scholarly journals Kombinasi Indeks Citra untuk Analisis Lahan Terbangun dan Vegetasi Perkotaan

2018 ◽  
Vol 32 (1) ◽  
pp. 24 ◽  
Author(s):  
Iswari Nur Hidayati ◽  
R. Suharyadi ◽  
Projo Danoedoro
Keyword(s):  
Data Extraction ◽  
Urban Land ◽  
Index Formula ◽  
Vegetation Density ◽  
Threshold Values ◽  
Building Density ◽  
Object Based ◽  
Pca Method ◽  
Normalized Difference Index ◽  
Selection Of

Lahan terbangun di perkotaan dan area vegetasi menjadi hal yang sangat menarik untuk dikaji. Apalagi dinamika penggunaan lahan di perkotaan yang sangat cepat berubah. Berbagai metode dikembangkan untuk ekstraksi lahan terbangun di perkotaan, mulai dari klasifikasi multispektral, object based approach, hingga penelitian berbasis indeks. NDBI menjadi salah satu indeks pioner untuk ekstraksi lahan terbangun perkotaan dengan menggunakan saluran SWIR. Pengembangan indeks lahan terbangun ini masih perlu dikembangan untuk citra yang tidak mempunyai panjang gelombang SWIR. Tujuan penelitian ini adalah merumuskan kombinasi saluran terbaik dalam ekstraksi lahan terbangun dan area vegetasi serta menghitung kepadatan bangunan dan kerapatan vegetasi berbasis indeks. Penelitian ini menggunakan Citra Worldview-2 yang diperoleh dari Digital Globe Foundation untuk ekstraksi lahan terbangun dan kerapatan vegetasi. Normalized difference index digunakan sebagai formula dalam pembuatan indeks. Pemanfaatan semua saluran spektral dalam citra Worldview-2 digunakan untuk ekstraksi lahan terbangun dan kepadatan bangunan di perkotaan dengan PCA sebagai metode untuk penggabungan delapan saluran dalam Worldview-2. Saluran NIR 1 dan NIR 2 yang digabungkan dengan Saluran Merah menjadi pilihan untuk ekstraksi vegetasi. Proses trial dan error mewarnai pemilihan kombinasi saluran yang digunakan dan treshold yang digunakan untuk analisis biner dalam membedakan lahan terbangun dan non lahan terbangun serta area vegetasi dan area non vegetasi. Pemanfaatan unique identification (UID) digunakan untuk pembuatan grid berbasis raster dalam perhitungan kepadatan bangunan dan kerapatan vegetasi. Hasil penelitian menunjukkan bahwa indeks yang dibangun dengan PC2 dan NIR 1 serta PC2 dan NIR 2 mempunyai akurasi tinggi yaitu 94,43% untuk bangunan dan kombinasi indeks dari NIR1_Red mempunyai akurasi optimal yaitu 99,51% dan NIR2_Red mempunyai akurasi 92,87 untuk ekstraksi data vegetasi.  Urban phenomenon becomes a very interesting thing to be studied. The urban land use, land conversion, urban green space, are rapidly changing. Various methods were developed for urban built-up data extraction, such as multispectral classification, object-based approach, and index-based research. NDBI became one of pioneer indices for urban-built urban land extraction using SWIR band. The development of this built-up index is still required for images that do not have SWIR wavelengths. The study objectives were to select the best methods for built-up land and vegetation extraction and to calculate building density and index-based vegetation density. Worldview-2 image obtained from Digital Globe Foundation tested for built-up land data extracting and vegetation density analyzing. Normalized difference index formula is applied for combining and setting built-up land and vegetation indexes. Merger of Worldview-2 spectral imagery were using PCA method for extracting built-up land and calculating building density. Combining eight bands into eight new images that have different information from original images was done by PCA method.  NIR 1, NIR2, and Red bands are the perfect choice for vegetation extraction because near infrared characteristics have high reflections on vegetation. Selection of band combinations and selection of threshold values through trial and error processes to perceive the best index combinations and reasonable threshold values. Binary analysis is particularly useful for separating the built-up and non-built-up areas as well as vegetation and non-vegetation. The Unique identification (UID) technique used in estimating built-up and vegetation density from precisely classified images provided better and accurate assessment of built-up and vegetation density.  The results show that the built-up index involving PC2_NIR 1 and PC2_NIR 2 for the urban built land research achieved an optimal accuracy of 94, 43%. The best accuracy for vegetation data extraction was obtained from the combined NIR1_Red index with 99,51% and NIR2_Red values with an overall accuracy of 92,87%.   

