leveling systems will provide technological improvement to the excavator. Modernization of excavators by introducing automatic leveling systems (ALS), allows you to increase the speed and accuracy of work, and therefore productivity. There are three main ALS solutions for excavator operation: ALS 2 D control system; ALS satellite monitoring system; ALS AUTO satellite leveling system. It was determined that for using ALS AUTO, the quality of the work performed does not depend on the human factor. Field tests were carried out at the test site with quality control of the construction embankments with JCB JS 205 excavator modernized with ALS. The data obtained were compared with the results of grading with a JCB JS 205 excavator without ALS. Based on the results of the data analysis, it was found that with the introduction of automatic leveling systems, the productivity of the equipment increases by 200%, and the accuracy of the work performed has increased 2 times.

scholarly journals Assessing Non-Photosynthetic Cropland Biomass from Spaceborne Hyperspectral Imagery

2021 ◽  
Vol 13 (22) ◽  
pp. 4711
Author(s):  
Katja Berger ◽  
Tobias Hank ◽  
Andrej Halabuk ◽  
Juan Pablo Rivera-Caicedo ◽  
Matthias Wocher ◽  
...  
Keyword(s):  
Hyperspectral Image ◽  
Quantitative Estimation ◽  
Gaussian Process Regression ◽  
Training Data ◽  
Coefficient Of Determination ◽  
Canopy Reflectance ◽  
Data Set ◽  
Area Index ◽  
Essential Information ◽  
Wide Range

Non-photosynthetic vegetation (NPV) biomass has been identified as a priority variable for upcoming spaceborne imaging spectroscopy missions, calling for a quantitative estimation of lignocellulosic plant material as opposed to the sole indication of surface coverage. Therefore, we propose a hybrid model for the retrieval of non-photosynthetic cropland biomass. The workflow included coupling the leaf optical model PROSPECT-PRO with the canopy reflectance model 4SAIL, which allowed us to simulate NPV biomass from carbon-based constituents (CBC) and leaf area index (LAI). PROSAIL-PRO provided a training database for a Gaussian process regression (GPR) algorithm, simulating a wide range of non-photosynthetic vegetation states. Active learning was employed to reduce and optimize the training data set. In addition, we applied spectral dimensionality reduction to condense essential information of non-photosynthetic signals. The resulting NPV-GPR model was successfully validated against soybean field data with normalized root mean square error (nRMSE) of 13.4% and a coefficient of determination (R2) of 0.85. To demonstrate mapping capability, the NPV-GPR model was tested on a PRISMA hyperspectral image acquired over agricultural areas in the North of Munich, Germany. Reliable estimates were mainly achieved over senescent vegetation areas as suggested by model uncertainties. The proposed workflow is the first step towards the quantification of non-photosynthetic cropland biomass as a next-generation product from near-term operational missions, such as CHIME.

scholarly journals The Impact of Selected Factors on the Quality of Business Environment Assessment in the Czech Republic and the Slovak Republic

2018 ◽  
Vol 6 (2) ◽  
pp. 71-80 ◽  
Author(s):  
Anna Kotaskova ◽  
Zoltan Rozsa
Keyword(s):  
Human Capital ◽  
Czech Republic ◽  
Research And Development ◽  
Slovak Republic ◽  
Business Environment ◽  
Coefficient Of Determination ◽  
The Czech Republic ◽  
Technological Factors ◽  
The Impact

Abstract The paper’s aim is to examine the dependence of the quality of the business environment on defined technological factors (availability of human capital and research and development infrastructure) and to define and quantify significant technological factors that create the quality of the business environment in the SMEs segment. Part of its goal was the comparison of the defined factors between the Czech Republic (CR) and the Slovak Republic (SR). In connection with the stated research goal, a questionnaire survey was conducted among businesses operating in the SME segment. Through this research, 312 companies were surveyed in the Czech Republic and 329 companies in the Slovak Republic. To achieve the primary goal of the article, methods such as correlation analysis and multiple linear regression modelling (t-tests, F-ratio, adjusted coefficient of determination, and so on) were applied. The results of the research have brought interesting findings. Research and development infrastructure, as well as the availability of human capital are important factors that have a positive impact on the business environment in both countries.