scholarly journals Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at Plot Scale

2018 ◽  
Vol 10 (8) ◽  
pp. 1285 ◽  
Author(s):  
Reza Attarzadeh ◽  
Jalal Amini ◽  
Claudia Notarnicola ◽  
Felix Greifeneder
Keyword(s):  
Soil Moisture ◽  
Optical Data ◽  
Estimation Accuracy ◽  
Support Vector ◽  
Practical Applications ◽  
Initial Stage ◽  
Object Based ◽  
Single Polarization ◽  
Selection Of

This paper presents an approach for retrieval of soil moisture content (SMC) by coupling single polarization C-band synthetic aperture radar (SAR) and optical data at the plot scale in vegetated areas. The study was carried out at five different sites with dominant vegetation cover located in Kenya. In the initial stage of the process, different features are extracted from single polarization mode (VV polarization) SAR and optical data. Subsequently, proper selection of the relevant features is conducted on the extracted features. An advanced state-of-the-art machine learning regression approach, the support vector regression (SVR) technique, is used to retrieve soil moisture. This paper takes a new look at soil moisture retrieval in vegetated areas considering the needs of practical applications. In this context, we tried to work at the object level instead of the pixel level. Accordingly, a group of pixels (an image object) represents the reality of the land cover at the plot scale. Three approaches, a pixel-based approach, an object-based approach, and a combination of pixel- and object-based approaches, were used to estimate soil moisture. The results show that the combined approach outperforms the other approaches in terms of estimation accuracy (4.94% and 0.89 compared to 6.41% and 0.62 in terms of root mean square error (RMSE) and R2), flexibility on retrieving the level of soil moisture, and better quality of visual representation of the SMC map.

scholarly journals Electronic data collection for multi-country, hospital-based, clinical observation of maternal and newborn care: EN-BIRTH study experiences

2021 ◽  
Vol 21 (S1) ◽  
Author(s):  
Harriet Ruysen ◽  
◽  
Ahmed Ehsanur Rahman ◽  
Vladimir Sergeevich Gordeev ◽  
Tanvir Hossain ◽  
...  
Keyword(s):  
Quality Assurance ◽  
Data Collection ◽  
Data Quality ◽  
Clinical Observation ◽  
Data Extraction ◽  
Observation Data ◽  
Electronic Data ◽  
Concurrent Events ◽  
Maternal And Newborn ◽  
Selection Of

Abstract Background Observation of care at birth is challenging with multiple, rapid and potentially concurrent events occurring for mother, newborn and placenta. Design of electronic data (E-data) collection needs to account for these challenges. The Every Newborn Birth Indicators Research Tracking in Hospitals (EN-BIRTH) was an observational study to assess measurement of indicators for priority maternal and newborn interventions and took place in five hospitals in Bangladesh, Nepal and Tanzania (July 2017–July 2018). E-data tools were required to capture individually-linked, timed observation of care, data extraction from hospital register-records or case-notes, and exit-survey data from women. Methods To evaluate this process for EN-BIRTH, we employed a framework organised around five steps for E-data design, data collection and implementation. Using this framework, a mixed methods evaluation synthesised evidence from study documentation, standard operating procedures, stakeholder meetings and design workshops. We undertook focus group discussions with EN-BIRTH researchers to explore experiences from the three different country teams (November–December 2019). Results were organised according to the five a priori steps. Results In accordance with the five-step framework, we found: 1) Selection of data collection approach and software: user-centred design principles were applied to meet the challenges for observation of rapid, concurrent events around the time of birth with time-stamping. 2) Design of data collection tools and programming: required extensive pilot testing of tools to be user-focused and to include in-built error messages and data quality alerts. 3) Recruitment and training of data collectors: standardised with an interactive training package including pre/post-course assessment. 4) Data collection, quality assurance, and management: real-time quality assessments with a tracking dashboard and double observation/data extraction for a 5% case subset, were incorporated as part of quality assurance. Internet-based synchronisation during data collection posed intermittent challenges. 5) Data management, cleaning and analysis: E-data collection was perceived to improve data quality and reduce time cleaning. Conclusions The E-Data system, custom-built for EN-BIRTH, was valued by the site teams, particularly for time-stamped clinical observation of complex multiple simultaneous events at birth, without which the study objectives could not have been met. However before selection of a custom-built E-data tool, the development time, higher training and IT support needs, and connectivity challenges need to be considered against the proposed study or programme’s purpose, and currently available E-data tool options.

scholarly journals Evolution of WRF-HAILCAST during the 2014–16 NOAA/Hazardous Weather Testbed Spring Forecasting Experiments

2019 ◽  
Vol 34 (1) ◽  
pp. 61-79 ◽  
Author(s):  
Rebecca D. Adams-Selin ◽  
Adam J. Clark ◽  
Christopher J. Melick ◽  
Scott R. Dembek ◽  
Israel L. Jirak ◽  
...  
Keyword(s):  
Threshold Values ◽  
Severe Storms ◽  
Object Based ◽  
Storm Prediction ◽  
Horizontal Grid ◽  
Grid Based ◽  
Hazardous Weather

Abstract Four different versions of the HAILCAST hail model have been tested as part of the 2014–16 NOAA Hazardous Weather Testbed (HWT) Spring Forecasting Experiments. HAILCAST was run as part of the National Severe Storms Laboratory (NSSL) WRF Ensemble during 2014–16 and the Community Leveraged Unified Ensemble (CLUE) in 2016. Objective verification using the Multi-Radar Multi-Sensor maximum expected size of hail (MRMS MESH) product was conducted using both object-based and neighborhood grid-based verification. Subjective verification and feedback was provided by HWT participants. Hourly maximum storm surrogate fields at a variety of thresholds and Storm Prediction Center (SPC) convective outlooks were also evaluated for comparison. HAILCAST was found to improve with each version due to feedback from the 2014–16 HWTs. The 2016 version of HAILCAST was equivalent to or exceeded the skill of the tested storm surrogates across a variety of thresholds. The post-2016 version of HAILCAST was found to improve 50-mm hail forecasts through object-based verification, but 25-mm hail forecasting ability declined as measured through neighborhood grid-based verification. The skill of the storm surrogate fields varied widely as the threshold values used to determine hail size were varied. HAILCAST was found not to require such tuning, as it produced consistent results even when used across different model configurations and horizontal grid spacings. Additionally, different storm surrogate fields performed at varying levels of skill when forecasting 25- versus 50-mm hail, hinting at the different convective modes typically associated with small versus large sizes of hail. HAILCAST was able to match results relatively consistently with the best-performing storm surrogate field across multiple hail size thresholds.

TRIZ Application in Bionic Modeling for Lightweight Design of Machine Tool Column

2018 ◽  
Author(s):  
Shenggang Guo ◽  
Zhiling Yuan ◽  
Fenghe Wu ◽  
Yongxin Li ◽  
Shaoshuai Wang ◽  
...  
Keyword(s):  
Machine Tool ◽  
Lightweight Design ◽  
Biological Database ◽  
Biological Phenomenon ◽  
Bionic Design ◽  
Evaluation Theory ◽  
Column Structure ◽  
Object Based ◽  
Heavy Machine ◽  
Selection Of

The selection of biomimetic prototypes mostly depends on the subjective observation of a designer. This research uses TRIZ to explore some inferential steps in bionic design of the heavy machine tool column. Conflict resolution theory of TRIZ is applied to describe improved and deteriorated parameters and a contradiction matrix is used to obtain recommended inventive principles. A reference table of solutions corresponding to the biological phenomenon and TRIZ solutions is formed to expedite retrieving the biomimetic object. Based on the table, herbaceous hollow stem is selected to imitate column structure. Four kinds of plant are chosen from the biological database. To select the best from four candidates, a bionic ideality evaluation index is proposed based on similarity analysis and ideality evaluation theory in TRIZ. Thus, the bionic effect can be described and compared quantitatively. Bionic configuration is then evolved concerning manufacturing requirements. Size optimization of stiffener thicknesses is implemented finally, and satisfactory results of the lightweight effect is obtained.

scholarly journals Selection of Fuzzy Controller Membership Functions Based on Adaptive Gaussian Cloud Transform

2018 ◽  
Vol 36 (3) ◽  
pp. 439-447
Author(s):  
Yong Wang ◽  
Cong Li ◽  
Hanqiao Huang ◽  
Huan Zhou
Keyword(s):  
Fuzzy Controller ◽  
Membership Functions ◽  
Threshold Values ◽  
Coverage Area ◽  
Concept Hierarchy ◽  
Response Characteristics ◽  
Sample Data ◽  
Cloud Transform ◽  
Six Degree Of Freedom ◽  
Selection Of