scholarly journals ANÁLISE DE SENSIBILIDADE DE PARÂMETROS HIDROLÓGICOS NA BACIA DO RIO DAS PEDRAS - GUARAPUAVA-PR

2019 ◽  
Vol 12 (5) ◽  
pp. 1746
Author(s):  
Rafael Adriano de Castro Adriano de Castro ◽  
Elias Machado
Keyword(s):  
Sensitivity Analysis ◽  
Input Data ◽  
Assessment Tool ◽  
Swat Model ◽  
Coefficient Of Determination ◽  
Land Use And Management ◽  
The Impact ◽  
Water Assessment ◽  
Soil And Water

O modelo Soil and Water Assessment Tool (SWAT) é amplamente utilizado para predizer o impacto das alterações no uso e no manejo do solo, entre outros, é extremamente sensível à qualidade dos dados de entrada.  Assim, antes da simulação é necessário que se realize uma análise de sensibilidade de tal forma que se possa dar ênfase maior à aquisição e refinamento de determinados dados, diminuir as incertezas e aumentar a confiança nos resultados gerados. Os resultados simulados na bacia do Rio das Pedras – Guarapuava, foram realizadas a análise de sensibilidade e a calibração do modelo SWAT. Após a calibração do modelo os resultados do Índice de Nash & Sutcliffe alterado (COE), do percentual de tendência (PBIAS), e o coeficiente de determinação (R²) foram, respectivamente, 0,69, -0,5 e 0,7, indicando bom ajuste entre a vazão média mensal da bacia Rio das Pedras simulada pelo modelo SWAT em relação aos dados observados.  Sensitivity analysis of hydrological parameters in the Rio das Pedras basin - Guarapuava-PR A B S T R A C TThe SWAT model is widely used to predict the impact of changes in land use and management, among others, is extremely sensitive to the quality of input data. Thus, prior to the simulation, it is necessary to perform a sensitivity analysis in such a way that greater emphasis can be placed on the acquisition and refinement of certain data, decrease uncertainties and increase confidence in the results generated. The simulated results in the Rio das Pedras - Guarapuava basin, were performed the sensitivity analysis and calibration of the SWAT model. After the calibration of the model, the results of the modified Nash & Sutcliffe Index (COE), percentage of trend (PBIAS), and coefficient of determination (R²) were, respectively, 0.69, -0.5 and 0.7, Indicating a good fit between the average monthly flow of the Rio das Pedras basin simulated by the SWAT model in relation to the observed data. 

scholarly journals Determinants of Accounting Information System in pt. Indomarco Adi Prima, Jember Branch

2020 ◽  
Vol 1 (1) ◽  
pp. 70-77
Author(s):  
Rina Dian AGUSTIN ◽  
Muhammad FIRDAUS ◽  
Nanda WIDANINGGAR
Keyword(s):  
Information Systems ◽  
Accounting Information ◽  
User Involvement ◽  
Education And Training ◽  
Coefficient Of Determination ◽  
Accounting Data ◽  
Accounting Information Systems ◽  
The Impact ◽  
And Training

The fundamental role of Accounting Information Systems (AIS) in organizations was a processor of accounting data to produce quality accounting information to support the company's internal activities, which had a significant correlation with the external. By the purposive sampling method, this study aims to analyze the impact of Education and Training Programs, Involvement of System Users, and Human Resources (HR) Competence on the Quality of Accounting Information Systems at PT. Indomarco Adi Prima Jember Branch, since there were ineffective process in selling application, by the late of manager approval and the network problem. The population in this study were all of employees who use Information Systems at PT. Indomarco Adi Prima Jember Branch. The method used was multiple regression, the data collection technique was questionnaire, and the result showed that the variable Education and Training Program significantly influences the quality of the AIS, System User Involvement variable significantly influences the quality of SIA, and HR competency variable significantly influences the quality of SIA and the coefficient of determination (R2) of all independent variables strongly explained the dependent variable.

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