Aiming at the boundedness of existing methods of selecting membership functions, an adaptive Gaussian cloud transform algorithm which is guided by the threshold values of hybridization degree is proposed to construct concept hierarchy from original sample data, and then the number, shape and coverage area of membership functions can be derived from the distribution of Gaussian cloud. To test and verify the effectiveness of membership function that is extracted based on adaptive Gaussian cloud transform algorithm, a six-degree-of freedom model of unmanned aerial vehicles(UAV) is constructed, and a fuzzy controller of pitching angle is established with the platform of Simulink. The simulation results show that the fuzzy controller which includes membership functions derived from the distribution of Gaussian cloud transform can achieve perfect control performance of pitching angle and meanwhile obtain good dynamic response characteristics.

scholarly journals Dimensions and Sub-Dimensions for the Evaluation of M-Learning Apps for Children: A Review

2018 ◽  
Vol 7 (3.20) ◽  
pp. 291
Author(s):  
Azham Hussain ◽  
Emmanuel O.C. Mkpojiogu ◽  
Fa’alina Hassan
Keyword(s):  
Learning Process ◽  
User Satisfaction ◽  
Data Extraction ◽  
Past Research ◽  
Review Of Literature ◽  
Implementation Phase ◽  
Synthesis Strategy ◽  
Definition Of ◽  
Selection Of

The introduction and rapid growth of mobile learning applications (m-learning apps) has improved the role of teachers in facilitating the learning process especially among children. The learning experiences of children are enhanced and enriched with the use of m-learning apps for children. There are several m-learning apps developed for children in the market today, however, some of these apps do not succinctly support and adequately assist in the learning process and educational endeavors and quest of these young minds. In this paper, a systematic review of literature was conducted to assess past research and studies on usability dimensions and sub-dimensions utilized in evaluating children’s m-learning apps. The systematic literature review consisted of the following approach: the definition of search strategy, selection of primary studies, data extraction, and implementation of synthesis strategy and lastly, the presentation of findings. The result of the review reveals that effectiveness, efficiency, learnability, and user satisfaction (with their corresponding sub-dimensions) were the top four usability dimensions used in the evaluation of m-learning apps for children. In addition, the works reviewed showed that usability evaluation is prominent only during the implementation phase of the applications’ development.  

Neural Mechanisms of Visual Attention: Object-Based Selection of a Region in Space

2000 ◽  
Vol 12 (supplement 2) ◽  
pp. 106-117 ◽  
Author(s):  
Catherine M. Arrington ◽  
Thomas H. Carr ◽  
Andrew R. Mayer ◽  
Stephen M. Rao
Keyword(s):  
Visual Attention ◽  
Spatial Attention ◽  
Brain Activity ◽  
Temporal Cortex ◽  
Brain Structures ◽  
Brain Regions ◽  
Brain Areas ◽  
Unbounded Region ◽  
Object Based ◽  
Selection Of

Objects play an important role in guiding spatial attention through a cluttered visual environment. We used event-related functional magnetic resonance imaging (ER-fMRI) to measure brain activity during cued discrimination tasks requiring subjects to orient attention either to a region bounded by an object (object-based spatial attention) or to an unbounded region of space (location-based spatial attention) in anticipation of an upcoming target. Comparison between the two tasks revealed greater activation when attention selected a region bounded by an object. This activation was strongly lateralized to the left hemisphere and formed a widely distributed network including (a) attentional structures in parietal and temporal cortex and thalamus, (b) ventral-stream object processing structures in occipital, inferior-temporal, and parahippocampal cortex, and (c) control structures in medial-and dorsolateral-prefrontal cortex. These results suggest that object-based spatial selection is achieved by imposing additional constraints over and above those processes already operating to achieve selection of an unbounded region. In addition, ER-fMRI methodology allowed a comparison of validly versus invalidly cued trials, thereby delineating brain structures involved in the reorientation of attention after its initial deployment proved incorrect. All areas of activation that differentiated between these two trial types resulted from greater activity during the invalid trials. This outcome suggests that all brain areas involved in attentional orienting and task performance in response to valid cues are also involved on invalid trials. During invalid trials, additional brain regions are recruited when a perceiver recovers from invalid cueing and reorients attention to a target appearing at an uncued location. Activated brain areas specific to attentional reorientation were strongly right-lateralized and included posterior temporal and inferior parietal regions previously implicated in visual attention processes, as well as prefrontal regions that likely subserve control processes, particularly related to inhibition of inappropriate responding.

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